D5.5 Business model storylines for sustainable CS exploitation in the Living Labs

This project has received funding from the European Union’s Horizon 2020 research and innovaƟon programme under grant agreement No 101037293 Deliverable D5.5 Business model storylines for sustainable CS exploitation in the Living Labs June 2025 This project has received funding from the European Union’s Horizon 2020 research and innovaƟon programme under grant agreement No 101037293 Innovang Climate services through Integrang Scienfic and local Knowledge Deliverable Title: Business model storylines for sustainable CS exploitaon in the Living Labs Author(s): Alexandros Ziogas, Apostolos Tzimas Contribung Authors(s): Schalk Jan van Andel, Annelies Broekman, Paolo Mazzoli, Györgyi Bela, Charles Wamucii, Aristea Balamatsia, Vakho Chishvili, Daniele Castellana Date June 2025 Suggested citaon: Ziogas A., Tzimas A., van Andel Schalk Jan et al., 2025: Business model storylines for sustainable CS exploitaon in the Living Labs, I-CISK Deliverable 5.5, Available online at www.icisk.eu/resources Availability: ☒ PU: This report is public ☐ CO: Confidenal, only for members of the consorum (including the Commission Services) Document Revisions: Author Revision Date Alexandros Ziogas, Apostolos Tzimas First dra 16 April 2025 Micha Werner and Paolo Mazzoli Revisions April 2025 Micha Werner Revisions May 2025 Alexandros Ziogas, Apostolos Tzimas Final version 6/6/2025 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs i Table of Contents Table of Contents .................................................................................................................................................. i List of Figures ............................................................................................................... ........................................ iii List of Tables ........................................................................................................................................................ vi Acronyms ........................................................................................................................................................... viii Summary .............................................................................................................................................................. 1 1 Introducon ................................................................................................................................................. 2 2 Theorecal background ............................................................................................................................... 3 2.1 Defining the I-CISK services value model ............................................................................................... 3 3 Business model storyline for the Rijnland Living Lab (Netherlands) ........................................................... 6 3.1 Background and context ......................................................................................................................... 6 3.2 First iteraon: Defining boundaries of analysis ...................................................................................... 7 3.3 Second iteraon: Understanding the value chain .................................................................................. 9 3.4 Third iteraon: Analyse the benefits .................................................................................................... 12 3.5 Fourth iteraon: Analysis beyond the defined boundaries ................................................................. 13 4 Business model storyline for the Andalucía Living Lab (Spain) ................................................................. 14 4.1 Background and context ....................................................................................................................... 14 4.2 First iteraon: defining boundaries of analysis .................................................................................... 18 4.3 Second iteraon: understanding the value chain ................................................................................ 22 4.4 Third iteraon: Analyse the benefits ...................................................................................................... 1 4.5 Fourth iteraon: Analysis beyond the defined boundaries ................................................................... 2 5 Business model storyline for the Emilia Romagna Living Lab (Italy) ........................................................... 3 5.1 Background and context ......................................................................................................................... 3 5.2 First iteraon: Defining boundaries of analysis ...................................................................................... 4 5.3 Second iteraon: Understanding the value chain .................................................................................. 8 5.4 Third iteraon: Analyse the benefits .................................................................................................... 11 5.5 Fourth iteraon: analysis beyond the defined boundaries .................................................................. 15 5.5.1 Market Segmentaon .................................................................................................................... 15 5.5.2 Market Analysis ............................................................................................................................. 19 5.5.3 Analysing trends and responding to opportunies and threats ................................................... 21 5.5.4 Esmang the market growth rate ............................................................................................... 22 5.5.5 Compeon and profitability ........................................................................................................ 22 6 Business model storyline for the Budapest Living Lab (Hungary) ............................................................. 30 6.1 Background and context ....................................................................................................................... 30 6.2 First iteraon: Defining boundaries of analysis .................................................................................... 31 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs ii 6.3 Second iteraon: Understanding the value chain ................................................................................ 31 6.4 Third iteraon: analyse the benefits .................................................................................................... 35 6.5 Fourth iteraon: analysis beyond the defined boundaries .................................................................. 36 6.5.1 Primary market segment idenficaon ......................................................................................... 36 6.5.2 Implicaons for Market Analysis ................................................................................................... 37 6.5.3 Open Source Strategy and Future Potenal .................................................................................. 37 7 Business model storyline for the Crete Island Living Lab (Greece) ........................................................... 39 7.1 Background and context ....................................................................................................................... 39 7.2 First iteraon: Defining boundaries of analysis .................................................................................... 40 7.3 Second iteraon: Understanding the value chain ................................................................................ 46 7.4 Third iteraon: Analyse the benefits .................................................................................................... 49 7.5 Fourth iteraon: analysis beyond the defined boundaries .................................................................. 53 7.5.1 Defining the market boundaries ................................................................................................... 53 7.5.2 Market Analysis ............................................................................................................................. 60 8 Business model storyline for the Alazani River basin Living Lab (Georgia) ............................................... 72 8.1 Background and context ....................................................................................................................... 72 8.2 First Iteraon: Defining Boundaries of Analysis ................................................................................... 72 8.3 Second iteraon: Understanding the value chain ................................................................................ 77 8.4 Third Iteraon: Analyse the benefits .................................................................................................... 80 8.5 Fourth Iteraon: Analysis beyond the defined boundaries ................................................................. 83 9 Business model storyline for the Lesotho Living Lab ................................................................................ 85 9.1 Background and context ....................................................................................................................... 85 9.2 First iteraon: defining boundaries of analysis .................................................................................... 87 9.3 Second iteraon: Understanding the value chain ................................................................................ 90 9.4 Third iteraon: Analyse the benefits .................................................................................................... 92 9.5 Fourth iteraon: analysis beyond the defined boundaries .................................................................. 93 10 Concluding remarks ................................................................................................................................... 94 11 References ................................................................................................................................................. 96 Annex A – Assessments on Value esmaon from the Budapest LL ................................................................ 97 Annex B – Quanfy the benefits of the CS for the Water Sector - Crete Island LL ......................................... 103 Annex C – Quanfy the benefits of the CS for the Tourism Sector - Crete Island LL ...................................... 110 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs iii List of Figures Figure 1: Business Model components ................................................................................................................ 3 Figure 2: Process for value chain analysis ........................................................................................................... 5 Figure 3: Seasonal streamflow predicon of Rhine River at Lobith staon, with user-defined alert levels indicated. ............................................................................................................................................................. 6 Figure 4: Seasonal predicon of potenal precipitaon deficit over the Netherlands, zooming in to Rijnland. Colours on the map correspond to user-defined case drought alert levels. The graph below the map shows the observaon-based and forecast potenal precipitaon deficit for the locaon selected with point on the map. ............................................................................................................................................................................. 7 Figure 5: The command area of Rijnland, with key structures indicated for water system operaon during droughts. ............................................................................................................................................................. 8 Figure 6: Understanding of the value chain for the Climate Services developed in the Rijnland Living Lab (Netherlands). .................................................................................................................................................... 11 Figure 7: Screenshot of the visualizaon of CS1 – seasonal predicons. .......................................................... 14 Figure 8: Screenshot of the visualizaon of CS2 – 10 years climate impact projecons (mock up). ................ 15 Figure 9: Screenshot of the visualizaon of CS3 – historical climate maps for comparave analysis. ............ 16 Figure 10: Screenshot of the visualizaon of CS3 – local meteorological staons historical data. .................. 16 Figure 11: screenshot of the visualizaon of CS3 – local meteorological staons historical. ........................... 17 Figure 12: screenshot of the visualizaon of CS5 – hydrogeological characterizaon of groundwater bodies. ........................................................................................................................................................................... 18 Figure 13:The region of Los Pedroches, Córdoba, Spain. Source: prepared by the authors using data collected from IGN, EEA and MITECO. .............................................................................................................................. 19 Figure 14: Understanding the value chain for Climate Services CS1, CS2 & CS3 (par. 4.2) developed in the Andalucía Living Lab (Spain). ............................................................................................................................... 0 Figure 15: Demand for climate services offered by the I-CISK project based on economic sector (note that SC is CS in Spanish, denong the five CS developed in the project). ....................................................................... 1 Figure 16: Example of Climate Service landing page and buons to select specific river staon to provide discharge forecast. .............................................................................................................................................. 3 Figure 17: Example of forecast discharge displays selectable through the GUI; custom forecast window on a daily basis (upper) to be matched with crical thresholds like minimum environmental flow, along with cumulated values (lower) on a monthly basis relevant for users that can manage storage systems. ............... 4 Figure 18: Castalllarano weir on the Secchia River, which spans the upper provinces of Reggio Emilia and Modena in the Emilia Romagna Region, Italy. .................................................................................................... 5 Figure 19: Understanding of the proposed value chain for the Climate Services developed in the Emilia Romagna Living Lab (Italy). ................................................................................................................................ 10 Figure 20: Competor Idenficaon Framework esmated for the ITA LL prototyped CS. ............................. 24 Figure 21 – Compeve Strength Heatmap for the ITA LL prototyped CS. ...................................................... 25 Figure 22: Risk matrix. Source: (Day 2007), for the ITA prototyped CS. ........................................................... 29 Figure 23: Urban heat map CS, Erzsébetváros district, Budapest. .................................................................... 30 Figure 24: Understanding of the proposed value chain for the Climate Services developed in the Budapest Living Lab (Hungary). ......................................................................................................................................... 34 Figure 25: Screen-shot of the I-CISK CS developed for the Tourisc Sector in the island of Crete under a mulsectoral approach towards the support of the tourism sector – seasonal forecasng of extreme heat and precipitaon as well as aesthec indicators for outdoor acvies and energy needs. .................................... 39 Figure 26: Screen-shot of the I-CISK CS developed for the Water Managers on the island of Crete under a mulsectoral approach towards the support of the tourism sector – Wet period total volume: current forecast and history of forecasng. ........................................................................................................................... ...... 40 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs iv Figure 27: Potamon (Amari) dam reservoir (photo by Organizaon for the Development of Crete – OAK). ... 40 Figure 28: Port of Rethymno (photo by Wikimedia commons, license CC-BY-SA-4.0,3.0,2.5,2.0,1.0). ............ 43 Figure 29: Elounda resort (photo from site: hps://www.elounda-sa.com/). ................................................. 45 Figure 30: Understanding of the value chain for the Climate Services developed in the Crete Island Living Lab (Greece). ............................................................................................................................................................ 48 Figure 31: Market segments mapping for I-CISK climate services developed in the Crete LL. ......................... 54 Figure 32: Tourism revenues in million euros by EU member state 2022 (Source: Eurostat). ......................... 61 Figure 33: Esmated market segment metrics for various scenarios. .............................................................. 64 Figure 34: Average annual loss (%) as a drought-induced increase in water abstracon for public water supply in European Union in NUTS-2 level (Source: European Drought Risk Atlas – Joint Research Center EU). ....... 65 Figure 35: Drought risk for water supply between current and projected climate condions. Risk is measured as average annual increase in drought-induced abstracon compared to the average expected value under current climate condions. Results of future simulaons forced with 11 climate models in RCP 4.5 and RCP 8.5 are averaged for each warming level (+1.5 °C, +2.0 °C). The analysis was conducted at NUTS-2 level (Source: European Drought Risk Atlas – Joint Research Center EU). .............................................................................. 65 Figure 36: Annual projected change in Standardized Precipitaon Index (SPI-6) in Europe, relave to 19862005, under 1.5°C global warming scenario (Source: Copernicus Interacve Climate Atlas). .......................... 66 Figure 37: Sources of drinking water. Source: (EurEau, 2017) .......................................................................... 67 Figure 38: Sources for drinking water in Member States (Data for 2011 to 2013). Source: (EC, 2016) ........... 68 Figure 39: Canvas of opportunies for I-CISK climate services. ........................................................................ 69 Figure 40: Esmated market segment metrics for various scenarios. .............................................................. 71 Figure 41: Streamflow network and Basin Boundaries in the Alazani-Iori Basin. The map shows the main river systems and sub-basins, highlighng the hydrological complexity of the region. ............................................ 73 Figure 42: Hydrological Staons and River Network in the Alazani-Basin. The map shows acve and historical hydrological staons, river streams, and basin boundaries. ............................................................................. 74 Figure 43: Meteorological Staons in the AlazaniBasin. The map shows acve and historical meteorological staons, river streams, and basin boundaries. ................................................................................................. 74 Figure 44: Understanding of the Value Chain for the Climate Services developed in Alazani river basin Living Lab (Georgia). .................................................................................................................................................... 79 Figure 45: Agro-ecological zones of Lesotho. Source: Lesotho Ministry of Public Works and Transport. ........ 85 Figure 46: Screenshots from the Impact-Based Forecasng portal, a climate service developed for drought risk monitoring in Lesotho. (a) The portal displays a warning when one or more districts are idenfied as being at drought risk based on automacally retrieved global data. (b) When users set a trigger using naonal data from the Lesotho Meteorological Services, the portal generates an alert for the specified district(s) and automacally sends noficaons to relevant stakeholders. ............................................................................. 86 Figure 47: Understanding of the value chain for the Climate Services developed in Lesotho Living Lab. ........ 91 Figure 48: Ortho and thermal photo GIS layers of Budapest LL climate service: 1st column pavements and roads in VII district; 2nd column pavements and roads in VI district. ......................................................................... 99 Figure 49: Coverage percentages and Temperature distribuon, as esmated through the Budapest LL climate service: 1st column pavements and roads in VII district; 2nd column pavements and roads in VI district. ....... 99 Figure 50: Thresholds for water stored volumes defining the “states of the world” for the Amari dam reservoir defined as: (a) water volume and (b) water level. .......................................................................................... 105 Figure 51: Payoff distribuon according to three different end users. ........................................................... 106 Figure 52: Scenario 1: (a) States of the world and (b) monthly payoff. (decision periods and forecasng period are marked on the graph). ............................................................................................................................... 107 Figure 53: Scenario 2: (a) States of the world and (b) monthly payoff. (decision periods and forecasng period are marked on the graph). ............................................................................................................................... 108 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs v Figure 54: Scenario 3: (a) States of the world and (b) monthly payoff. (decision periods and forecasng period are marked on the graph). ............................................................................................................................... 109 Figure 55: Adapve capacies of the selected sectors (A) and sectoral efficiencies for the selected sectors (B). These capacies are influenced by the availability and relevance of climate services (CS), the meliness of access to CS products, the proximity to CS providers, the type of each sector, and the resources inherent to those sectors. The sectoral efficiencies are determined by the relaonship between the adapve capacies to meet resource demands within each sector against the maximum resource demand (Biella et al. 2024). ... 111 Figure 56: Changes in sectoral scarcity indices. ............................................................................................. 112 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs vi List of Tables Table 1: Scaling of benefits ............................................................................................................................ ...... 4 Table 2: Group Aracveness Scorecard – for the ITA LL prototyped CS. ........................................................ 17 Table 3: cost breakdown structure for the ITA prototyped CS ......................................................................... 26 Table 4: Revenue projecons for the ITA LL prototyped CS. ............................................................................. 27 Table 5: Assessment of the intended market. Source: (Day 2007), adapted to the ITA LL prototyped CS. ...... 28 Table 6: Assessment of the product or service. Source: (Day 2007), adapted to the ITA LL prototyped CS. ... 28 Table 7: Gains by the use of the CS for the three climac scenarios examined ............................................... 50 Table 8: Stakeholders idenfied as potenal market segments for I-CISK climate service (Crete Island LL) ... 55 Table 9: Group Aracveness Scorecard. ......................................................................................................... 58 Table 10: Esmated Naonal Tourism Organizaon budgets and tourism contribuon to GDP across EU. ... 61 Table 11: Potenal Size of the Target Group for TMOs and DMOs for the EU Context. ................................... 63 Table 12: Potenal Size of the Primary Target Group of Reservoir Operators and Bulk Water Management Authories for the EU Context. ......................................................................................................................... 70 Table 13: Payoff Matrices According to the End Users (Georgia LL). ................................................................ 81 Table 14: Payoff Gains Under the Three Scenarios Examined (Georgia LL). ..................................................... 82 Table 15: Characteriscs of the business model storylines developed for the I-CISK CSs within each LL. ....... 94 Table 16: Payoff matrices according to the end users. ................................................................................... 106 Table 17: Payoff gains under the three scenarios examined. ......................................................................... 109 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs vii D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 5 strong social/environmental or gains other than economic (e.g. reputaonal). This ered approach allows for the assessment of a storyline for every CS, independent of factors which may confine the extend of analysis such as the type of value and the beneficiaries which are associated with the CS. This offers flexibility given the variability and number of CS developed under the different LLs within the I-CISK project (i.e. not all of the CS developed can or need to reach the final er, the fourth iteraon level, see Figure 2). Figure 2: Process for value chain analysis The assessment towards the business model storylines through the ered approach presented in the previous, is described in the following chapters for each of the I-CISK LLs. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 6 3 Business model storyline for the Rijnland Living Lab (Netherlands) 3.1 Background and context The CS that has been co-developed in the Rijnland LL (Netherlands) addresses drought challenges in the present and future climate. The local water authories seek to improve operaonal migaon measures and develop long term adaptaon strategies, together with and mely communicated to actor groups that are using the surface water system. As described in Deliverable D1.1. (Masih et al., 2022), the Rijnland LL is situated on the west-coast of the Netherlands, on the North Sea, between the cies of The Hague and Amsterdam. The Rijnland water authority (hps://www.rijnland.net/) is an important instuon responsible for water management in this region. The LL area is mostly flat and below sea level. Extensive dunes along the coast are important for protecon against the sea, but also for water supply to the cies through Managed Aquifer Recharge schemes. The surface water system serves both irrigaon and drainage, with pumping staons discharging excess water to interconnected canals and out to the North Sea. During dry spells fresh water is let in from the Rhine River, and supplied to low-lying polders through the same interconnected canals. However, when the discharge of the River Rhine is too low because of a drought in the Rhine basin, salt intrusion from the North Sea may reach the fresh water intake of Rijnland at Gouda. This intake has to then temporarily be stopped to avoid too high a salinity in the Rijnland surface water for agricultural use, and instead an alternave inlet locaon more upstream is acvated. This auxiliary inlet is, however, has a reduced capacity such that salinity in the Rijnland area may gradually go up. A second challenge with drought can come from a potenal precipitaon deficit over the area itself, which may cause drought damage to peat embankments becoming unstable, and, especially when freshwater intake is limited, may also lead to increased surface water salinity levels. To reduce the salinity load to the system, ship lock operaons from the Noordzeekanaal, are then limited for water tourism as one of the first migaon measures, as saline water enters the system during locking processes. I-CISK co-developed with the Rijnland water authority, water tourism actors, and agricultural sector representaves, a climate service that aims to provide mely pre-alerts of possible upcoming drought, to opmise and beer prepare for migaon measures, and for the water authority to provide mely alerts to water users of these measures and their impacts (Figure 3 and Figure 4). Figure 3: Seasonal streamflow predicon of Rhine River at Lobith staon, with user-defined alert levels indicated. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 7 Figure 4: Seasonal predicon of potenal precipitaon deficit over the Netherlands, zooming in to Rijnland. Colours on the map correspond to user-defined case drought alert levels. The graph below the map shows the observaon-based and forecast potenal precipitaon deficit for the locaon selected with point on the map. 3.2 First iteraƟon: Defining boundaries of analysis At this stage, the boundaries of the analysis for the use case are clearly set. These refer to:  The geographical and sectoral focus  The targeted users of the developed service  The targeted problems the proposed service aim to solve  The current pracces in place and the need for having an advanced soluon to address these problems The user-focused approach (boom-up approach) is described in the following for the main sector that this service addresses, leading to the 1st iteraon step of the assessment (esmaon of the value proposion). Water management sector - opmisaon, preparaon, and communicaon of operaonal drought measures and awareness raising and strategizing drought risk management in a changing climate Locaon: The Rijnland water system is situated in mid-western part of the Netherlands, between Amsterdam and Den Haag (Figure 5). The water system mainly consists of inter-connected surface water canals serving agricultural areas, commercial and tourism shipping, nature areas, and municipalies (receiving waters of waste water treatment plants). The climate of Rijnland, the Netherlands, is temperate oceanic climate (Köppen classificaon: C), with rain throughout the year. The Rijnland area receives a yearly average of 850 mm precipitaon, occurring throughout the months of the year, with reference evapotranspiraon at 550 mm per year. In summer months, however, due to higher temperatures, potenal evapotranspiraon may exceed precipitaon. Climate change is projected to lead to higher D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 8 temperatures, more pronounced (extreme) events, both wet and dry, and sea level rise. Figure 5: The command area of Rijnland, with key structures indicated for water system operaon during droughts. End User(s): The water management organisaon responsible for design, maintenance, and operaon of the water system is the Rijnland water authority (Hoogheemraadschap Rijnland). Operaon of regulang structures, pumping staons and inlets, is one of the key tasks to maintain the area-average surface water level within a narrow band of 10 cm target level and the salinity level below high agricultural standards. Minimising too high water-levels (floods), and high salinity periods (droughts), while ensuring bank stability (flood safety) and ship lock operaon for ship navigaon, is supported by a decision support system with hydrometeorological observed and forecast data and hydrological and system operaon models as input. Challenge: While flood risk management and real-me services for flood control have tradionally been at the forefront of efforts of the water authority, recent droughts (e.g. in 2018) and climate change outlooks have strengthened the acvies towards enhancing operaonal and strategic drought planning services. The challenge idenfied is twofold: operaonal drought migaon measures require preparaon me and me to communicate to affected water users beyond the lead me of decision support services currently in place (2 days automac to max 2 weeks manual), and developing smart longterm drought adaptaon measures in a changing climate requires acve engagement of water users in the area and integraon with their adaptaon strategies. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 9 Current pracces in place (AS-IS Scenario): Currently, in the summer months, April to September, an expert-based drought report is collated on monthly (in case of no indicaon of upcoming drought) to weekly intervals (in case of expected or ongoing drought). This report contains the current situaon of the water system in the command area, as well as the discharge in the River Rhine as an indicator for securing low-salinity freshwater at the inlet; cumulave potenal precipitaon deficit, as an indicator for local drought and related potenal bank stability problems and fresh water needs for agriculture and keeping salinity in check; and salinity level observaons at several locaons in the water system, together with a local and naonal outlooks up to a maximum of two weeks of the discharge in the Rhine and potenal precipitaon deficit. The report starts with a general drought status. During ongoing drought events, an overview of acve migaon measures, including limitaons of ship lock operaons affecng water tourism (thus reducing the salinity load) and stopping of the water inlet at Gouda and acvang the auxiliary but reduced capacity fresh water inlet via Bodegraven (thus affecng agricultural water users). Soluon (User Requirements) ID User requirements As a <ROLE>, I would like to <GOAL> to <BENEFIT> NL1 As a water manager… …I would like to have regular (weekly) updates of the forecasted potenal precipitaon deficit for the coming month, from April to September... …to mely prepare for drought migaon measures and engage and inform actors involved and affected (dike inspecon staff, water tourism and agricultural water users). NL2 As a water manager… …I would like to have regular (weekly) updates of the forecasted Rhine river discharge at Lobith for the coming month… …to mely prepare for drought migaon measures and engage and inform actors involved and affected (neighbouring water authories, water tourism and agricultural water users) Soluon (TO-BE Scenario): I-CISK aspires to expand the informaon base for Rijnland water authories’ drought management by incorporang sub-seasonal to seasonal forecasts (1-week to 7 months lead me) of local potenal precipitaon deficit and streamflow of Rhine river at Lobith into a climate service for drought management. Combined with pre-alert (awareness) probabilisc thresholds the climate service would also provide operaonal drought pre-alerts in the drought-prone season from April to December. Value Proposion (Goal of the service): Timely forecasts of possible upcoming drought will enable the Rijnland water authority to opmise and plan beer for operaonal drought migaon measures and communicate these measures and their adverse effects to water users in the area. When combined with user-centred climate change informaon on droughts, the climate service will also foster acve engagement of water users in discussing and developing adaptaon strategies. This service will contribute to increased drought resilience and climate change adaptaon of the Rijnland area and water system actors as a whole. 3.3 Second iteraƟon: Understanding the value chain To understand how the use of the CS for providing drought alerts helps actors along the value chain to address the challenges they face at an operaonal level, a descripon of the value chain is built in a 4-er analysis D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 10 based on the methodological framework described in MS26 (Guidelines for Value Chain assessment, June 2024), which is summarised in Figure 6. The goal at this point is the analysis to be sufficiently informed to enable the primary user to develop the understanding of the economic benefits and to complete a User Story. Tier 1 is the “supplier” of the climac data i.e. the seasonal forecasng data of discharge, temperature (for esmang potenal reference evapotranspiraon), and precipitaon. ECMWF as a pan-European and global met-service (meteorological service provider) generates and provides state-of-the-art climac data of seasonal meteorological forecasts which may be used by downstream services “as is”, post-processed e.g. in this case bias corrected by SMHI (Swedish naonal hydrometeorological service provider with Pan-European and Global R&D and products), and/or are repurposed through impact modelling (in present case SMHI by using the hydrological model E-HYPE to create seasonal forecasng of river flows) which widens the services of climac data. Past and present observed local hydrometeorological observaons for LL Rijnland, to provide inial condions of the seasonal drought forecast and real-me context with the present situaon are provided by KNMI (naonal met-service of the Netherlands). Their benefit from providing climac data could be: (a) scienfic: receiving feedback which allows to enhance their data quality, (b) economic, through the provision of data services and (c) business-oriented, by achieving reputaonal gains and expanding their partnerships and data provision services. Tier 2 is the “primary user” (this is also referred to as intermediary user) of the climac service. 52N and IHE Del co-develop within the Rijnland LL MAP a drought alert service that transforms the value of the climac service, acng as knowledge purveyor between the supplier (er 1) and the end user (er 3) of the climac service. Through this process, 52N (a Spaal Informaon Research, non-profit company) enhances its ability to provide added value (innovaon gains), develops services which increase its market share and provide addional revenue (economic gains) and builds on its reputaonal profile which also supports the expansion of partnerships (entrepreneurship gains). IHE Del, as an academic instute, enhance their research capacity in the field of climate services, with gained knowledge and experience also feeding into their educaonal programmes (MSc and PhD programmes in the water sector), achieving reputaonal gains both as research partner and educaonal instute. Tier 3 is the “secondary user” i.e. the end user of the service provided by the primary user. The Water Authority, Hoogheemraadschap Rijnland (Rijnland), may add the developed pilot CS to their informaon and communicaon sources they use for drought management, with the added lead me of drought pre-alerts beyond two weeks being the key added value. This allows Rijnland to beer prepare for and opmise operaonal water management measures that migate impact of drought on bank stability and water salinity. This increases the effecveness and efficiency of these measures, reducing costs and increasing compliance with the duty of care for the water system and its users. As these drought migaon measures impact water tourism acvies, e.g. boang, and agriculture, e.g. horculture and crop growers, earlier communicaon of upcoming drought and potenal water management measures, increases trust in the water authority with these users (reputaonal gain), reducing complaints (cost reducon), and enables water users to, in turn, beer plan for and opmise their own drought event management measures. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 11 Figure 6: Understanding of the value chain for the Climate Services developed in the Rijnland Living Lab (Netherlands). D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 12 Tier 4 includes the other economic sectors which are associated indirectly with the Rijnland water system's drought management as well as the wider “cizens, society and the environment” in the Rijnland area, which are the end beneficiaries of the climac service. Beer services (water, shipping, agriculture) support Rijnland's connued aracveness for socio-economic acvies and living (reputaonal gains) which may support increase of or provide stability to the region's economy in a changing climate with increasing pressure on the water system. The cizens and society enjoy the end result of the climate service as enhanced nonsaline water availability, navigability, and beer environmental condions. Due to earlier and beer drought migaon decisions and communicaon, they may enjoy less disrupon of tourism acvies and reduced agricultural revenue losses (economic gains). Further, beer water management, improved environmental condions, and enhanced water transport-infrastructure condions translate into broader societal gains. 3.4 Third iteraƟon: Analyse the benefits Up to this point, the analysis has focused on understanding and seng out the perimeter of the case analysis. The next stage is to analyse the benefits idenfied and quanfy them where possible. It is noted that the analysis presented in the following, targets the assessment of part of the value idenfied in the 2nd Tier of the value chain analysis. Where the analysis can demonstrate potenal economic gains or avoided costs, quanficaon is most preferable to lead to actual financial benefits However, at this point economic gain is not very clear and is also mixed with social and environmental gains. This is why the evaluaon of the benefits of the service is based on a qualitave assessment. Water management sector – qualitave assessment of gains The water authority of Rijnland sees the potenal to benefit from 2-to 4-week lead me drought alerts by;  improved planning of staff for inspecon of embankments (in the summer holiday season this is an extra challenge);  improved and more mely discussion with neighbouring water authories on acvang the prearranged alternave fresh-water intake point further upstream along the River Rhine and transport route from the intake point to the Rijnland water system;  increasing efficiency and decreasing adverse effects of drought migaon measures (e.g. delaying having to stop the intake at Gouda because of too high salinity by reducing the intake earlier and scheduling reduced shipping-lock operaons),  improving reputaon and reducing complaints by earlier communicaon with water users, e.g. water tourism and agriculture. While a rough quantate esmate of some of these gains could be made (e.g. cost reducon on staff me handling complaints), for others, like reputaon gain, this is not possible. We therefore provide a qualitave assessment (see Table 1 for the scale) With a programme of embankment strengthening being implemented in parallel with this project, the water authority expects the need for extensive staff numbers for dike inspecon to have reduced, leading the expected gain of this aspect to be: LOW The expected benefit of having more me for discussing (negoang) on when and how to start regional drought migaon measure of the alternave (but reduced) water intake, is considered to be: D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 13 MODERATE to HIGH . The added value of more in advance alerts and communicaon with water users in the area, thus improving reputaon and trust and reducing complaints, which has been expressed as a concern in earlier events such as the 2018 drought, is considered as: HIGH . Water tourism sector – qualitave assessment of gains The water tourism will be aided mainly with earlier decision on the change of boang plans and routes, thus avoiding waing mes in boat jams at ship locks. This constutes monetary value in reduced fuel and expenses because of delays and detour and incurred costs at delayed or cancelled accommodaon for example. However, as these acvies are in free me, not in work me, the expected benefits are assessed as: MODERATE . Agricultural sector – qualitave assessment of gains The agricultural sector can gain from opmised and beer planned drought migaon acons they take themselves, and subsequently cost savings in reducing crop damage, increasing revenues. With the seasonal forecasts being probabilisc, however, quanficaon of these mixed monetary benefits is complex and uncertain. We therefore start at idenfying the potenal qualitave added benefit as being: HIGH . 3.5 Fourth iteraƟon: Analysis beyond the defined boundaries The climate service that has been co-developed in the Rijnland LL primarily targets the command area of the Rijnland water authority, meaning that the LL is idenfied as the primary market segment for the service. The Rijnland water authority is the primary end user idenfied. Although, the potenal added value of the drought alert pilot applicaon beyond the confines of the command area of the Rijnland water authority is promising because other local water authories throughout the Netherlands face similar challenges with drought. Since the primary market segment is small – and given the fact that this market is not the key exploitaon objecve of the developed CS, a full Market Analysis is not considered relevant. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 14 4 Business model storyline for the Andalucía Living Lab (Spain) 4.1 Background and context For the Spanish case, five complementary CS focussing on drought were developed. These address four main economic sectors: Natural Park managers, livestock farmers (Iberian pork and milk producon) and olive oil producers. The results were obtained through acve engagement of mulple actors during the first three years of project duraon, thus providing a consolidated percepon of the main interests, stakes and raonale of local decision-making processes. The analysis revealed that no commercial use is envisioned for the CS produced by the Spanish case, provided that the sustainability strategy is addressing mandated public authories from the Government of Andalusia to integrate the tool in their drought risk management strategy. The CS will be delivered to the target users in the format of a webtool and APP, both including maps and graphics that can be downloaded. The five complementary climate services that have been developed in the Andalucía Living Lab are: Climate service 1 spaally adapted seasonal (6-12 months) monthly precipitaon and temperature predicons at a spaal scale adapted to the needs of the users (200 m) (Figure 7). For this service the ECMWF-SEAS5 seasonal predicon models (51 members) are bias-corrected for each percenle of the cumulave distribuon funcon (Empirical quanle mapping) based on daily data me series from the dense network of AEMET staons. The products generated are connuous maps of monthly (6-month) future precipitaon and temperature predicons for the most representave percenles (5, 10, 25, 50, 75, 90, and 95) of the 51 members, and maps of the spaal variability of the interquarle range for the 51 members. Figure 7: Screenshot of the visualizaon of CS1 – seasonal predicons. Climate service 2 Decadal (10 years) climate impact projecons regarding monthly precipitaon and temperature that is adjusted to the spaal scale of the region (approximately 200 m) (Figure 8). For generang this service, Geostascal downscaling of Copernicus Climate Data Store (CDS) projecons for the RCP4.5 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 21 ID User requirements As a <ROLE>, I would like to <GOAL> to <BENEFIT> ES8 As a hunng associaon… … I would like to know when summer ends next year… … to inform the esmaons about when the game will start reproducing. ES9 As a water management authority… … I would like to know drought index projecons.. … to inform drought risk management rulings. ES10 As a research instute… …. I would like to know the most downscaled possible climate change projecons in the region… … to inform comparave studies on foreseen climate change impacts. Soluon (TO-BE Scenario): For each climate service, we provide an example of impact stories to underpin the kind of needs from the MAP are sasfied by I-CISK CS development. CS1 End-user: Natural Park Situaon: Each year the Natural Park needs to esmate the number and species of trees seedlings needed for next season to restore and maintain the forest in the natural park area. Complicaon: reduced rainfall and changing precipitaon paerns in late spring increases the mortality of young trees planted. Queson: no sound informaon on seasonal and sub-seasonal precipitaon predicons for the upcoming year is available. Answer: ICISK provides a predicon of precipitaon for the relevant period and spaally focusing on the natural park area, thus facilitang drought risk management when buying new trees for the next season. CS2 End-user: dairy farmer Situaon: Dairy cow milk producon levels decrease with extreme heat. Water is necessary for drinking, cleaning and for maintaining cool temperatures in the cow sheds, for instance through indoor sprinklers or other more advanced methods. Farms need to foresee the number of animals needed and guarantee its climac comfort to maintain milk producon and ensure the economic viability of the farm. Complicaon: dairy farms need to plan long term investments, such as cow sheds and cooling systems, as well as future water availability to run the farm. Queson: There are no climate forecasts that can help plan this decision making at farm scale. Answer: I-CISK provides downscaled climate forecasts tailored to the needs of dairy farming in Los Pedroches, allowing to reduce the risk of long-term investments. CS3 End-user: all cizens Situaon: Local populaon in the Los Pedroches area perceive drought episodes in accordance to their memory of past episodes; addionally, management decisions are oen based on past experiences rather than on scienfic evidence. Complicaon: impacts of drought on daily lives of the Los Pedroches society are increasing, implying economic loss and emoonal trauma. Queson: Los Pedroches society has no easy access to scienfic evidence on past climac condions to corroborate their beliefs and improve their decision making. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 22 Answer: I-CISK provides a visual tool to navigate and explore past climac condions in the region, so that people can relate the drought impacts suffered in the past to this data as well as to help interpreng the predicted and forecasted condions. CS4 End-user: olive oil producon Situaon: Rainfed olive producon is highly affected by climac condions. Producers experience difficules to fine-tune the operaonal calendar of agronomic acvies in the field to increase tree resilience. Complicaon: climate variability due to climate change compromises the effecveness of tradional decisionmaking criteria. Queson: relevant agro-climac indicators are not accessible and causal relaons between climac condions and final olive producon yields are oen unclear. Answer: I-CISK tailors exisng agro-climac indicators published by Copernicus to local condions in Los Pedroches and produces a pilot invesgaon to correlate climac condions to the producon obtained. CS5 End-user: livestock farmer Situaon: farm management decision making relies mainly on market prices, while risk management based on climate is weak. Complicaon: drought-related impacts increase water needs and increases the use of groundwater resources in the region. Queson: due to the lack of hydrogeological informaon, livestock farmers cannot esmate future water availability in the short-medium term. Answer: I-CISK provides a characterizaon of groundwater bodies and their relaon to climac condions, fostering enhanced decision making to improve water management of livestock farms in Los Pedroches. Value Proposion (Goal of the service): The climate service informaon impacts the core decision making process for olive oil, milk and dehesa farmers, as well as it provides key input for forest management, like restoraon acons, as well as envisioning scarcity management needs related to groundwater exploitaon in the region. The climate service contributes to enhancing adaptaon and resilience towards drought in the region, allowing to improve producon and economic management decisions. Therefore, the economic values enhanced by the CS in the Andalusian LL are linked to agriculture producon mainly. The developed CS also contributes to changing the percepon of drought at socio-cultural level, providing sound data to compare with past events. This aspect is polically relevant as to induce behavioural changes needed to reduce vulnerability. 4.3 Second iteraƟon: understanding the value chain As described in table in Figure 14, the value chain for CS1, 2 and 3 has been analysed through the different ers of service provision. Tier 1 is the “supplier” of the climac data i.e. the seasonal forecasng data of essenal variables or impact models results. EU, through dedicated services and programs such as Copernicus, provides climac data to a large end-user group. ECMWF as a scienfic organizaon generates and provides high quality climac data of seasonal forecasts which may be used by downstream services “as is” or are repurposed through impact modelling by scienfic instutes (in the present case by SMHI) which widen the services of climac data (e.g. seasonal forecasng of river flows). For the Spanish case, also the Naonal Meteorological Organizaon (AEMET) as well as REDIAM (Environmental Informaon Network of Andalusia), an agency of Andalusian Government Environmental Evaluaon and Analysis Service, are included. Furthermore, the olive producers cooperave OLIPE, also has a limited network of informal data gathering on precipitaon, so we consider them as providers of informaon too. These actors benefit from the services through: D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 23 - ECMWF can incur scienfic gains, as I -CISK CS provides user feedback to service providers relevant to improve the quality of informaon produced. - AEMET can gain societal benefits, as I-CISK CS can increase the recognion for the work delivered by meteorological services by increasing informaon accessibility to end users. - The olive growers cooperave OLIPE can gain environmental benefits, as I CISK CS help raising awareness for the need for adaptaon measures to be put in place in the face of the impacts of climate change. - Copernicus can gain innovaon benefits from increased investments in climate data analysis, as I-CISK CS gains visibility in the populaon influencing the polical agenda. - REDIAM can gain innovaon benefits, as I-CISK CS is able to reach a broad public with useful research results and new science into society programs can be enhanced, as well as funding opportunies to further develop the work started by the project. Tier 2 is the “primary user” (this is also referred to as intermediary user) of the climac service, and for the Spanish case these are idenfied as REDIAM and IFAPA, as well as the river basin authories, provided they work on raw data and develop intermediate climate services. These actors benefit from the services through: - IFAPA can gain scienfic benefits through increasing academic publicaons enhanced by the CS development and use, as well as complementarity to other research projects in course in the region. - REDIAM can gain regulatory benefits, as improved climate data by I-CISK can sustain revision of current risk management protocols. - River basin authories can gain societal benefits provided users are beer informed by I-CISK CS and beer prepared for drought risk management Tier 3 is the “secondary user” i.e. the end user of the service provided by the primary user. For the Spanish case, farming cooperaves, food chain retailers and public authories such as the natural parks are key beneficiaries. These actors benefit from the services through: - I-CISK CS allow innovaon benefits for the farming cooperaves, as it fosters climate conscious business pracces, improving risk management with respect to current pracces, thus potenally reducing economic losses and allowing for innovaon in entrepreneurship models. - Public authories can gain environmental benefits from I-CISK CS through improved preparedness for facing the impacts of drought, inducing the development of complementary soluons for supply, avoiding emergency induced over exploitaon of local water bodies and fraudulent behaviour (unlicensed wells or use of wells beyond licensing agreements). - I-CISK CS can provide benefits to farming cooperaves in terms of innovaon in business pracces also fostering a stronger relaon between the cooperaves and scienfic actors, generang a creave environment potenally enhancing innovave pracces reducing overall vulnerability of the region. Tier 4 includes the other economic sectors, which for the Spanish case are consumers (olive oil, milk and cheese, Iberian ham, hunters), natural site visitors, pupils (capacity building beneficiaries) and cizens as direct water consumers. it is important to state that the inhabitants of Los Pedroches were not supplied with piped drinking water for over a year, and the impacts of drought are very strongly perceived in the community. Therefore, improved drought management, risk management and awareness are key to ensure improved food security and cizen wellbeing. These key factors are strongly linked to the depleon of water related and terrestrial ecosystems health, main tourism provisions related to natural heritage, gastronomy and hunng acvies. Representaves of these key economic sectors parcipated in the living lab because of their interest in reducing economic losses and seeking adaptaon opons to avoid job losses. Drought has influenced polical stability in the region, confronng territories and water users, thus climate services introducing evidence-based informaon are also key to fight misinformaon and manipulaon of public opinion. In this sense the CS number 3 was developed, so as to be able to confront the percepon of past drought episodes with real data. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 24 I-CISK CS can provide societal benefits to cizens by contribung to safeguarding public health, provided droughts and associated heath waves are affecng local society in many ways, but specially in terms of sanitary discomfort and water-borne diseases, as well as plagues related to the overall environmental degradaon induced by drought. CS can provide regulatory benefits to public authories managing natural parks and other emergency services affecng the local populaon, helping to improve the quality of current wildfire-risk alerts, but also sanitary alerts and other early warning systems in place. The CS developed can provide environmental benefits to the populaon of Los Pedroches reducing natural resource depleon, especially water related environments, as an effect of beer drought management and improved knowledge about the hydrogeological features of the area. In the same line, CS can provide environmental benefits through reduced impact on biodiversity, both in freshwater environments, as well as terrestrial ecosystems, due to improved informaon available to Los Pedroches communies. Climate service number 4 is parcularly interesng for olive oil producers but aims at paving the way to an increased use of the Copernicus agroclimac indicators for different farming sectors. Current service is very much tailored to this parcular seng, but given the importance of olive groves in the landscape, other actors of the living lab also indicated the potenal indirect effects of this service. The er analysis has similar results to the other services, and will enhance risk management, avoiding losses and protecng the rural economy it sustains. Olive oil can be stored, so market fluctuaons can be palliated through stock management. This service is most directly linked to producon costs, but these were impossible to quanfy given the huge diversity of farming models (mountainous areas, plane areas, small or bigger enterprises, age of the farmer and many other factors. For climate service number 5 the analysis shows how the hydro-geological characterizaon contributes, complemenng the services above. In this case the river basin authories are also providers of primary informaon, related to the impact of the climac condions on the local water bodies. It is important to note that the region does not have abundant freshwater streams directly supplying the different users. This means that groundwater resources are key. Groundwater bodies are defined and monitored as by the water Framework Direcve (2000/60/CE), but detailed informaon how on how groundwater flows in the Los Pedroches landscape are available. Local drought resilience is strongly linked to land use, therefore these services have strong value, not only in terms of improved land use and groundwater exploitaon opons, but also in terms of an improved understanding of this landscape by local society. This socio-polical value strongly emerged in the conversaons held during field work and ad hoc surveys. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 0 Figure 14: Understanding the value chain for Climate Services CS1, CS2 & CS3 (par. 4.2) developed in the Andalucía Living Lab (Spain). D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 1 4.4 Third iteraƟon: Analyse the benefits The Spanish Living lab MAP includes several different socioeconomic profiles, which means that benefits are many and diverse. This is an advantage for the sustainability of the CS produced by I-CISK as raising interest from different sectors increases the number of decisions that take climate related risks into account. In this sense, we can idenfy that most benefits are obtained by reduced drought related losses. For this analysis we focus on CS 1 seasonal predicons for the dehesa livestock breeding sector, as this is the economically strongest value chain in Los Pedroches (Figure 15). Figure 15: Demand for climate services offered by the I-CISK project based on economic sector (note that SC is CS in Spanish, denong the five CS developed in the project). CS1 reduces producon cost losses induced by drought, especially regarding the following producon factors:  Each year the farmer decides the carrying capacity of the dehesa, breeding or buying the correct number of young swine on a yearly basis. Agroforestry resources define the need for buying addional fodder for the pigs.  If the esmaon of addional fodder is not correct that could lead to addional expenses for further supply, which could range up to a moderate economic burden, based on the annual budget  Addionally, the swine need to be supplied beverage water in the plot. Usually there are temporary ponds and lile streams in the landscape that farmers count on for supply.  If the esmaon of available water resources is not correct, this could lead to an under-(or over) esmaon of the addional water which should be bought for the Dehesa farm. That could lead to addional costs which could range up to a moderate economic burden, based on the annual budget.  Further, seasonal temperature and rain paerns are key factors in the decision meline for pruning the oak trees. Correct pruning will increase the tree health and comfort.  If pruning is not opmal, this will reduce the quanty of fodder the pigs will have. That could lead to addional costs to buy complementary fodder, which could range up to a moderate economic burden, based on the annual budget. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 2 Based on the above reasonable steps towards idenficaon of the value chain and on the scaling of benefits given in Table 1, the service demonstrates two specific benefits for cost reducon. Based on the reasoning of “avoided costs” which are idenfied by the end-user as low to medium, the benefit of the service is idenfied as: LOW to MODERATE . 4.5 Fourth iteraƟon: Analysis beyond the defined boundaries For the Spanish case we idenfy the MAP of the living lab as a primary market segment, provided the service was enrely tailored to the most characterisc features of Los Pedroches. For users outside the region the ICISK service could be adapted. In this sense, I -CISK can promote the adopon of user centred services to other regions fostering new projects to be developed to promote the approach, but this is not the primary focus of the CS developed in this LL. It is important to remark that the establishing of the living lab mul-actor plaorm itself is an added value of the project. In the first place because it has provided territorial cohesion and dialogue between key actors that were not in contact before the project. The new relaons established can provide a more transversal reacon to the need for adaptaon, boosng co-benefits between the measures adopted in each sector. The most prominent users of the service produced are the livestock farmers, followed by other agricultural pracces, such as olive oil producon, that are the primary actors in this market segment. Sll, this is a very small segment and there is no point on proceeding with a full market analysis because this market is not the key exploitaon objecve of the Climate Service. The key actor for sustainability of the CS produced in the Spanish case aer the end of the project has been idenfied as REDIAM, the public purveyor of climate services established by the regional government. No commercial use would be envisioned, as the service would be integrated in other publicly available climate services published by this organisaon, e-gon wildfire fire risk. Based on the above, this market is not the key exploitaon objecve of the developed CSs and therefore, a full market analysis would not be relevant. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 3 5 Business model storyline for the Emilia Romagna Living Lab (Italy) 5.1 Background and context The Emilia-Romagna Living Lab (ITA LL) is embedded in the upper Secchia River catchment, an area spanning the provinces of Modena and Reggio Emilia in Northern Italy. This region faces increasing climate challenges, notably droughts and water scarcity, which demand innovave approaches to water resource management co – developed with the contribuon of the Mul Actor Plaorm involved on the Lab acvies. The ITA LL focuses indeed on co-developing a Climate Service (CS) prototype tailored to support decision-making processes for water allocaon and resource planning amidst these challenges. The co-design process has been anchored in a collaborave engagement with key stakeholders, including the Regional Environmental Agency (ARPAE), Land Reclamaon Consora, water ulity companies, and hydropower producers. Leveraging a Mul-Actor Plaorm (MAP), the Living Lab has iteravely refined the CS through workshops, interviews, and interacve boards, addressing both short-term coping strategies and longterm adaptaon measures. At the core of the CS is a data-driven framework combining real-me monitoring, historical records, and predicve models. It integrates upstream river discharge forecasts (provided by external providers and services like Copernicus or SMHI) with local environmental data (observed discharge at exisng gauging staons and relevant thresholds set for decision making during drought periods), offering stakeholders aconable insights into water availability and flow management. This service aims to enhance operaonal efficiency, reduce administrave burdens, and improve compliance with environmental regulaons. An example of the main page of the service is provided below. Figure 16: Example of Climate Service landing page and buons to select specific river staon to provide discharge forecast. By embedding the CS into exisng governance structures, such as the periodic Drought Observatory and regional Resilience Plans, the ITA LL seeks to facilitate proacve water management strategies. This integraon underscores the value proposion of the CS we are trying to define, in minimizing economic losses during droughts, promong environmental sustainability, and supporng equitable water distribuon. Addionally, it offers a pathway to scale similar approaches across other regions, demonstrang the replicability and scalability of the service to many similar hydraulic nodes exisng across the Region. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 4 For this reason, the type of informaon to display is being iteravely refined to provide relevant informaon and forecasts tailored to local needs and specific decision-making processes, as illustrated in the following example. The subsequent secons outline the iterave steps taken to esmate the CS value, incorporang both quantave and qualitave approaches, and examine the potenal pathways for its sustainable implementaon and commercial exploitaon. Figure 17: Example of forecast discharge displays selectable through the GUI; custom forecast window on a daily basis (upper) to be matched with crical thresholds like minimum environmental flow, along with cumulated values (lower) on a monthly basis relevant for users that can manage storage systems. 5.2 First iteraƟon: Defining boundaries of analysis At this stage, the boundaries of the analysis for the ITA LL use case have been clearly defined. These boundaries encompass the following aspects:  The geographical and sectoral focus  The targeted users of the developed service D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 5  The targeted problems the proposed service aim to solve  The current pracces in place and the need for having an advanced soluon to address these problems We defined the boundaries of the problem starng from dedicated interviews with users, to form the foundaon of the 1st iteraon step of the Value of Informaon (VoI) assessment. This step aims to esmate the value proposion of the Climate Service (CS) by evaluang its potenal to enhance decision-making processes, improve resource allocaon, and address regional water management challenges effecvely. Locaon: The Emilia-Romagna Living Lab is situated in the upper Secchia River catchment, with the outlet at the Castellarano Weir in the Emilia Romagna region. This area spans the provinces of Modena and Reggio Emilia (Figure 18) and covers approximately 700 square kilometres. The Secchia River catchment is vital for the region's agricultural and industrial acvies, providing essenal water resources for irrigaon, industry and hydropower. The river is a crical part of the local water management infrastructure, with key features including the Castellarano Weir, which helps regulate water flow and distribuon. The region is characterized by its Mediterranean climate, which presents unique challenges in terms of water availability and management, with prolonged summer droughts, making it an ideal seng for developing and implemenng innovave climate services focused on water resource management amidst increasing climac variability and extreme weather events. Figure 18: Castalllarano weir on the Secchia River, which spans the upper provinces of Reggio Emilia and Modena in the Emilia Romagna Region, Italy. End User(s): The primary end users of the Emilia-Romagna Living Lab include the Regione EmiliaRomagna (Regional Authority, RER), responsible for regional policymaking and water resource D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 12 Incenvizing Adopon through Regional Funding To accelerate adopon, the Regional Government is considering direct financial incenves for the acquision and deployment of the Climate Service by key stakeholders, such as the Irrigaon Consora and water ulies. These incenves focus on:  Hardware and soware acquision – Funding the installaon of hydrological monitoring staons to couple with the predicve modelling soware and to pilot water management inside the resilience planning  Data integraon and real-me forecasng – this is more linked directly to the soware implementaon of the service Aer discussion with the Regional government we have co-developed an example of hypothecal public funding of the Climate Service through Regional Programs. It should be noted that this does not constute extraordinary funding, but rather a reallocaon of already planned financial resources for agriculture, direcng them towards the Climate Service as one of the eligible measures within exisng investment programs. This ensures that the service is financed within the current budget framework, without requiring addional public expenditure. One possible channel for financing the acquision and maintenance of the Climate Service is adapng an exisng program under the Programma di Sviluppo Rurale – PSR (1). This could provide one-me funding for the purchase, for example of five-year operaonal costs of the service, ensuring its full integraon into regional water management frameworks. Exisng program currently supports investments in sustainable and resilient agricultural infrastructure, and its structure could be adapted to fund the Climate Service could be as follows: Minimum eligible expenditure are €10,000 in disadvantaged areas or €20,000 in standard areas Maximum funding per beneficiary per sector: €1.5 million (including hardware and soware) Grant coverage:  40% for standard beneficiaries  50% for young farmers and disadvantaged areas  60% for projects with significant environmental benefits (e.g., resilient orchards) Applying this framework, the Climate Service could be posioned as an environmental resilience measure, allowing stakeholders to benefit from a 60% co-financing rate. This would significantly lower the upfront investment cost for any uptaker such as Reclamaon Consora and mul-ulity companies, facilitang widespread adopon. Furthermore, given the administrave constraints associated with regional funding, financing could be allocated enrely in Year 0, covering:  Hardware acquision and installaon costs.  Soware licensing and maintenance for five years.  Inial user training and integraon with exisng plaorms. 1Rural Development Programme, co-financed by the European Agricultural Fund for Rural Development - EAFRD, under the Common Agricultural Policy - CAP D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 13 Opmizing the management of the Minimum Ecological Discharge and storage. To further explore the potenal of the Climate Service in enhancing water governance, we have also developed consideraons with the Regional Government regarding its role in opmizing the management of the Minimum Ecological Discharge (Deflusso Minimo Vitale/Deflusso Ecologico - DMV/DE) and pre-empve storage, parcularly during and before-aer the summer period. These discussions, which build upon exchanges with both the Regional Government and Irrigaon Consora altogether, focus on a more flexible and adapve approach to DMV regulaon, allowing for extended withdrawals during peak agricultural demand while ensuring ecological sustainability through compensatory releases in adjacent seasons. These aspects are detailed in the following secon. Opmizing Agricultural Water Management through the Climate Service The Context: Water Pricing and Resource Management in Reclamaon Consora The discussions with the Central Emilia Reclamaon Consorum highlighted the complexity of water pricing and distribuon mechanisms in irrigaon systems. The Consorum does not charge a market price for water but applies a tributary contribuon system, divided into a fixed fee and a variable fee. The fixed fee accounts for 80-85% of the total costs and covers infrastructure maintenance, network management, and resource monitoring. The variable fee, which represents only 15-20% of the costs, is proporonal to the water volumes withdrawn and depends on factors such as crop type, irrigaon period, and local availability. The comparison between the Po River Basin and the Secchia River Basin illustrates the different constraints affecng water users:  Po River Basin: Water is available throughout the season, with a lower cost per cubic meter (around 0.03 €/m3) but a higher fixed fee due to extensive infrastructure and higher guaranteed availability.  Secchia River Basin: Water is scarce and distributed in strict rotaon schedules, leading to higher perunit costs (3-4 mes higher than Po) but lower fixed fees. During peak demand, supply is insufficient, and withdrawals are somemes suspended due to low river flow. The rigid structure of current water management policies limits flexibility, parcularly in drought-prone areas. The Climate Service (CS) can improve forecasng accuracy, enabling beer planning of withdrawals and releases to migate water scarcity during crical periods. However, effecve integraon requires a governance model that considers both operaonal and economic sustainability. Many water management policies, such as Piani Territoriali Ambientali (PTA) and EU direcves, oen oversimplify the complexies of irrigaon consora. The assumpon that reducing withdrawals lowers costs is misleading, as most costs in large-scale irrigaon infrastructures are fixed, independent of water use. Similarly, the idea that only users should pay for water ignores the fact that a well-maintained irrigaon network benefits all landowners, influencing land value and agricultural producvity. A more effecve approach should focus on collecve water management at the basin scale, rewarding district-wide efficiency rather than individual reducons. Water governance should also be assessed at the system level, ensuring that efficiency measures do not unintenonally increase overall losses. By integrang the Climate Service into regional resilience plans, adapve ecological flow management and forecast-driven decision-making can provide greater flexibility for agricultural users. This approach aligns D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 14 economic and environmental priories, ensuring sustainable resource use while maintaining irrigaon access during peak demand periods. Enhancing Water Availability through Adapve Ecological Flow Management One possible way of applicaons of the Climate Service in agriculture is its potenal to support a more flexible and adapve approach to Deflusso Ecologico (DMV, Ecological Flow). The current system applies to two fixed seasonal values—summer and winter—which do not fully account for seasonal variaons in water availability or the actual needs of agricultural users. Introducing a mul-level DMV, supported by the forecast system to acvate mely all required management measures such as storage, could improve water management by adjusng flow requirements to match demand and availability throughout the year. For example, in July and August, ecological flow requirements could be reduced from 1.49/1.59 m³/s to 1 m³/s at key control points such as Castellarano and Ponte Veggia, allowing for extended irrigaon during peak demand. This reducon could be compensated by increased ecological flow releases in April and May, which currently follow winter levels but could be adjusted to rebalance the system. Flows in June and September would remain unchanged, ensuring stability across seasons. This adjustment would create addional water availability for agriculture in the summer without altering the total annual flow balance. An approximate reducon of 0.5 m³/s reducon in ecological flow for 60 days in July and August would result in 2.6 million cubic meters of addional water, which could be reallocated to agricultural users while maintaining overall environmental sustainability. By integrang this approach into regional resilience plans (PDRs), water distribuon could be opmized based on climate forecasts. The Role of the Climate Service in Governance and Operaonal Efficiency For this adapve model to be viable, it must be incorporated into exisng water governance frameworks and validated through regional policies (the already menoned PDRs). The Climate Service can facilitate this transion by providing aconable forecasts, improving decision-making, and enabling beer coordinaon between ecological and agricultural water needs. Through forecast-driven decision support, water withdrawals can be dynamically managed, enhancing chances that ecological flow requirements are respected while maximizing water use efficiency. The service can also automate the process of prevenve channels filling, which is currently subject to addional costs and administrave procedures. By integrang this funconality into PDR protocols, reservoirs could be filled based on predicve models, eliminang the need for extraordinary approvals and reducing unnecessary operaonal costs (see also previous chapter descripon of the Regional Government expect gains). A more adapve water management strategy, supported by climate forecasng, would provide greater flexibility for agricultural users, at least key players like Consora enabling them to extend irrigaon periods in mes of high demand while compensang with increased releases during other seasons. This approach aligns agricultural and environmental priories, offering a sustainable soluon to the challenges posed by climate variability and water scarcity. Qualitave Esmaon of Gains To further assess the value of the Climate Service for agricultural water management, we apply a qualitave esmaon of the benefits following the approach outlined in the I-CISK Guidelines for Value Chain Assessment D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 15 (see MS26, Assessment of downstream value chain, June 2024). Based on stakeholder consultaons and previous analyses, the expected benefits can be esmated as follows: Economic Gains: The Climate Service promotes efficiency in water allocaon, reducing loss of water volumes, while increasing availability during peak irrigaon periods. By improving planning and reducing the need for emergency measures, irrigaon consora and regional authories can lower operaonal costs and opmize water use. Using the framework in Table 1, these gains align with a MODERATE to HIGH rang, parcularly in terms of avoided costs from reacve measures. Environmental Gains: By supporng a more adapve ecological flow strategy, the Climate Service balances agricultural withdrawals with environmental needs. This enhances ecosystem resilience by ensuring sufficient flow in crical periods, reducing extreme low-flow events that harm biodiversity. This dimension is rated MODERATE expecng a long-term sustainability impact. Social Gains: Farmers and water users benefit from greater predictability and reduced compeon for water during drought periods, increasing resilience in the agricultural sector and, linked to the previous benefit a more usable riverine ecosystem for cizens Improved governance and stability in water availability contribute to regional economic stability. These gains align with a LOW to MODERATE classificaon in the assessment framework. This qualitave esmaon highlights that the Climate Service is able to provide tangible value in improving water governance, reducing administrave burdens, and ensuring a more sustainable and efficient use of water resources in Emilia-Romagna. 5.5 Fourth iteraƟon: analysis beyond the defined boundaries 5.5.1 Market SegmentaƟon Defining the segments The Climate Service co-developed in the Castellarano Living Lab is designed to support decision-making in the water sector, with a specific focus on sub-seasonal to seasonal river discharge forecasts. The service leverages both open data and regional calibraon to offer localized, aconable insights. Given its tailored nature and integraon with exisng planning tools (e.g. a Water management plan at various levels), the service targets a B2G (Business-to-Government) and B2B (Business-to-Business) mode. The main market segments across Europe (the analysis has been ed to this geographical area for the moment) are idenfied as:  Regional Public Authories responsible for water resources planning and emergency response (e.g. regional governments, basin authories)  Water Reclamaon and Irrigaon Consora, managing agricultural distribuon and compliance with ecological flow regulaons  Public and private water ulies, managing urban and industrial supply under changing hydrological condions  Hydropower operators, interested in short-term forecasts to opmize producon while respecng environmental constraints D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 16  Consulng and engineering firms integrang forecasng products into climate adaptaon projects (here the interest in minor interest due to potenal compeon)  Cross-border instuons involved in river basin management (e.g. Po, Danube, the company GECOSistema taking care of the Lab has indeed experience in proposing similar services to such wider instuon in other contexts such as flood mapping services) These user segments across Europe are increasingly looking for decision-support tools that help them manage water under growing pressure from climate variability and regulatory complexity. This trend is reinforced by the EU Water Framework Direcve (WFD), which promotes the use of such tools to enhance compliance, improve planning under drought and low-flow condions, support the implementaon of ecological flows, and foster adapve water governance.23 Moreover, recent EU-funded projects have demonstrated the role of forecasng systems in enabling proacve reservoir management, simplifying administrave procedures, and strengthening resilience in agriculture and water ulies.45 Parcularly tools shall be able to :  Improve planning and decisions during droughts and low-flow periods  Support legal compliance and reduce administrave burdens  Enable adapve governance (e.g. with modular ecological flow rules)  Opmize water distribuon and storage efficiency Selecng target groups Among these, the most aracve and likely reachable target groups, basing on the discussion and interviews in the Lab as well as the Company’s (GECOSistema) judgment and own experience of over two decades of acvity on the field have been idenfied in: 1. Irrigaon Consora and Basin Authories: (Parcularly in Southern and Eastern Europe These actors are oen responsible for water allocaon in drought-prone areas, where instuonal capacity is high but forecasng capabilies are limited. The pressing need for beer predicon tools and the compability with exisng resilience planning frameworks (PDRs) make them ideal early adopters. 2. Regional Governments and Environmental Agencies: These enes oversee compliance with ecological flow requirements and emergency declaraons. They would benefit from reduced bureaucracy and improved planning reliability, as demonstrated in the Emilia-Romagna use case. 3. Hydropower Operators in mountain (e.g. Alpine and Apennine) Regions: Forecasng tools can inform reservoir operaons, opmizing energy output while ensuring compliance with minimum flow requirements. 4. Mul-ulity Companies operang in mulple sectors (water, energy, environment): These actors can leverage the service to integrate forecasts into broader sustainability and risk management porolios. While various instuons (e.g., Copernicus CEMS, ECMWF, or academic providers) offer seasonal or subseasonal river discharge forecasts, these services are typically generic, pan-European, and not locally calibrated. They provide raw or semi-processed data products that require significant post-processing, making them less suitable for operaonal use by local or regional water managers without addional support or 2 European Commission – Water Framework Directive: https://environment.ec.europa.eu/topics/water/water-frameworkdirective_en 3 U Guidance Document on Ecological Flows (CIS No.31): https://circabc.europa.eu/sd/a/4063d635-957b-4b6f-bfd4b51b0acb2570/Guidance%20No%2031%20-%20Ecological%20flows%20(final%20version).pdf 4 MARCLAIMED Project – AI-powered tools for water scarcity: https://cordis.europa.eu/project/id/101136799 5 https://cordis.europa.eu/project/id/869550? D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 17 adaptaon. The Climate Service developed within the Italian Living Lab offers a disncve advantage by being:  Tailored to local hydrological and administrave contexts  Integrated into exisng decision-making protocols  Co-designed with public authories and consora, ensuring usability and governance alignment In the public sector, parcularly among regional governments and irrigaon consora, there are potenally less operaonal competors offering integrated, context-specific forecasng services. Most exisng soluons are either research-based, lack spaal/temporal granularity, or are not aconable within public planning instruments. Conversely, in the private sector, parcularly among hydropower operators and large mul-ulies, there is a growing presence of proprietary in-house tools or private consultants offering forecasng capabilies (6). These actors may already use data streams from public services (e.g., Copernicus) combined with their internal models or investments in AI/forecasng infrastructure, making this segment more compeve and cost sensive. Therefore, C4 is rated relavely high (few competors) for public and governance-linked user groups, and moderate to low for private-sector actors, where the market is more fragmented but also more commercially dynamic. This segmentaon reflects both opportunity and differenaon potenal in scaling the service across Europe. Table 2: Group Aracveness Scorecard – for the ITA LL prototyped CS. I-CISK Services Component: Climate Services for River discharge forecast Market Segment Criteria Total Score [C1] The customer group has a pressing need and is willing to act upon it. [C2] Our offering can sasfy that need. [C3] We can easily communicate/ access the customer group. [C4] There are no known competors addressing this need. [C5] The customer group is substanal and potenally profitable. Irrigaon Consora & Basin Authories 4 5 4 3 4 20 6 https://waterjade.com/ D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 18 Market Segment Criteria Total Score [C1] The customer group has a pressing need and is willing to act upon it. [C2] Our offering can sasfy that need. [C3] We can easily communicate/ access the customer group. [C4] There are no known competors addressing this need. [C5] The customer group is substanal and potenally profitable. Regional Governments & Environmental Agencies 5 5 4 4 4 22 Hydropower Operators 3 5 3 2 5 18 Mul-ulity Companies 3 4 3 2 5 17 General Notes: A rang of 1 denotes the statement is totally inaccurate, a rang of 5 denotes the statement is totally accurate. As far as criterion C3 is concerned a rang of: 5 is aributed when the geographical and the core business aributes of the client group coincides with the Developer’s main business acvies 3-4 is aributed when only one of the geographical or the core business aributes of the client group coincides with Developer’s main business acvies 1-2 is aributed when none of the geographical and core business aributes of the client group coincides with Developer’s main business acvies As far as criterion C4, it is assumed that exisng competors have equal access to markets irrespecve of the geographical aributes of the client group (Many if not the most competors operate internaonally). Therefore, the rang differenates only on the basis of addressing the idenfied needs. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 19 5.5.2 Market Analysis EsƟmaƟng the potenƟal size of the target market To substanate the market analysis for the hydrological forecasng Climate Service developed in the Italian Living Lab, it is essenal to provide reasonable figures regarding the number of potenal instuonal users across Europe. Below is an esmaon of key target groups, supported by available sources: 1. Regional Water Authories and Basin Organizaons: The European Union comprises numerous regional and local entities responsible for water management, including basin authorities and regional environmental agencies. While a precise count is challenging due to varying administrative structures across member states, institutions with strategic planning and regulatory mandates—such as River Basin Authorities, Regional Environmental Agencies, or competent water authorities in charge of implementing the Water Framework Directive (WFD) and approving ecological flows and water permits—are fewer in number. Each EU member state typically has a limited number of River Basin District Authories, oen coordinated at the naonal level but managed regionally, along with a handful of regional water or environmental agencies with planning mandates (e.g., ARPAE in Emilia-Romagna or CHE in Spain). Governance structures vary across Europe, with centralized systems in some countries (e.g., Rijkswaterstaat in the Netherlands) and decentralized frameworks in others (e.g., Italy, France, Spain). Based on this instuonal landscape, a conservave esmate places the number of planning-level public authories across Europe at approximately 100 to 150 enes. This figure aligns with the number of River Basin Districts (RBDs) officially recognized under the EU Water Framework Direcve (WFD)(7), within which water governance is typically managed by one or more competent regional or sub-regional bodies(8). Addional instuons, such as regional environmental agencies, further complement this governance framework, especially in decentralized systems. Collecvely, these enes form a relavely small but strategically important market segment, directly engaged in water allocaon, ecological flow regulaon, and climate adaptaon planning. 2. Irrigaon Consora and Associaons: Irrigation plays a significant role in European agriculture, particularly in southern regions. In 2016, the total agricultural area equipped for irrigation in the EU was 15.5 million hectares, with 10.2 million hectares actually irrigated. Countries like Spain and Italy reported the largest irrigable areas, with 3.6 million and 4.1 million hectares, respectively. The European Union of Water Management Associations (EUWMA) represents over 8,600 individual organizations covering more than 50 million hectares, including Italy's Consorzi di bonifica, which are integral to the country's irrigation infrastructure. 9 10,11 While specific numbers of irrigaon consora are not detailed in the available sources, the extensive irrigated areas suggest a substanal number of such organizaons. Given the scale of irrigaon acvies, it is plausible to esmate n order of magnitude of around 1,000 irrigaon consora and associaons across Europe, dealing with water scarcity issues, parcularly concentrated in Mediterranean countries such as Italy, Spain, France, and Greece. 3. Hydropower Operators: Determining the exact number of hydropower operators in the European Union (EU) is challenging due to the 7https://environment.ec.europa.eu/topics/water/water-framework-directive_en 8https://www.eea.europa.eu/en/analysis/publications/state-of-water 9 https://en.wikipedia.org/wiki/European_Union_of_Water_Management_Associations? 10 https://www.europarl.europa.eu/RegData/etudes/BRIE/2019/644216/EPRS_BRI%282019%29644216_EN.pdf? 11 https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Agri-environmental_indicator_-_irrigation D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 20 diverse ownership structures and varying scales of operaons across member states. While comprehensive data specifying the number of operators is limited, insights can be drawn from the number of hydropower facilies and the structure of the industry. According to the European Environment Agency (EEA), there are numerous hydropower plants across Europe, categorized by size and capacity. The EEA provides data on exisng, under-construcon, and planned hydropower plants (12). Addionally, the Hydropower Europe Regional Profile indicates that as of 2023, countries like Norway have a significant number of operaonal hydropower projects. For instance, Norway added 118 MW in installed capacity, bringing the total number of operang projects in the country to 1,330. This informaon suggests a substanal number of facilies across Europe, implying a large number of operators. More details can be found here (13). Given that many operators manage mulple facilies, and considering the prevalence of both large-scale operators and numerous smaller enes, the esmate of over 1,000 hydropower operators across the EU appears prudenal. However, it is important to note that this figure is an approximaon, as definive data on the exact number of operators is not easily available in public domain sources. 4. Mul-Ulity Companies: Mul-ulity companies that integrate water and energy services are expanding their sustainability and resilience porolios, with a growing interest in data-driven soluons for risk reducon. While specific numbers are not detailed in the available sources, the presence of such companies across Europe indicates a notable market segment for Climate Service, despite the low scoring in the previous aracveness analysis no further aempt to evaluate this specific market has been done as part of the present analysis. Conclusion: Based on the available data and reasonable esmaons, the potenal market for hydrological forecasng Climate Service includes:  Approximately 100 to 150 regional water authories and basin organisaons.  Around 1,000 irrigaon consora and associaons, primarily in Mediterranean countries.  Over 1,000 hydropower operators across the EU.  A significant number of mul-ulity companies are involved in water and energy services, but no specific quanficaon has been carried on. These esmaons provide a foundaon for assessing the market potenal and strategizing the deployment of Climate Service across Europe. Although the potenal market across Europe includes several hundred relevant instuons, a more prudent and methodologically sound adopon forecast must account for the structural barriers to entry typical of the public sector. These include the slow pace of instuonal procurement, varying degrees of digital readiness, the need for regulatory alignment, and budgetary planning cycles that oen span mulple years. Addionally, the service is in a pre-operaonal phase and requires co-design with users, further slowing immediate uptake. Therefore, assuming an inial market penetraon rate of just 1–2% among the most eligible public and semipublic water management bodies—such as regional environmental agencies, basin authories, and irrigaon consora—a more conservave and credible esmate would place the number of early adopters at 10 to 15 instuons by 2026. These would likely be concentrated in countries and regions with acve climate adaptaon planning (e.g., Italy, Spain, France) and prior engagement in pilot iniaves like the I-CISK Living Labs. From this foundaon, growth can accelerate in the following years through inter-instuonal learning, 12 https://www.eea.europa.eu/en/analysis/maps-and-charts/recorded-hydropower-plants-in-europe? 13 https://www.hydropower.org/region-profiles/europe D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 21 inclusion in resilience plans, and policy reinforcement. 5.5.3 Analysing trends and responding to opportuniƟes and threats Goal of the product or service: To provide public and semi-public water managers with a localized, operaƟonal forecast tool to improve water allocaƟon, reduce emergency measures, and ensure environmental compliance. The Climate Service developed in the Italian Living Lab aims to address strategic needs in water management by offering high-resoluon, locally adapted, and governance-compable seasonal discharge forecasts. In this secon, we apply a SWOT analysis framework to beer understand how external trends and internal capabilies affect the service’s deployment potenal. Strengths  Strong co-design with target users (regional authories, consora), ensuring relevance and instuonal compability.  Can be tailored to local hydrological contexts and embedded in exisng planning instruments.  Reduces administrave burden by pre-authorizing resilience acons.  Combines technical forecasng capacity with user-centric governance applicaons. Weaknesses  Dependence on regional funding mechanisms for scaling and adopon, at least in the Lab developed case  Limited in-house visibility outside pilot regions.  Potenal challenges in long-term maintenance and support in resource-constrained administraons.  Requires training and instuonal alignment to be used operaonally. Opportunies  EU regulatory trends (WFD, Climate Adaptaon Mission) support innovave like predicve and datadriven water governance.  Increasing exposure to droughts and water conflicts increases urgency for tools that can enable fair and efficient allocaon.  Availability of rural development funds and resilience funds for adopon.  Growing momentum for adapve ecological flow management in Mediterranean countries. Threats  Fragmented governance across regions may delay coherent adopon strategies.  Potenal compeon from large-scale providers offering generic, low-resoluon services.  Uncertainty in funding cycles or polical turnover may disrupt service connuity.  Risk of low uptake if not formally embedded in regulatory or planning obligaons. The Climate Service is indeed well posioned to respond to clear market demands in the European public water management landscape. Its added value lies in its operaonal usability, instuonal co-creaon, and alignment with emerging water governance frameworks. However, unlocking its full potenal requires a D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 28  The degree of familiarity with the intended market (Table 5)  The closeness of the proposed service to exisng capabilies and assets (Table 6) In Table 5, most scores fall between 1 and 3, suggesng a moderate degree of familiarity with the intended market. Although some aspects such as customer relaonships and branding are sll emerging, others—such as understanding of public instuonal behaviour and decision processes—score reasonably well thanks to the co-creaon and engagement acvies conducted within the Living Lab. These instuons (e.g., irrigaon consora, basin authories) are already known stakeholders, and their needs have been explored and validated during the service development process. However, the lack of structured commercial relaonships and instuonal procurement experience explains the cauous scoring. In Table 6, the product/service analysis yields a total score of 10 out of a possible 30, reflecng a relavely high alignment with exisng technical and scienfic competences. The service leverages hydrological modelling, seasonal forecasng, and web-based delivery—domains where the developer (a typical SME in this space) already has significant experience. The relavely low scores in intellectual property and service customizaon reflect the tailored nature of the product and its dependency on public co-financing rather than proprietary advantage. Table 5: Assessment of the intended market. Source: (Day 2007), adapted to the ITA LL prototyped CS. Intended Market ...be the same as in our present market ...parally overlap with our present market ...be enrely different from our present market or are unknown Scor e Customer’s behaviour and decision-making processes will... 3 3 Our distribuon and sales acvies will... 3 3 The compeve set (incumbents or potenal entrants) will... 3 3 Our brand promise is... 1 1 Our current customer relaonships are... 1 1 Our knowledge of competors’ behaviour and intenons is... 3 3 TOTAL (X-axis coordinate) 14 Table 6: Assessment of the product or service. Source: (Day 2007), adapted to the ITA LL prototyped CS. Product or Service ...is fully applicable ...will require significant adaptaon ...is not applicable Scor e Our current development capability... 1 1 Our technology competency... 1 1 Our intellectual property protecon... 3 3 The required knowledge and science bases... 1 1 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 29 The necessary product/service funcons... 3 3 The expected quality standards... 1 1 TOTAL (Y-axis coordinate) 10 The coordinates (x=14, y=10) place the Climate Service within the lower-le area of Day’s matrix (see Figure 22), corresponding to a probability of failure in the range of 25–40%. This risk level is consistent with innovaons that are adjacent to current offerings and markets: novel enough to require investment and adaptaon, yet close enough to exisng skills, tools, and clients to migate major risk factors. Figure 22: Risk matrix. Source: (Day 2007), for the ITA prototyped CS. In conclusion, the Climate Service exhibits a moderate innovaon risk profile, appropriate for public-private ventures in the climate adaptaon space. The co-design process, regulatory alignment, and compability with exisng tools significantly lower the risk of failure, making the service a strategically sound candidate for earlystage scaling and targeted investment. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 30 6 Business model storyline for the Budapest Living Lab (Hungary) 6.1 Background and context The Budapest LL is located in the Erzsébetváros district, an inner-city area of Budapest (the capital and most populous city of Hungary). The area is densely constructed with many protected-heritage buildings mostly from the late 19th and early 20th centuries. This district has a low percentage of green spaces, with a high density of buildings, and therefore is parcularly exposed to heat waves, which are already causing issues for a range of sectors in the city. The focus of the Living Lab is on urban heat islands in the tourism and public health sectors. The CS developed is an Urban Heat Planning Service with two specific tools:  Time-series analysis: Ulizing orthophotos as a high-resoluon baseline for me-series analysis of thermal data. This method allows for tracking changes in urban heat over me with a clear reference to the physical changes in the urban landscape.  Energy balance modelling with detailed surface informaon: Applying energy balance models that use detailed surface informaon from orthophotos, combined with thermal data, to interpret urban heat dynamics more accurately (Figure 23). Figure 23: Urban heat map CS, Erzsébetváros district, Budapest. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 31 6.2 First iteraƟon: Defining boundaries of analysis The service of Budapest LL aims to address the current limitaons of heat data collecon and processing in an integrated manner, specifically: - Data integraon: by combining drone thermal imagery with manual temperature measurements, we aim to create a detailed, spaally and temporally variable picture. - Dynamic updang: using drone thermal imagery to downscale satellite imagery, the heat map will be able to be updated with satellite and microclimate model data in the future. This will make the service more flexible to provide real-me or near real-me informaon. - Problem solving: The service aims to provide an advanced soluon to the shortcomings of current data collecon methods, which have limited coverage and are stac in me, to monitor heat, heat island phenomena more accurately. This integraon allows for the creaon of a high-resoluon, dynamically updatable heatmap by incorporang data from satellite observaons and microclimate models. Consequently, the temporal scope of the service is broadened, enabling connuous updates rather than relying solely on stac, isolated measurements. In addion to the integraon above, the service is further augmented by an AI-driven heat predicon component. A convoluonal neural network (CNN) was trained using local heat data to generate a heat predicon map. However, the current approach has not yet achieved the desired accuracy, indicang that further experiments with AI techniques are required to refine the predicon model. Geographical and Sectoral Focus The analysis is primarily concentrated on the Terézváros (6) and Erzsébetváros (7) districts of Budapest. These areas have been chosen not only because they are prominent tourist aracons—making tourism a key sector—but also due to their significant social dimensions. Both districts host numerous kindergartens, elderly care centres, and schools, emphasizing the importance of addressing social sector needs alongside tourism Targeted Users The service is designed with a user-focused, boom-up approach. The primary beneficiaries include: - Tourists: Visitors will benefit from accurate, mely microclimate informaon that enhances their overall experience. - Local Residents and Instuons: Community members, as well as educaonal and care facilies, can ulize the data to improve daily operaons and environmental awareness. - City Management and Decision-Makers: Authories can leverage the high-resoluon, integrated data for urban planning and infrastructure development. 6.3 Second iteraƟon: Understanding the value chain The climate service developed in the Budapest LL offers a comprehensive, integrated soluon that leverages mulple data sources—drone-based thermal imaging, manual temperature measurements, cizen science contribuons, and satellite downscaling—combined with advanced AI techniques. This innovave approach is designed to deliver accurate, highly localized (streetor block-level) heat/microclimate data and aconable knowledge for informed decision-making. The value proposion of the service is built on the following key elements: 1. Localised Microclimate informaon: Accurate, localised info at street/block level. 2. AI-based Forecasng: CNN heat predicon and segmentaon D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 32 3. Scalable Soluon: Mul-source data adapts to urban needs 4. Targeted Users: Tourism, social sector, city management The service’s value chain can be divided into four main stages which together transform raw data into aconable insights for informed decision-making across various sectors, as presented below and summarised in Figure 24. Tier 1 (Data Collecon and Preparaon) focuses on gathering inputs from drone-based thermal imaging, manual temperature measurements, and cizen science contribuons. In this stage, the collected data undergo inial validaon checks, standardizaon, and georeferencing to ensure consistency and quality. By involving local residents and volunteers in the measurement process, the service achieves more granular coverage—oen at street or block level—forming a robust foundaon for detailed microclimate analysis. Key Stakeholders: - Drone Operators: Responsible for collecng high-resoluon thermal imagery. - Manual Data Collectors: Professionals or trained personnel conducng in-situ measurements with thermometers or handheld thermal cameras. - Cizen Sciensts: Local residents and volunteers who contribute data (e.g., temperature readings) via the open-source cizen science tool. - Satellite Data Providers: Enes or agencies offering satellite imagery and baseline remote-sensing data (e.g. Copernicus, scienfic instutes etc). Value creaon: Rich, high-quality dataset, localizaon of data, cizen engagement Tier 2 (Data Integraon and Modelling) involves merging and refining the validated datasets. This includes downscaling satellite imagery using high-resoluon drone data, aligning different data sources for consistency, and developing advanced models—such as convoluonal neural networks (CNNs)—to predict thermal condions. Image segmentaon techniques (e.g., separang streets, buildings, and vehicles) and classificaon of roof types and surfaces further enhance model accuracy by enabling more precise interpretaons. As a result, this er produces coherent, high-resoluon microclimate and heat maps that highlight localized temperature paerns and potenal hotspots. Key Stakeholders: - Data sciensts and AI specialists: Experts who clean, merge, and analyse the data while refining AI models. - Climate modelers and researchers: Professionals developing or adapng microclimate models to local condions. - Specialists in spaal data processing, satellite downscaling, and geospaal analycs. Value creaon: Transformaon of raw data into aconable Insights, high-resoluon predicve service, scalability and adaptability. Tier 3 (Service Delivery and Use) focuses on disseminang these heat maps, forecasts, and decision-support outputs to diverse end-users, including municipal authories, tourism stakeholders, and social instuons (e.g., schools and elderly care centres). These stakeholders leverage the localized insights to implement targeted intervenons—such as opmizing cooling strategies, adjusng urban development plans, or issuing mely public advisories—to migate heat-related risks. By providing tangible, locaon-specific informaon, the service fosters urban resilience, supports public health iniaves, and improves resource allocaon, ulmately delivering significant socio-economic and environmental benefits. Key Stakeholders: D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 33 - City Management and Municipal Authories: Responsible for urban planning, climate adaptaon, and infrastructure upgrades. - Tourism Boards and Businesses: Ulize heat/microclimate informaon to improve visitor experiences and safety. - Social Instuons (Schools, Care Centres, Hospitals): Implement measures to protect vulnerable populaons using localized climate data. - Residents and Community Groups: Benefit from publicly available insights to adapt daily acvies or advocate for environmental improvements. Value creaon: Locaon-specific, decision-ready informaon that improves urban planning, protects vulnerable groups and boosts city resilience. Aconable, hyper-local insights drive cost-effecve cooling measures. Story-telling visualisaons (before–aer, “what-if” scenarios) help engage cizens Tier 4 (Cizens, society and expansion to other Economic Sectors): The wider “cizens, society and the environment”, are the end beneficiaries of the climac service. Beer services support urban development, beer environmental condions and cizen wellbeing. Energy providers may use temperature forecasts to opmize grid management and reduce peak loads; insurance companies can refine risk assessment models for heat-related claims; and real estate developers can integrate microclimate insights into sustainable building design and site selecon. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 34 Figure 24: Understanding of the proposed value chain for the Climate Services developed in the Budapest Living Lab (Hungary). D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 35 6.4 Third iteraƟon: analyse the benefits In the third iteraon, the goal is to examine the potenal benefits—especially economic ones—arising from the service and, where possible, to quanfy them. The Budapest Living Lab’s climate service offers a forward-looking soluon to urban heat-related challenges through a highly localized, data-driven, and user-focused approach. By integrang drone-based thermal imagery, manual temperature measurements, cizen science contribuons, and satellite downscaling, the service delivers accurate, high-resoluon microclimate data and forecasts. These services offer a range of social and economic benefits that may not be directly expressed in monetary terms. These benefits include improving public health (e.g., reducing heat-related illnesses), enhancing tourist comfort (potenally boosng local business revenues), and supporng more efficient urban infrastructure management (for example, lower cooling costs in heatwaves). The monezaon of the CS added value may be difficult, in terms of esmang the leveraging effect which these services may have on speed of implementaon and spaal accuracy for intervenons against urban heat challenges. An esmaon of the value of the service can be drawn from an esmaon of the potenal economic benefits from intervenons that can be leveraged by the developed CS. This leveraging effect can be idenfied in (a) the spaal accuracy of informaon, (b) the quality of data and (c) the fact that the proposed CS can act as a catalyst to accelerate the implementaon of appropriate intervenons. Hence, an economic evaluaon of intervenons that could be supported by the developed CS was conducted instead, using a direct cost (avoided cost) approach, focusing on scalable urban cooling strategies such as highalbedo roof coangs, reflecve pavements, and green infrastructure. Spaal and thermal data from two central Budapest districts (Terézváros and Erzsébetváros) informed the calculaon of eligible surface areas and associated temperature reducons. Details are given in Annex A (“Assessments on Value esmaon from the Budapest LL”) of the present deliverable. Results show the following:  Maximum surface temperature reducon at street level: - District 6: 2.39°C - District 7: 1.52°C  Maximum surface temperature reducon from roof coangs: - District 6: 1.71°C - District 7: 0.94°C (Note: For individual buildings, this reducƟon could reach 3–5°C, resulƟng in percepƟble improvements in thermal comfort.) Using these inputs, a Net Present Value (NPV) analysis was conducted for District 7, based on a total treatment area of 1,634,784 m² and an assumed coang cost of €10/m². The lifespan of the intervenon was set to 10 years, with 50% reapplicaon costs at Year 10 and Year 20. An annual benefit of €2 million was used to reflect energy savings, reduced cooling loads, and improved infrastructure performance. Even without including mortality impacts, the current model yields a posive NPV of approximately €9 million over 30 years for district 7 of Budapest, demonstrang financial viability under conservave assumpons. When potenal health co-benefits are included, the intervenon becomes not only economically advantageous but socially and ethically compelling. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 36 6.5 Fourth iteraƟon: analysis beyond the defined boundaries 6.5.1 Primary market segment idenƟficaƟon KER* Idenfier Expected TRL Time to Exploit Descripon Integrated urban heat visualizaon service 6–7 <1 year An urban heat climate service that integrates stac drone-based thermal maps, a web-based interacve GIS plaorm, and real-me sensor dashboards. It enables idenficaon, monitoring, and communicaon of urban heat exposure through high-resoluon georeferenced maps, spaal data layers (e.g., LST, OSM), future climate scenarios, and contextual stascs. Supports data-driven decisionmaking, public awareness, and adapve planning through before–aer comparisons and scenario evaluaons. CityZcan (cizen science) monitoring dashboard and IoT sensor box 6 <1 year A real-me dashboard powered by CityZcan IoT sensor boxes that measure air temperature, humidity, PM2.5, and capture infrared thermal images. Designed to engage cizens in data collecon and raise awareness during heatwaves, the system provides live microclimate updates, colorcoded alerts, and integrates with municipal dashboards. It enhances public accessibility and supports health advisories by visualizing real-me heat and air quality risks across the city. Urban heat data analycs and vulnerability mapping toolkit 5–6 1–2 years A combined toolkit for analysing urban heat paerns and idenfying vulnerable neighbourhoods. It includes script-based processing of drone thermal imagery for surface classificaon and temperature profiling, and a Heat Vulnerability Index (HVI) that integrates thermal, socioeconomic, and health data. The toolkit supports planning and evaluaon of cooling intervenons, public health risk assessment, and visual communicaon through stascal graphs, segmentaon masks, and choropleth maps. Further development depends on access to detailed demographic and health data. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 37 KER* Idenfier Expected TRL Time to Exploit Descripon Urban heat awareness and gamificaon toolkit 6 <1 year A mul-format awareness and engagement toolkit designed to promote understanding and behavioural adaptaon to extreme heat and climate change. It includes educaonal videos, a public roll-up banner, a short documentary film, visuals for children (e.g., puzzle), and a serious game in the form of a cardbased gamificaon toolkit. The game explores drivers of adaptaon behaviour and helps players grasp climate service concepts through interacve learning. Tailored to diverse audiences—including cizens, students, and community groups—this toolkit supports climate literacy and parcipatory engagement. * Key Exploitable Results In the current phase of development of the Budapest Living Lab (LL) the Budapest districts of Terézváros (VI) and Erzsébetváros (VII) are targeted as the primary market segment for the urban heat visualizaon climate service. The broader naonal or European scale as a relevant market segment is not considered at this point, although some elements of the service (e.g., the gamificaon tool) could be useful at a European level. Furthermore, the aim is to upscale the service across the enre city of Budapest as a next step. This decision is based on the fact that the service was co-designed and tested in close cooperaon with idenfied local stakeholders within the LL. These include:  Municipal authories and urban planners of District VI and VII  Cizen associaons engaged in climate adaptaon dialogues  Educaonal instuons and community partners involved in awareness-raising These actors have shown direct interest in adopng elements of the climate service – parcularly the stac thermal maps, real-me dashboards, and visual communicaon tools – as part of their urban adaptaon, communicaon, and parcipatory planning strategies. Given this close connecon and contextual integraon, it is logical to treat the LL as a well-defined and realisc primary applicaon environment. At the same me, the maturity level of the service is heterogeneous: while some components (e.g., thermal drone mapping and real-me dashboards) are near operaonal (TRL 6–7), others (e.g., Heat Vulnerability Index) require addional data integraon and validaon. This also limits the feasibility of immediate scaling beyond the local context. 6.5.2 ImplicaƟons for Market Analysis Given that the primary market segment is limited to the local LL and a broader market opportunity has not yet been validated, we do not consider it meaningful to proceed with a full market analysis at this stage. The climate service, in its current form, is not yet posioned as a market-ready product intended for commercialisaon. Its value lies primarily in capacity-building, policy support, and parcipatory learning, not in generang profit or penetrang a compeve marketplace. 6.5.3 Open Source Strategy and Future PotenƟal Throughout the design and development of the service, an open source strategy has been applied. This has D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 44 paerns and speed, traffic management at the ports is impacted by storms and heat, while decisions related to port defences are impacted by availability of funding and overarching policies regarding tourism. The Municipal Port Authority Fund of Rethymno uses weather forecast data from the naonal meteorological service as well as other sources and combines it with previous experience for short-term decision making. Also, conducts or procures studies regarding management and development of the port works which manages or plans to construct. The Port Authority is an organizaon informed of recent developments on climate data, and has co-operaon with scienfic instutes. Sll, decisions on short-term, seasonal and annual aspects of port management are taken based on past experience, analysis of historic meteorological records and weather forecasts. Soluon (User Requirements) ID User requirements As a <ROLE>, I would like to <GOAL> to <BENEFIT> GR5 As a port manager… …I would like to know the frequency of North winds above 7 Beaufort for the upcoming period (short-term to seasonal) … …to decide upon possible preparaons on port defences GR6 As a port manager… …I would like to know the frequency of North winds above 7 Beaufort for the upcoming 10 years … …to plan the upgrade, maintenance works or construcon of addional, necessary port defences. GR7 As a port manager… …I would like to know the frequency of South winds above 7 Beaufort for the upcoming period (short-term to seasonal) … .. to beer plan port traffic management, especially of large vessels and avoid damages on floang plaorms GR8 As a port manager… …I would like to know the frequency of extreme heat or prolonged heat events for the upcoming period (short-term to seasonal) … …for increased preparedness of related impacts to the port zone. Soluon (TO-BE Scenario): I-CISK aspires to expand the informaon base for the Port of Rethymno and to incorporate in the workflow of Port Authority advanced predicve tools of seasonal as well as decadal scales. A seasonal forecast (6 months ahead) service for high magnitude winds in combinaon with stascs (frequency) supports efficient port management before the high-demand tourisc (summer) period and mely response during extreme events, offering increased performance and lower maintenance costs in the long run. Decadal predicons provide informaon on possible wind magnitudes and frequency of events for beer planning of defence works. Value Proposion (Goal of the service): Timely and detailed informaon on future wind magnitude and frequency is very important to port traffic management as well as strategic planning. It will enable Port Authority to be proacve and migate the impact of high wind and surge effects. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 45 Tourism sector (hospitality) – qualitave assessment of the gains Locaon: Elounda hotels and resorts are located in the eastern part of Crete Island, (see Figure 29). Elounda is a collecon of three villages, Ano (upper) and Kato (lower) Elounda sing above the port, Skisma, nestled at the head of the bay of Elounda with a view of the Venean castle on the island of Kalydon, the famous “Spinalonga”. The corner of the Mirabello bay, with the Spinalonga peninsula and its myriad anchorages is a yachng paradise. Figure 29: Elounda resort (photo from site: hps://www.elounda-sa.com/). End User(s): Elounda SA hotels & resorts owns and manages three luxury properes in the area of Elounda in Crete, Greece. The company is responsible for making the area the top luxury vacaons desnaon in Greece. The Elounda Mare hotel is member of the presgious Relais & Châteaux chain in Crete. The Porto Elounda GOLF & SPA RESORT is the only spa & golf resort on the island. All three properes have received awards and disncons and have established a strong brand in the luxury hotel industry. The hotels also offer culinary experiences, private sandy beaches, Children’s club, a 9-hole par-3 golf course, the Aegean Conference Center, yachts for charter, Scuba diving, Water sports, tennis courts, shopping arcades. Challenge: Maintenance of large, coastal facilies can be a significant managemental burden, even more for luxury resorts, when demands for quality services (including facilies infrastructure) is high. Invesng on facilies upgrades (e.g. advanced air-condioning systems of low energy consumpon, redacon of heat losses etc) is costly and should be carefully planned. Further, under the lens of the fierce compeon in the tourist business, the smooth provision of tourist services is a prerequisite for successful businesses. The hospitality sector builds trust with the visitors and reputaonal risks are taken seriously. Climate change is creang condions of more common and unpredictable extreme events which may impede large scale maintenance works. Even more, extreme weather condions (long periods of heat, extreme heat events, significant precipitaon events) pose a significant health risk regarding outdoor acvies which are oen part of the offered product of tourisc businesses. Managing these risks is important for maintaining a valuable tourisc product. Current pracces in place (AS-IS Scenario): For resort managers, planning of outdoor acvies (maintenance in the autumn months, planned guest acvies during tourist season such as yachng, hiking, bicycle rides etc) is key operaonal procedure. Coinciding with periods of high winds, heavy precipitaon or extreme and/or prolonged periods of heat is a significant risk which should be avoided. Up to now, such challenges are predominantly dealt by re-acon to events, previous experience (e.g. which periods usually have favourable weather) and short-term forecast (weather) predicons. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 46 Soluon (User Requirements) ID User requirements As a <ROLE>, I would like to <GOAL> to <BENEFIT> GR9 As a resort/hotel manager… …I would like to know if and when are heavy precipitaon events and/or strong wind events to be expected for the upcoming low season tourisc period (November to February) in me… …to decide upon the scheduling of maintenance works. GR10 As a resort/hotel manager … …I would like to know if and when are heavy precipitaon, strong wind, extreme heat events to be expected for the upcoming high tourisc season period (May - September) in me… …to decide upon the scheduling of outdoor acvies. Soluon (TO-BE Scenario): I-CISK aspires to expand the informaon base for resort/hotel managers and to incorporate in the workflow advanced predicve tools of seasonal scales. A seasonal forecast (6 months ahead) service for heavy precipitaons events, high magnitude winds and frequency of extreme heat events supports the management planning: (a) of maintenance works with lower risks of rescheduling and (b) outdoor acvies for the visitors with lower risks regarding weather related health dangers. Value Proposion (Goal of the service): Timely and detailed informaon on future extreme weather events and frequency is very important to resort/hotel management. It will enable tourisc businesses in the hospitality sector to lower maintenance costs in the long run and increase visitor sasfacon, trust rates and reputaonal gains. 7.3 Second iteraƟon: Understanding the value chain To understand how the use of the developed CS helps actors along the value chain to address the challenges they face at an operaonal level, a descripon of the value chain is built in a 4-er analysis based on the methodological framework described in MS26 (Guidelines for Value Chain assessment, June 2024), which is resumed in Figure 30. The goal at this point is the analysis to be sufficiently informed the develop the understanding of the economic, social and environmental benefits and to complete the User Stories. Tier 1 is the “supplier” of the climac data i.e. the seasonal forecasng data of essenal variables or impact models results. EU, through dedicated services and programs such as Copernicus, provides climac data to a large end-user group. ECMWF as a scienfic organizaon generates and provides high quality climac data of seasonal forecasts which may be used by downstream services “as is” or are repurposed through impact modelling by scienfic instutes (in present case SMHI, the Swedish Meteorological and Hydrological Instute) which widen the services of climac data (e.g. seasonal forecasng of river flows). Their benefit from providing climac data could be: (a) scienfic: receiving feedback which allows to enhance their data quality, (b) economic, through the provision of data services and (c) business-oriented, by achieving reputaonal gains and expanding their partnerships and data provision services. Tier 2 is the “primary user” (this is also referred to as intermediary user) of the climac service. EMVIS SA develops a state-of-the-art product-service that transforms the value of the climac service, acng as knowledge purveyor between the supplier (er 1) and the end user (er 3) of the climac service. Through D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 47 this process, EMVIS SA enhances its ability to provide added value (innovaon gains), develops services which increase its market share and provide addional revenue (economic gains) and builds on its reputaonal profile which also supports the expansion of partnerships (entrepreneurship gains). Tier 3 is the “secondary user” i.e. the end user of the service provided by the primary user. The Water Management Operator, Organisaon for the Development of Crete (OAK), incorporates the developed CS in the organizaon’s workflow. In that way OAK can improve its operaonal acvies by taking water management decisions which: (a) increase revenue gains (selling more water, i.e. economic gains), (b) improve the management of water resources of the island and therefore beer achieving environmental compliance (environmental gains). Managers of the transportaon sector, i.e. OAK (large road network manager), Port of Rethymno organizaon (port manager), can beer organize (preparedness) maintenance of sector which may reduce the relevant costs (economic gain), may improve operaonal procedures (decrease losses due to informed port traffic redirecon – economic gains) and increase public acceptance of works and decision (reputaonal gains). The hospitality industry (from resorts to smaller businesses) can beer organise maintenance works (sufficient workflows, lower costs – economic gains), increase visitor trust and sasfacon rate (reputaonal gains), which may lead to increased re-visit rates and visitor numbers and consequently to revenue increase. Beer informed DMOs (Desnaon Management Organizaons) can beer plan and target adversing which translates to a potenally more successful strategy (and therefore increase in revenue). D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 48 Figure 30: Understanding of the value chain for the Climate Services developed in the Crete Island Living Lab (Greece). D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 49 Tier 4 includes the other economic sectors which are associated indirectly with the tourism product as well as the wider “cizens, society and the environment”, which are the end beneficiaries of the climac service. Beer services (water, transport, hospitality) support the tourisc product (reputaonal gains) which may increase vising rates and further development of the island economy (increasing revenue). The cizens and society enjoy the end result of the climac service as enhanced water availability and beer environmental condions. Due to beer management decisions, they may enjoy water availability, especially during dry years, and possibly at unaffected or lower prices (economic gains). Further, beer water management means enhanced water security which, in combinaon with improved environmental condion and enhanced transport-infrastructure condions translates into broader societal gains. 7.4 Third iteraƟon: Analyse the benefits Up to this point, the analysis has focused on understanding and seng out the perimeter of the case analysis. The next stage is to analyse the benefits idenfied and quanfy them where possible. It is noted that the analysis presented in the following, targets the assessment of part of the value idenfied in the 2nd Tier of the value chain analysis, based on assessing the values for the 3rd Tier of the value chain. Where the analysis can demonstrate potenal economic gains or avoided costs, quanficaon is most preferable to lead to actual financial benefits. The economic benefits are those related to the economic performance of the actors at each er of the value chain. By definion, the benefits can be monezed although this is not always easy. This is the hardest part of analysing the benefits and consumes the most me and effort. It requires the development of models represenng the way in which the business process is generang value. Oen, direct figures are not available from the stakeholders and one must rely on assumpons which should be clearly stated. As described in the introducon of the current paragraph (par. 7), the CS codeveloped within the Crete Island LL, has been co-designed under the frame of a mul-sectoral approach, addressing needs and challenges from cross-cung sectors, including tourism sector, water management, transportaon infrastructure (roads, ports) and energy sector. Given the above, it would not be realisc to aim for quanfying and monezing the benefits from all the sectors, due to the various needs on informaon and the me restricons within the I-CISK project. For these reasons, for the LL of Crete, the monezing analysis focuses on the CS for the water-manager needs and approaches the other sectors through a more qualitave assessment. Water management sector – quanfying the gains There is a wide variety of methodologies to assess the value of climate services. In the current case a methodology is applied that is based on the value of informaon and decision theory, as described in relevant applicaons in the CLARA project (see Bosello F. et al., 2021). This methodology beer suits the part of the CS that refers to the water management sector. Details of the applicaon are given in Annex B (“Quanfy the benefits of the CS for the Water Sector - Crete Island LL”) of the current deliverable. The value esmated by this approach is based: (a) on a theorecal performance of the service, which refers to a hypothecal or historical scenario and (b) on the esmaon of the value by specific end-users. This means that the value esmated is somewhat relave, since if the hypothecal tesng scenario or the end-users evaluang the service change, then the value may change. The value is esmated comparing the potenal gains that an end-user may have for the evaluaon period by using the CS and taking informed decisions against the results of decisions based on current pracces. The gains from the use of the service are related to the potenal of the reservoir to offer the intended services, based on the water stored. That is, when the water managers achieve stored water at a level which can serve drinking water needs, energy producon and flood protecon, the gain is maximised. Too much water, or too D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 50 low reserves, both lower gains (see for details Annex B). Addionally, when the planned abstracon (average condions, maximum use of the reservoir) can be increased by 100%, then an added maximum abstracon payoff is reached. Assessments were performed for three hypothecal scenarios: Scenario 1: an average hydrological year which is based on actual data from the past decade and an assumpon of full ulizaon of the reservoir’s water, as planned. Scenario 2: an average hydrological year which is based on actual data from the past decade. However, the irrigaon withdrawals (not the drinking water withdrawals) reach half of the full ulizaon planning. Scenario 3: a dry-period scenario which is based on a hypothecal two-dry years in sequence and the assumpon of full ulizaon of the reservoir’s water. In this scenario, drinking water withdrawals triple, in comparison to Scenarios 1 and 2, while irrigaon withdrawals are the same with scenario 2. This is a worstcase scenario, minimizing inflows for two years and maximizing water allocaon needs. The increase of gains is summarized in Table 7. Scenario 1 is close to a full ulizaon of the reservoir reserves and therefore there is limited room for changes in water abstracon during the tourisc period, when they are needed most. However, the CS demonstrated potenal gains (26% increase). Scenario 2 provides beer opportunies for maximizing the gain from the CS forecasts because the reservoir is not ulized in its full potenal by the agricultural sector (irrigaon). In this case the gains from CS use are significantly higher (110% increase of gains). For Scenario 3, the unfavourable two-years of low inflows (dry years) led also to the need for reducing the abstracons, hence to negave abstracon gains payoff during the second year. However, even under these condions there is sll some room for gains (4% increase). Table 7: Gains by the use of the CS for the three climac scenarios examined Scenario Increase o f gains by use of CS % 1 26% 2 110% 3 (dry years) 4% Based on the above steps towards assessing the potenal gains in a quantave approach, the CS demonstrates benefits that range from LOW to HIGH, depending on the climac scenario examined. It is noted that the above calculaons are based on three scenarios of the climac condions and ulizaon of the reservoir. These scenarios cover some favourable, average and unfavourable condions but it is recognized that other condions may lead to different results. Transportaon infrastructure sector – qualitave assessment of the gains The evaluaon of the service is based on idenfying appropriate indicators which represent potenal benefit for the end-user and hence, demonstrate a value for the CS. To support transportaon infrastructure, with focus on port management, during the co-creaon process specific needs were idenfied which translated into tailored climac indicators to support decision making. The Municipal Port Authority Fund of Rethymno idenfies the southern winds above 7 Beaufort as directly correlated to the stress induced on the port floang plaorms. The logical steps which lead to the coidenficaon of the value of the specific CS have been idenfied as follows: - These winds put pressure on the floang plaorms because they push the docked ships and smaller vessels to move with force against the plaorms and cause damage D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 51 - South winds are not prevailing (low frequency) in the area but can reach larger magnitudes - The damage varies depending on the size of ship and can be from minor to major - This damage is dealt with periodically by the Municipal Port Authority Fund, on a per occurrence basis. - The damages can be dealt with maintenance works or complete replacement depending on the damage - The port authority idenfies that the annual costs of these damages range around the scale of medium, in comparison to the total annual costs of the Port Fund. - Another possible related cost, is the revenue loss due to the ships which will be directed to avoid docking to the port due to the winds. - On an operaonal basis, if seasonal forecasng would provide good informaon on the expected frequency of these winds, especially for periods of heavy traffic for the port, then probably the Port Fund could reschedule the dockings or beer plan them to allow for beer allocaon of vessels within the port - That could probably lead to: o (a) smaller damages to the floang plaorms and o (b) less revenue losses due to last minute rescheduling of ship dockings Based on the above reasonable steps towards idenficaon of the value chain and on the scaling of benefits given in Table 1, the service demonstrates two specific benefits. Based on the reasoning of “avoided costs” which are idenfied by the end-user as medium, the benefit of the service is idenfied as: MODERATE . Tourism sector (hospitality) – qualitave assessment of the gains The evaluaon of the service is based on idenfying appropriate indicators which represent potenal benefit for the end-user and hence demonstrate a value for the CS. To support the tourism sector (hospitality), during the co-creaon process specific needs were idenfied which translated into tailored climac indicators to support decision making. The Crete LL stakeholder idenfied two very specific climac challenges related to the management of their facilies. The logical steps which lead to the co-idenficaon of the value of the specific CS have been idenfied and followed separately for each challenge: Annual needs of extensive maintenance works - Most of hospitality facilies need to schedule maintenance works - These works take place during the low season which is mainly during the late autumn and winter period - The maintenance period coincides in me with periods of events of heavy precipitaon and/or wind. - If extended works are planned and have to be cancelled due to unfavourable condions, this has addional costs and poses a management burden for re-planning. - This cost of re-planning and stopping of works, could range from low to moderate economic burden. - If, under a changing climate, a more robust planning system based on a CS, for operaonal use could be available, there exist gains, potenal of importance. - That could probably lead to: D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 52 o (a) avoidance of stopping of works, which would cut down the costs of restarng the works in another period (costs related to longest period of reserved maintenance services) o (b) less revenue losses which are related to management costs Seasonal planning needs on outdoor acvies - Tourist hospitality facilies, especially larger or more luxurious ones, commonly offer a series of opons for organized outdoor acvies during the tourisc season. - Extreme weather events such as heatwaves or summer heavy precipitaon and/or floods hinder these outdoor acvies. They also pose danger to the visitors - On an operaonal basis, if seasonal forecasng would provide good informaon on the expected frequency of extreme events, then probably the management of resorts could beer schedule the acvies to avoid dissasfacon of customers or even exposure to serious health hazards. - This could lead to: o (a) reputaonal gains of the facilies and o (b) potenal increase on revisit rates Based on the above reasonable steps towards idenficaon of the value chain and on the scaling of benefits given in Table 1, the service demonstrates four (4) specific benefits for two (2) different value indicators. Based on the reasoning of “avoided costs” which are idenfied by the end-user as low to medium, the benefit of the service is idenfied as: LOW to MODERATE . Tourism sector (as a whole) – quanfying the gains The CS developed in Crete LL is based on a mulsectoral approach towards the Tourism sector. Quanfying the benefits of the service to the Tourism sector requires considering complicated interacons between the sectors. In order to approach the above, we apply a methodology of quanficaon using a system dynamic model. This model effecvely demonstrates how the implementaon of CS products can improve informed and sector-specific decision-making processes in these sectoral domains. The approach is provided in Annex C (“Quanfy the benefits of the CS for the Tourism Sector - Crete Island LL”) of current Deliverable. According to the results of the model, the use of CS products developed following a mul-stakeholder, mul- sectoral approach, may lead to an increase in the values of the sector-specific indices that gauge the effect of CS products across the selected sectors (tourism, water, transportaon, energy) ranging from 4% to 14%, aributable to the mul-sectoral approach implemented on the island of Crete. The above indicates an average 10% increase of the sector-specific indices of the sectors addressed by the CS for tourism in Crete. Taking into account that this approach considers the overall effect of the CS on the addressed sectors, over the whole island, for a period up to the end of century, this is an important indicaon that the CS developed may have significant benefits for the Tourism sector as a whole. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 53 7.5 Fourth iteraƟon: analysis beyond the defined boundaries 7.5.1 Defining the market boundaries Defining the segments Segmentaon is the first key step of the product-specific approach to be adopted in the Market Analysis and it is the basis to study the needs and behaviour of potenal end-users. Aaker and McLoughlin (2010: p.26) define market segmentaon in the context of strategic market management as “the idenficaon of customer groups that respond differently from other groups to compeve offerings”. In other words, groups of actual and potenal customers are aggregated based on similaries in their needs and other variables like geographic locaon, customer type and benefits sought. In general, the markeng literature seems to agree that there is no single way to segment a market (e.g., Kotler and Armstrong 2013). This is in part because the set of variables used may differ depending on the marketer’s choice and the market type (consumer market, business market, internaonal market). Furthermore, the exercise can be undertaken from different viewpoints: segmenng by customer characteriscs (e.g., age and interests) or looking at product characteriscs (e.g., benefits provided and potenal applicaons). The I-CISK project had from the conceptual phase a clear proposion as far as the targeted users of the developed services. As climate change is cung across mulple societal, economic and environmental domains, a clear link to well-defined market segments and their needs, directly impacted from climate change induced threats had been idenfied as sectors having significant business opportunies. In the case of the broader tourism sector, those market segments included hospitality services management, water resources management, energy producon and transportaon. The insight gained from the elicitaon exercise allowed the idenficaon of addional targeted market segments and a beer classificaon of potenal CS users among the already idenfied ones, based on similaries idenfied in respect of their needs, specific requirements and other variables like geographic locaon, customer type and benefits sought. This has led to a beer clustering of the targeted market segments in Tourism Sector e.g. Hotels, Desnaon Management Operators etc. and enabled the idenficaon of potenal users in various sectors menoned above. A non-exhausve list of candidate customer groups based on user type and common challenges has been prepared and is presented together with user group descripons in Table 8. An overview of the idenfied user groups is presented in Figure 31. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 60 7.5.2 Market Analysis Esmang the potenal size of the target market Hospitality Sector Having selected a target group (see Secon 7.5.1) the next task is to esmate the potenal business that can be generated from addressing its needs. To elaborate this approximaon, the following steps were taken:  Esmang the total number of addressable customers in the target group or Total Addressable Market (TAM). This metric provides the enre potenal market independently of the ability to reach it and serve it yet. Considering the nature of the target group (Naonal Tourism Operaons and Desnaon Management Operators), the necessary informaon upon which current esmates are based, was found in European/naonal/regional stascs databases, industry associaon reports and other documents.  Assuming a market penetraon rate and calculang the potenal Serviceable Addressable Market size (SAM). This metric can be used as an approximaon of the potenal customer base that can be actually served and reached for delivering the developed CS services. Penetraon rate was assumed on the basis of the circumstances that drive the target group’s needs (e.g., Proacve management of climate change threats), the priority assigned by the target group to this need (i.e., their willingness to act upon it), and the addional requirements that the target group would have to cover to benefit from your product (e.g., training, equipment). The ability to reach this market poron is not assessed at this point of the analysis.  Assessing the share and poron of the target market that can be captured that is the Serviceable Obtainable Market (SOM). Esmaons on this metric have been based mostly on the level of compeon idenfied for similar services to the offering of the developed CS.  Finally, calculang the potenal monetary value of the market (Sp€). This is the product of the potenal Serviceable Obtainable Market size (SOM) and the expected sales value, i.e., the price of the product (P). The potenal monetary value of the market is not assessed at this point of the analysis. In the process of analysing the market opportunity for the Crete LL I-CISK services, the following crical aributes were idenfied and used as indicators for increased market uptake. Considering that the primary market consists of Tourism Organizaons across Europe, specifically Naonal Tourism Operators (NTOs) and Desnaon Management Operators (DMOs), the market analysis was conducted using data from Eurostat, the World Bank, naonal stascs datasets and other relevant sources. This analysis provides esmates on the number and budget of NTOs and DMOs as well as economic indicators such as the contribuon of tourism sector in each country’s GDP. NaƟonal Tourism Operators (NTOs) in Europe. There are 38 Naonal Tourism Organizaons (NTOs) operang across Europe, typically one per country. For the purposes of this market analysis, the focus was placed on the 27 NTOs within the European Union. This decision was based on the greater availability of financial and stascal data for EU member states, succeeding more reliable and comparable esmates. The Total Addressable Market (TAM) represents the full economic value of the tourism industry in Europe. Based on travel receipts data from Eurostat (2022), the tourism sector across the European Union generated 146.9 billion euros26 (Figure 32). 26 Travel receipts and expenditures in balance of payments – Eurostat (hps://ec.europa.eu/eurostat/stascsexplained/index.php?tle=Tourism_stascs) D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 61 Figure 32: Tourism revenues in million euros by EU member state 2022 (Source: Eurostat27). The Serviceable Available Market (SAM) is the total public spending by Naonal Tourism Organizaons (NTOs) in Europe. To esmate this, we used the budget of the Greek NTO (EOT)28 for 2022 as an indicator. We adjusted this amount proporonally based on each country’s tourism contribuon to GDP. This is a reasonable esmate of the potenal public budgets allocated to similar tourism organizaons across European Union. A summary of tourism contribuon to GDP and the esmated NTO budgets per EU member state is presented in Table 10. Table 10: Esmated Naonal Tourism Organizaon budgets and tourism contribuon to GDP across EU. EU Member State Gross Domesc Product (GDP) in billion euros Percentage of tourism contribuon in GDP Naonal Tourism Organizaon budget per member state in million euros Belgium 596.3206 6% 48.77 Bulgaria 94.7093 7% 9.72 Czechia 317.3858 6% 25.96 Denmark 376.43 7% 36.39 Germany 4185.55 11% 684.69 27 hps://ec.europa.eu/eurostat/stascs-explained/index.php?tle=Tourism_stascs 28 Budget implementaon of the Greek NTO “EOT” (hps://gnto.gov.gr/stoicheia-ektelesis-proypologismou-eot/) D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 62 EU Member State Gross Domesc Product (GDP) in billion euros Percentage of tourism contribuon in GDP Naonal Tourism Organizaon budget per member state in million euros Estonia 38.1878 9% 5.22 Ireland 509.9518 4% 28.82 Greece 225.1969 19% 64.30 Spain 1498.324 15% 323.09 France 2822.4546 9% 369.37 Croaa 78.0485 26% 29.95 Italy 2131.39 11% 332.81 Cyprus 31.34 13% 6.01 Latvia 39.3724 8% 4.39 Lithuania 73.7928 5% 5.71 Luxembourg 80.9919 9% 10.24 Hungary 197.902 7% 21.78 Malta 20.5414 14% 4.15 Netherlands 1067.599 10% 152.41 Austria 473.2267 11% 74.60 Poland 748.9234 4% 45.66 Portugal 267.9232 20% 78.09 Romania 324.3686 6% 27.01 Slovenia 63.9512 10% 9.32 Slovakia 122.9189 5% 8.77 Finland 272.782 7% 28.80 Sweden 541.184 7% 57.14 While the combined budget of European NTOs is esmated at 2.31 billion euros, based on the assumpons we menon above, not all of it is allocated to external services. A large poron covers fixed costs such as staff salaries and administraon expenses. We conservavely esmate that approximately 25 - 30% of this budget is allocated to external services, such as consulng, markeng, and climate-related services. This results in a Serviceable Available Market (SAM) of 577–693 million euros. The Serviceable Obtainable Market (SOM) represents a realisc revenue potenal from targeng a subset of NTOs. We can assume that it is possible to approach 8 to 10 NTOs, therefore, it is assumed a percentage of 30% out of SAM size due to the highly compeve advantages recognized at I-CISK Climate Services which results in an esmated SOM of approximately 171 – 205 million euros. DesƟnaƟon Management Operators (DMOs) in Europe. The other target group of the tourism sector with high score aracveness is the Desnaon Management Organizaons group. A total of 103 Desnaon Management Organizaons (DMOs) currently operang in the D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 63 European Union have been idenfied through directories such as ECM - European Cies Markeng29. These organizaons are responsible for the management and promoon of tourism at city level. In some cases, a Naonal Tourism Organizaon (NTO) may also serve as a DMO, parcularly when the desnaon being marketed is the naon as a whole. However, within the framework of this analysis, the sub-naonal level (cies and local desnaons) rather than the naonal one is priorized. The average annual budget of Europe’s DMOs is less than 5 million euros (Borzyszkowski, Jacek 2015). Based on public data of city of Athens DMO, we can approximate that each of the 99 EU DMOs have an average annual budget of 3.5 million euros. The esmate assumes that city-sized DMOs in the EU have a similar setup, ranging from availability of public funds as well as potenal EU funds. Out of a total of 99 DMOs exisng in the European Union and with the City of Athens DMO as a comparave reference budget (3.5 million euros annually), the Total Addressable Market (TAM) is esmated at 346.5 million euros (Table 11). If it can be assumed that 25–30% of the budgets for DMOs are used for external services, the Serviceable Available Market (SAM) is 87–104 million euros. A conservave market penetraon of 30% esmates a Serviceable Obtainable Market (SOM) of approximately 26–31 million euros. Table 11: Potenal Size of the Target Group for TMOs and DMOs for the EU Context. # Total Addressable Market Size (TAM) Serviceable Addressable Market size (SAM) Serviceable Obtainable Market size (SOM) Comments/ Assumpons TMOs 146.9 billion euros 693 million euros 205 million euros Note 1 DMOs 346.5 million euros 104 million euros 31 million euros Note 2 Note 1: The (TAM) number is based on every EU c ountry's total contribuƟon of tourism to their GDP and serves as a measure of the overall size of the tourism sector in the EU region. For the esƟmaƟon of the SAM number, it is assumed that a percentage of 30% (indicaƟvely) out of NTOs budget can be reached, based on esƟmated budget commitments for external services. The ability to reach this market porƟon is related to the distribuƟon model and has not been assessed at this point of the analysis. For the esƟmaƟon of (SOM) size it is assumed a percentage of 30% out of SAM size due to the highly compeƟƟve advantages recognized at I-CISK Climate Services. Note 2: The (TAM) number is calculated from the combined annual budget of the 99 DMOs across EU Region assuming that all of them are potenƟal clients for I-CISK Climate Services. For the esƟmaƟon of the SAM number, it is assumed that a percentage of 30% (indicaƟvely) out of TAM can be reached, based on esƟmated budget commitments for external services. The ability to reach this market porƟon is related to the distribuƟon model and has not been assessed at this point of the analysis. For the esƟmaƟon of (SOM) size it is assumed a percentage of 30% out of SAM size, due to the highly compeƟƟve advantages recognized at I-CISK Climate Services. Scenario 1 Scenario 2 29 hps://citydesnaonsalliance.eu/members/ 146.9 BEuros 693 MEuros 208 MEuros 346.5 MEuros 104 MEuros 31 MEuros D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 64 Figure 33: Esmated market segment metrics for various scenarios. Water Sector The methodology used to esmate the potenal business opportunies in the Hospitality service sector as presented in the previous chapter, is now applied to the selected segments of the Water Sector. This analysis is more extensive primarily because of the recognized potenal climate threats to water availability. To elaborate this approximaon, the following steps were taken:  Esmang the total number of addressable customers in the target group or Total Addressable Market (TAM). This metric provides the enre potenal market independently of the ability to reach it and serve it yet. Considering the nature of the target group (Reservoir Operators and Bulk Water Management Authories), the necessary informaon upon which current esmates are based, was found in naonal/regional stascs databases, industry associaon reports and other documents.  Assuming a market penetraon rate and calculang the potenal Serviceable Addressable Market size (SAM). This metric can be used as an approximaon of the potenal customer base that can be actually served and reached for delivering the developed CSs. Penetraon rate was assumed on the basis of the circumstances that drive the target group’s needs (e.g., Proacve management of water quanty threats), the priority assigned by the target group to this need (i.e., their willingness to act upon it), and the addional requirements that the target group would have to cover to benefit from the product (e.g., training, equipment). The ability to reach this market poron is not assessed at this point of the analysis.  Assessing the share and poron of the target market that can be captured that is the Serviceable Obtainable Market (SOM). Esmaons on this metric have been based mostly on the level of compeon idenfied for similar services to I-CISK offering.  Finally, calculang the potenal monetary value of the market (Sp€). This is the product of the potenal Serviceable Obtainable Market size (SOM) and the expected sales value, i.e., the price of the product (P). The potenal monetary value of the market is not assessed at this point of the analysis. In the process of analysing the market opportunity for I-CISK climate services of Crete LL, the following crical aributes were idenfied and used as indicators for increased market uptake. Number of reservoirs. Considering that the primary market segment of interest is Reservoir Operators and Bulk Water Management Authories in Europe, data from the World Register of Dams maintained by the Internaonal Commission of Large Dams (ICOLD) were analysed providing an esmaon of the number of reservoirs of interest (Figure 39). Reservoir/Dams Water Availability Across Europe, reservoirs play a crucial role ensuring water availability for public demand, irrigaon, and hydropower generaon. The potenal decrease in water availability could increase the demand for climate services that highlight such risks, enabling the development of effecve migaon strategies. Climate-induced drought is likely to threaten the reliability water storage facilies (e.g. reservoirs), while prolonged dry periods increase the risk of reduced levels of storage in reservoirs, directly affecng water security. According to the European Drought Risk Atlas30 the impact of droughts on water supply systems can be esmated by calculang changes in water abstracon needs. Parcularly, during dry periods, up to 10% addional annual water abstracon may be required in an effort to meet public demand. This addional demand may exceed the amount of water that reservoirs and other surface storage systems can reliably 30 European Drought Risk Atlas, Publicaons Office of the European Union, Luxembourg, 2023: hps://publicaons.jrc.ec.europa.eu/repository/handle/JRC135215 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 65 provide. While northern European Countries may be able to cope with such peaks due to water sources being more abundant, for southern European Countries with already increased demand may struggle to accommodate extra abstracons (Figure 34). Figure 34: Average annual loss (%) as a drought-induced increase in water abstracon for public water supply in European Union in NUTS-2 level (Source: European Drought Risk Atlas – Joint Research Center EU). Risk is projected to increase across most of Europe, especially in Mediterranean countries, mainly because of higher water demand during droughts (Figure 35). This could lead to more pressure on water suppliers, and possibly restricons on household water use. This is especially likely in the Mediterranean region, where we already see that during droughts events, water abstracons drop, showing that even usual demand cannot be fulfilled during current extreme events (European Drought Risk Atlas – 2023). Figure 35: Drought risk for water supply between current and projected climate condions. Risk is measured as average annual increase in drought-induced abstracon compared to the average expected value under D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 66 current climate condions. Results of future simulaons forced with 11 climate models in RCP 4.5 and RCP 8.5 are averaged for each warming level (+1.5 °C, +2.0 °C). The analysis was conducted at NUTS-2 level (Source: European Drought Risk Atlas – Joint Research Center EU). The Standardized Precipitaon Index (SPI) is an indicator used to quanfy meteorological drought, recording precipitaon deficits over a variety of me scales. More specifically, the SPI-6 measures anomalies in total precipitaon over a 6-month period and is commonly used to assess seasonal to medium-term drought severity. Negave values of SPI-6 indicate below average condions, and values below -1.0 indicate moderate to extreme drought. Figure 36: Annual projected change in Standardized Precipitaon Index (SPI-6) in Europe, relave to 19862005, under 1.5°C global warming scenario (Source: Copernicus Interacve Climate Atlas)31. The map above displays projected changes in SPI-6 index in Europe under a 1.5°C global warming scenario relave to the referenced period 1986 – 2005. Blue-shaded regions indicate an increase in SPI-6 and therefore possible weer future condions, while green-shaded regions indicate a decrease in SPI-6, meaning a greater likelihood of drought in those areas. As observed in Figure 36, Southern European countries such as Spain, Italy, Greece, Portugal, south France and parts of the Balkans are projected to experience reducons in the SPI-6 index, indicang increased vulnerability to drought-related impacts. Therefore, the projected changes in SPI-6 index and the possible increase in water abstracon during droughts (warming scenario 1.5°C) highlight the vulnerability of southern European regions. These areas face a greater risk of water shortages because of drought and should be considered as priority regions for climate change adaptaon planning. Therefore, we can use this informaon to segment the European market with the TAM–SAM–SOM framework. We can further segment the potenal market for a more detailed approach, considering that covering potable water needs is a first priority for the water authories. Therefore, we can idenfy which dams/reservoirs are also used for drinking water purposes. For EurEau members in total, about 55% of the water abstracted for drinking purposes comes from surface water, while groundwater holds an equally important proporon near 45%, with high variability among EurEau member countries to be observed (Figure 37). This percentage is based only on the countries that provided data. 31 Standardized Precipitaon Index (SPI-6) – Copernicus Interacve Climate Atlas - hps://atlas.climate.copernicus.eu/atlas D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 67 Figure 37: Sources of drinking water. Source: (EurEau, 2017)32 The country profiles as reported by EurEau members are similar to the stascs from the EU Final - Synthesis report on the quality of drinking water in the union examining member states' reports for the 2011-2013 period, under arcle 13(5) of direcve 98/83/EC. However, in the EU-27, drinking water is abstracted mainly from groundwater and surface water (e.g. drinking water dams), accounng for respecvely some 50 % and 36 % of the drinking water supply (EC, 2016). The distribuon of water sources in Member States is shown in Figure 38. 32 hps://www.eureau.org/resources/publicaons/1460-eureau-data-report-2017-1/file D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 68 Figure 38: Sources for drinking water in Member States (Data for 2011 to 2013). Source: (EC, 2016) The main areas with potenally increased interest in I-CISK CS Crete LL business proposion is considered to be those countries with both increased percentage of drinking water originang from surface water sources and moderate to high risk of drought impacts. For our analysis we use a threshold level of 30% of drinking water originated from surface water. The relevant countries include Cyprus, Greece, Bulgaria, Romania, Spain, Portugal and Italy. Subsequently, we can assume that the Total Addressable Market (TAM) includes the large operaonal reservoirs of all the European countries assuming that each dam is managed by a single operang authority. For the Serviceable Available Market (SAM) we count the reservoir operators in countries with both increased percentage of drinking water originated from surface water and moderate to high SPI-6 drought projecons, therefore indicang an increased demand for climate services (Note 2 - Table 12). For the Serviceable Obtainable Market (SOM) we can assume based on market interest that approximately 30% of the dams/reservoirs operators of the selected countries (SAM) could be approached for acquiring the I-CISK climate services. The total number of reservoirs (and therefore operang managers) in countries with both moderate SPI-6 and over 30% of drinking water originated from surface water is 2,450. Consequently, the SOM includes approximately 735 operang dam managers. As part of an effort for a more detailed segmentaon of the European market, addional indicators can be considered such as the “Annual Investment rate by water service providers (euro/inhabitant/year)” as reported by EurEau (2017). This index provides data on the financial capacity and investment readiness of water operators across different naons and can be used to further refine the market strategies within the SOM (Note 3 - Table 12). This analysis is summarized in Figure 39 and Table 12. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 69 Market Aributes Rang Low Medium High DWD – Percentage of Surface water resources usage for potable water (period 2011-2013) 0-30 30-50 >50 Annual investment rate by water service providers (euro/inhabitant/year) NA <50 >50 Risk of drought impacts based on the SPI-6 under 1.5°C global warming scenario - √ √ Figure 39: Canvas of opportunies for I-CISK climate services. EU Water Sector Market Aributes Cyprus Ireland UK Sweden Czech Republic Bulgaria Romania Spain The Netherlands Slovakia France Germany Italy Belgium Poland Finland Portugal Greece Number of Large Dams (ICOLD, 2021) 57 16 579 189 118 181 242 1.059 10 51 693 371 533 15 69 72 230 148 The significance of Potable Water Ulies Sector in the esmaon of the Market Segment Percentage of Surface water resources usage for potable water (DWD period 2011-2013) 58% 87% 68% 61% 47% 65% 64% 49% 39% 33% 29% 15% 39% 40% 24% 43% 38% 71% Annual investment rate by water service providers (euro/inhabitant/year) (EurEau, 2017) NA 130 150 70 25 NA 25 NA 100 40 100 90 25 80 50 70 70 40 Countries with moderate or high risk to drought impacts Risk of drought impacts based on the SPI-6 under 1.5°C global warming scenario √ - - - - √ √ √ - - √ - √ - - - √ √ Notes: Large Dam is defined a dam with a height of 15 meters or greater from lowest foundaon to crest or a dam between 5 meters and 15 meters impounding more than 3 million cubic meters D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 76 Soluon (User Requirements) ID User requirements As a <ROLE>, I would like to <GOAL> to <BENEFIT> GA1 As a Farmer I would like to have a streamflow predicon system (monthly, sub-seasonal, seasonal) .. so that I could opmize the use of allocated water for agriculture. GA2 NEA I would like to have a streamflow predicon system …to provide hydrological informaon to GA, RDA, and other stakeholders GA3 Georgian Amelioraon I would like to have a streamflow forecasng …to beer manage water resources for local farmers GA4 Rural Development Agency I would like to have a Climate predicon system …to inform local communies about future water availability challenges GA5 Hydropower Plants I would like to have forecasng for water levels …to opmize electricity generaon without harming irrigaon GA6 Policy Makers I would like to have a Water governance framework …to strengthen legal regulaons for sustainable water use Soluon (TO-BE Scenario): Α workflow of advanced predicve tools based on hydrological forecasts of monthly, sub-seasonal and seasonal scales. These hydrological forecasts in combinaon with stascs from historical hydrologic and meteorological data will promote efficient water allocaon before the high-demand period (summer) and mely drought response during the August and September management period, offering increased system performance in the long run. An Operaonal Early Warning System could interpret forecasts into readily comprehensible warnings that can also be coupled with proacve pracces to enhance the resilience and adapve capacity. The tools include: - Integraon of a Streamflow Predicon System: Use of hydrological and meteorological models to forecast water availability. - Farmer Decision Support Tools: Digital plaorms providing real-me irrigaon scheduling recommendaons. - Operaonal Early Warning System: Converts forecasts into aconable alerts for farmers, hydropower operators, and water managers. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 77 Value Proposion (Goal of the service): For the region, mely and detailed informaon on future surface water availability is crucial to water allocaon planning, drought response, and strategic planning. The workflow that has been developed will help local authories beer understand processes and be proacve by providing soluon-based decisions and proacvely plan the upcoming season by storing water in the reservoir or, if necessary, recommending steps for drought-resilient farming (e.g., the stakeholders can use the informaon to implement drought resilience plans, such as selecng drought-resistant crops or opmizing irrigaon schedules, ulmately reducing water demand and migang the impact of drought). 8.3 Second iteraƟon: Understanding the value chain To understand how the use of the climate service (CS) for water management in the Alazani-Iori basin helps actors along the value chain address their challenges at an operaonal level, a descripon of the value chain is built in a 4-er analysis based on the methodological framework described in MS26 (Guidelines for Value Chain assessment, June 2024). The goal is to develop an understanding of the economic, social, and environmental benefits and to complete the User Stories. The services are organized into two levels: (a) Level 1 (Data Provision Stage): Provision of raw climac and hydrological data (Tier 1). (b) Level 2 (Service Development and Delivery Stage): Development and implementaon of the streamflow predicon system and associated tools (Tiers 2–4). More specifically: - Tier 1: Supplier of Climac Data (Level 1 – Data Provision Stage): The supplier provides the raw climac and hydrological data necessary for the streamflow predicon system. This role is likely fulfilled by organizaons like the European Centre for Medium-Range Weather Forecasts (ECMWF) or the Na- onal Environmental Agency (NEA) in Georgia, which monitors hydrological data. These enes provide seasonal forecasng data (e.g., precipitaon, temperature) and historical hydrological data. Benefits:  ScienƟfic: Feedback from users in the service development and delivery stage (e.g., NEA, Georgian Amelioraon) helps improve data quality.  Economic: Potenal revenue from data provision services.  ReputaƟonal: Strengthens partnerships with local and regional stakeholders, enhancing their role in climate service provision. - Tier 2: Primary User/Intermediary (Level 2 – Service Development and Delivery Stage): The primary user transforms the raw data into a tailored climate service. In the Georgia LL, this role is played by a research or technical partner within the I-CISK project (e.g., a hydrological modelling group or a partner like SMHI). Other users (e.g. local stakeholders like NEA) help develop the streamflow predicon system, integrang hydrological and meteorological models, and provide aconable tools like farmer decision support plaorms and early warning systems. Benefits:  InnovaƟon Gains: Developing advanced predicve tools enhances their technical experse.  Economic Gains: Potenal to expand market share by offering similar services to other regions.  ReputaƟonal Gains: Builds credibility and fosters partnerships with local stakeholders like NEA and Georgian Amelioraon. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 78 - Tier 3: Secondary User (End User) (Level 2 – Service Development and Delivery Stage): The end-users directly benefit from the climate service. In the Alazani-Iori basin, these include:  NaƟonal Environmental Agency (NEA): Uses the streamflow predicon system to provide hydrological informaon to stakeholders, improving water resource management.  Georgian AmelioraƟon (GA): Manages irrigaon networks more efficiently, reducing water losses.  Rural Development Agency (RDA): Informs farmers about water availability, supporng agricultural resilience.  Hydropower Plants (HPPs): Opmizes water use for energy producon without compromising irrigaon needs.  Farmers and Vineyards: Use real-me irrigaon scheduling tools to improve producvity.  Local MunicipaliƟes: Enhance water infrastructure maintenance and development. Benefits:  Economic Gains: Reduced water losses (e.g., 15% reducon as noted in the 3rd iteraon) and increased agricultural producvity (e.g., 20% increase).  Environmental Gains: Beer water management supports sustainable use and reduces over-extracon.  ReputaƟonal Gains: Improved service delivery enhances trust among farmers and communies. - Tier 4: Wider Society and Environment (Level 2 – Service Development and Delivery Stage): The broader beneficiaries include the local communies, other economic sectors, and the environment in the Alazani-Iori basin. Benefits:  Economic Gains: Enhanced agricultural producvity boosts the local economy, especially in the Kakhe region, known for its vineyards.  Societal Gains: Improved water availability during dry periods ensures water security for communies.  Environmental Gains: Sustainable water management reduces the risk of over-extracon and supports ecosystem health in the basin.  ReputaƟonal Gains: A more resilient agricultural sector enhances the region’s reputaon as a reliable producer of high-quality goods (e.g., wine). The value chain analysis, including the services, beneficiaries, types of benefits, and value proposion for each er, is summarized in Figure 44. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 79 Figure 44: Understanding of the Value Chain for the Climate Services developed in Alazani river basin Living Lab (Georgia). D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 80 8.4 Third IteraƟon: Analyse the benefits Previous iteraons established the scope of analysis (1st iteraon) and delineated the value chain (2nd iteraon). This iteraon focuses on quanfying the idenfied benefits, where feasible, to assess the tangible impacts of the climate service. The analysis targets the benefits for Tier 3 (end users), as they directly integrate the climate service into operaonal workflows, allowing for more precise quanficaon. Benefits for other ers and sectors are evaluated qualitavely due to data and me constraints. The climate service developed for the Alazani-Iori Basin LL adopts a mul-sectoral approach, addressing challenges across water management, agriculture (farmers and vineyards), hydropower, and local governance. Given the diversity of sectors and the limited meframe of the I-CISK project, comprehensive monezaon across all sectors is not feasible. Consequently, quantave analysis focuses on water management and agricultural sectors (specifically Georgian Amelioraon and farmers, key Tier 3 beneficiaries), while hydropower and local municipalies are assessed qualitavely. The focus on Tier 3 is jusfied by their direct applicaon of the climate service, enabling measurable outcomes. Analysis of Tier 4 (wider society) is deferred, as broader societal benefits (e.g., economic growth, water security) are indirect and require addional data for accurate quanficaon. Water Management and Agricultural Sector – Quanfying the Gains There is a wide variety of methodologies to assess the value of climate services. In the current case, we apply a methodology based on the value of informaon (VoI) and decision theory, as described in relevant guidelines of MS26 (Guidelines for Value Chain assessment, June 2024). This methodology suits the part of the CS that refers to the water management and agricultural sectors. The skill of the service cannot be measured without actual data from the implementaon of the service itself, and this assessment of skill in this basin is further hampered by the lack of (recent) observaons of hydro-meteorological variables. Therefore, the evaluaon is based on the concept of value of perfect informaon (we assume that the service’s forecast is always correct – 100% skill). The value esmated by this approach is based on: (a) a theorecal performance of the service, which refers to a hypothecal or historical scenario, and (b) the esmaon of the value by specific end users. This means that the value esmated is somewhat relave, since if the hypothecal tesng scenario or the end users evaluang the service change, then the value may also change. The value is esmated by comparing the potenal gains that an end user may have for the evaluaon period by using the CS and taking informed decisions against the results of decisions based on current pracces. The CS is assumed to convey perfect knowledge of what has occurred, so the esmated value is considered the maximum value for that specific user that the service could have produced for that period. For the praccal applicaon of the methodology, the informaon required has been produced/collected by the service developers in collaboraon with the end users of the Georgia LL: - Idenficaon of specific decisions related to specific informaon needed. - Idenficaon of the potenal acons by the user. - Gains and/or losses are not directly expressed with a monetary indicator. For this applicaon, the case of water management and irrigaon in the Alazani-Iori basin is used, as described in the 1st iteraon. The CS supports operaonal decision-making through: (1) ancipang the risk of drought, (2) supporng decisions on the annual distribuon of water among uses through forecasts of available water for the wet period of the coming hydrological year, for two decision periods (April and September) to increase agricultural producvity and support all uses, (3) allowing managers to manage water excess inflows from extreme precipitaon events to migate flood risks. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 81 Seng the States of the World As an indicator of the basin’s “states of the world,” the amount of water available for irrigaon (streamflow) is selected. Four states of the world are idenfied in cooperaon with the Georgia LL stakeholders represenng the water management and agricultural sectors (Georgian Amelioraon and farmers): - Flood Risk: Streamflow exceeds the capacity of irrigaon canals, leading to potenal flooding. This state includes volumes that could cause overflow, exposing agricultural areas to damage. - Normal State: Streamflow allows irrigaon to operate normally without restricons. Higher streamflow within this state means more water for agriculture and hydropower. - Water Shortage: Streamflow is low, liming irrigaon and affecng agricultural producvity. This is an alert state for drought preparaon. - CriƟcal Drought: Streamflow is below the minimum required for irrigaon, leading to severe agricultural losses. Forecasted States of the World The basic state assumes that water managers (Georgian Amelioraon) and farmers ulize the available streamflow to support irrigaon as planned. This state is produced for three hypothecal scenarios: - Scenario 1: An average hydrological year based on historical data from the past decade, assuming full ulizaon of streamflow for irrigaon. - Scenario 2: A dry year based on historical data, with irrigaon withdrawals reduced to 50% of the planned amount due to water scarcity. - Scenario 3: An extreme flood year, with high streamflow leading to potenal flooding, based on historical flood events in the basin. The Payoff Matrix A payoff scale (0–10, for more informaon on the payoff scale, see Annex B - Quanfy the benefits of the CS for the Water Sector - Crete Island LL) evaluates outcomes for Georgian Amelioraon and farmers, considering irrigaon availability, agricultural producvity, and losses from flooding/drought. The payoff matrix is presented in Table 13. Table 13: Payoff Matrices According to the End Users (Georgia LL). State of the World Payoff (Georgian Amelioraon) Payoff (Farmers) Flood Risk 4 (due to flood management costs) 3 (due to crop damage risk) Normal State 10 (opmal water distribuon) 10 (maximum producvity) Water Shortage 5 (limited water distribuon) 4 (reduced yields) Crical Drought 0 (no water for irrigaon) 0 (severe crop losses) Payoffs are linear within each state, decreasing as streamflow approaches thresholds (e.g., from 10 to 5 in the Normal State nearing Water Shortage). An addional payoff for water abstracon (beyond planned amounts) ranges from -10 to 10, based on the rao of extra abstracon to maximum planned abstracon. Total payoff combines state and abstracon gains equally. Payoff Results: - Scenario 1 (Average Year): Climate service increases payoff for Georgian Amelioraon from 78.0 to 82.5 (6% increase) and for farmers from 75.0 to 80.0 (7% increase). Abstracon gains add 20.0, yielding total payoffs of 102.5 (31% increase) and 100.0 (33% increase), respecvely. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 82 - Scenario 2 (Dry Year): Payoff improves significantly—Georgian Amelioraon from 50.0 to 70.0 (40% increase), farmers from 45.0 to 65.0 (44% increase). Abstracon gains of 15.0 result in total payoffs of 85.0 (70% increase) and 80.0 (78% increase). - Scenario 3 (Flood Year): Payoff rises modestly—Georgian Amelioraon from 55.0 to 60.0 (9% increase), farmers from 50.0 to 58.0 (16% increase). Abstracon gains of 10.0 yield total payoffs of 70.0 (27% increase) and 68.0 (36% increase). Table 14: Payoff Gains Under the Three Scenarios Examined (Georgia LL). Scenario State of the World Gains Payoff (Georgian Ameliorao n) State of the World Gains Payoff (Farmers) Water Abstracon Gains Payoff Total Payoff Gains (Georgian Ameliorao n) Total Payoff Gains (Farmers) Total Payoff Gains % (Georgian Ameliorao n) Total Payoff Gains % (Farmers) Scenario 1 (Average) 4.5 5.0 20.0 24.5 25.0 31% 33% Scenario 2 (Dry) 20.0 20.0 15.0 35.0 35.0 70% 78% Scenario 3 (Flood) 5.0 8.0 10.0 15.0 18.0 27% 36% Hydropower Sector – Qualitave Assessment of the Gains The evaluaon of the service for the hydropower sector (a Tier 3 beneficiary) is based on idenfying appropriate indicators that represent potenal benefits for the end user, demonstrang the value of the CS. During the co-creaon process, specific needs were idenfied, which translated into tailored climac indicators to support decision-making. Hydropower plants in the Alazani-Iori basin idenfy streamflow forecasts as crical for opmizing electricity generaon without harming irrigaon needs. The logical steps leading to the co-idenficaon of the value of the specific CS are as follows: - Streamflow forecasts allow hydropower plants to predict water availability for energy producon, especially during the high-demand summer period. - Low streamflow can lead to reduced energy producon, increasing reliance on more expensive energy sources (e.g., fossil fuels). - High streamflow can lead to overflow, requiring the release of water without energy generaon, resulng in lost revenue. - The annual costs of subopmal water management (e.g., reduced producon, increased fuel costs) are esmated by hydropower operators as medium to high, relave to their total operaonal costs. - On an operaonal basis, if seasonal forecasng provides accurate informaon on expected streamflow, hydropower plants can adjust their operaons (e.g., store water during low-demand periods, release water strategically during high-demand periods). - This could lead to: (a) Increased energy producon efficiency, reducing reliance on alternave energy sources (economic gain). D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 83 (b) Reduced environmental impact by minimizing unnecessary water releases (environmental gain). Based on the above steps and the scaling of benefits given in Table 1, the service demonstrates two specific benefits. Based on the reasoning of “avoided costs” idenfied by the end user as medium to high, the benefit of the service is idenfied as MODERATE to HIGH . Local Municipalies – Qualitave Assessment of the Gains The evaluaon of the service for local municipalies (another Tier 3 beneficiary) is based on idenfying appropriate indicators that represent potenal benefits for the end user. During the co-creaon process, specific needs were idenfied, which translated into tailored climac indicators to support decision-making. Local municipalies in the Alazani-Iori basin idenfy the early warning system as crical for flood preparedness and infrastructure maintenance. The logical steps leading to the co-idenficaon of the value of the specific CS are as follows: - Extreme flood events can damage water infrastructure (e.g., canals, reservoirs), leading to high repair costs and disrupons in water supply. - The frequency of flash floods is increasing due to climate change, as noted in the 1st iteraon. - The annual costs of flood damage and infrastructure repairs are esmated by municipalies as medium, relave to their total budget. - If the CS provides mely informaon for ancipated surface flows of significant height, municipalies can take proacve measures (e.g., reinforce canals, evacuate at-risk areas). - This could lead to: (a) Reduced repair costs for water infrastructure (economic gain). (b) Increased public trust in municipal services due to effecve flood management (reputaonal gain). Based on the above steps and the scaling of benefits given in Table 1, the service demonstrates two specific benefits. Based on the reasoning of “avoided costs” idenfied by the end user as medium, the benefit of the service is idenfied as MODERATE . 8.5 Fourth IteraƟon: Analysis beyond the defined boundaries Market Analysis: The Alazani-Iori basin is part of a larger region facing similar water management challenges. The streamflow predicon system has the potenal to be scaled to other river basins in Georgia and neighbouring countries. Commercial Exploitaon: While the system is not yet commercially viable, the roadmap for development includes several recommendaons to enhance its effecveness and scalability. These include improving model accuracy, installing addional stream gauges and meteorological staons in strategic locaons to improve data collecon, and integrang real-me data sources. Addionally, rehabilitang irrigaon infrastructure, such as through canal dredging and modernizaon, could further support the effecve implementaon of the climate service by reducing water losses and improving distribuon efficiency. Once fully operaonal, the system could be marketed to other regions facing similar challenges. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 84 The Alazani-Iori Living Lab has made significant progress in developing a streamflow predicon system, but further development is needed to improve accuracy and reliability. The potenal benefits of the system are clear, and with connued investment in data collecon and model refinement, the system could become a valuable tool for water management in Georgia and beyond. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 85 9 Business model storyline for the Lesotho Living Lab 9.1 Background and context Lesotho is a landlocked country in Southern Africa, characterized by a high-altude landscape with elevaons ranging from 1,500m to 3,482m. The country's climate is influenced by its topography, with disnct agroecological zones: The Lowlands, Senqu River Valley, Foothills, and Mountain regions. Lesotho experiences extreme weather condions, including droughts, cold waves, and snowfall, which significantly impact livelihoods, parcularly for vulnerable communies reliant on agriculture and livestock. Figure 45: Agro-ecological zones of Lesotho. Source: Lesotho Ministry of Public Works and Transport. Several organizaons play a crucial role in climate services and disaster preparedness in Lesotho, including:  Lesotho Red Cross Society (LRCS): Leads humanitarian response efforts, implemenng ancipatory acons based on climate forecasts.  Lesotho Meteorological Services (LMS): Provides weather and climate forecasts to inform disaster preparedness.  Disaster Management Authority (DMA) and other governmental stakeholders: Contribute to emergency response and risk reducon. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 92 9.4 Third iteraƟon: Analyse the benefits Through the 2nd iteraon (see previous paragraph) the value of the CSs was idenfied in various Tiers of the chain of the service. At the 3rd iteraon the analysis proceeds one step further, to idenfy and quanfy the benefits of the service. The analysis may be performed for each one of the 4 Tiers recognized in the previous. However, at this stage, the benefits of those services cannot be properly assessed, even in a qualitave aspect, as sufficient empirical data is not yet available. However, one tangible impact already observed is that some of the suggested improvements to the Early Acon Protocol (EAP) for cold waves have been incorporated into its latest version, demonstrang an immediate influence on ancipatory acon planning. To systemacally evaluate the benefits of this approach, a well-structured measurement framework should be implemented. This can be broken down into the following steps: 1. Define relevant indicators for each er, as detailed below. 2. Develop data collecon mechanisms: Implement post-event assessments, user feedback surveys, plaorm analycs, and acvaon reviews to gather qualitave and quantave data. 3. Establish baseline measurements: Idenfy inial benchmarks for each indicator to track progress and improvements over me. 4. Monitor and analyse outcomes: Regularly assess the collected data against the predefined indicators to determine trends and effecveness. 5. Classify benefits using a qualitave scale: Apply a structured assessment approach, to categorize observed impacts. 6. Refine and adapt intervenons: Use the insights gained to adjust business model strategies, improve forecast tools, enhance training programs, and opmize early acon protocols. Key indicators should be established at different ers:  Tier 1: The focus should be on assessing the accuracy and reliability of forecasts. This includes evaluang forecast skill metrics and comparing past predicons with actual events to determine their precision.  Tier 2: It is essenal to evaluate whether the EAPs are effecvely implemented in pracce. The Internaonal Federaon of Red Cross and Red Crescent Sociees (IFRC) already have processes in place to assess protocol acvaons and revisions. Addionally, for the IBF portal, performance indicators should include system stability (e.g., upme and plaorm responsiveness), funconality, and the capacity of Disaster Risk Reducon officers at LRCS to use the plaorm efficiently following adequate training.  Tier 3: The assessment should focus on the meliness of early warnings in supporng decision-making and the effecveness of cash distribuon in response efforts. This could involve analysing response melines, beneficiary reach, and overall impact in migang humanitarian consequences. Beyond these evaluaons, it is crucial to acknowledge the dependencies that influence the realizaon of these benefits. Key factors include the effecve adopon of the IBF portal for droughts by LRCS to inform their acons, the successful validaon and approval of the updated EAP for cold waves by the IFRC validaon commiee, and the connued availability of funding to support early acons. Other crucial factors include the presence of sufficient staff within naonal stakeholders to enable coordinaon and response efforts and the sustained trust and acceptance of LRCS by local communies. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 93 9.5 Fourth iteraƟon: analysis beyond the defined boundaries The primary objecve of climate services in the Lesotho Living Lab is not to develop a marketable product but to strengthen resilience and improve decision-making through ancipatory acons. This includes enhancing early warning systems for droughts and cold waves, which are crucial for protecng vulnerable communies and advancing disaster risk reducon efforts in Lesotho. Given this focus, a full market analysis is not relevant, as commercialisaon is not the primary aim. Instead, efforts should be directed toward refining the value proposion, aligning the service with naonal strategies and stakeholder needs, and ensuring long-term sustainability through partnerships and instuonal integraon. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 94 10 Concluding remarks In the current analysis, business model storylines were draed for the I-CISK Climate Services (CS), which were co-developed in seven LLs in Europe and Africa. The analysis focused on the Value Model framework (opportunity, problem to be solved, value proposions). Beyond the economic value, social and environmental gains and/or losses, were also considered in the overall value extracon model. The CSs that were assessed target the sectors of (a) tourism, (b) agriculture, (c) water management (d) urban planning, (e) humanitarian, and (f) general public. Due to the broad nature of the economic sectors targeted and the number of sector components and potenal beneficiaries, mulple market segments are recognized. It is noted that a ered approach of four steps has been applied, where every step develops the user story (business story) of a CS, gradually building up in detail and extent of analysis. This allowed to consider the fact that there are CSs developed with strong social/environmental or gains other than economic (e.g. reputaonal), and dra business model storylines independent of factors that may confine the extent of the analysis, such as the type of value and the beneficiaries that are associated with the CS. Business storylines have been produced for each one of the services, though not all the services developed can or need to reach the final er of the analysis. The findings of this ered analysis to develop the business model storylines are summarised in Table 15. Table 15: Characteriscs of the business model storylines developed for the I-CISK CSs within each LL. LL Sectors/segments addressed business model storylines adopting a user-focused approach Added value evalua- on 4rth step – beyond the defined boundaries Netherlands (3) water management, recrea- on, agriculture 3 ers of analysis qualitave quanfica- on for the 3 sectors components No - LL is idenfied as the primary market segment Spain (3) water management, agriculture, forest 3 ers of analysis qualitave quanfica- on for the 1 sector component No - LL as a primary market segment / The key actor for sustainability is the public purveyor of CS from the regional government. No commercial use would be envisioned Italy (2) Water management (alloca- on and agriculture) 3 ers of analysis Moneze 1 CS and qualitave evaluaon for another aspect Yes - Full Market Analysis Hungary (3) Tourism, Residents and Instu- ons, City Management (urban planning) 3 ers of analysis Moneze for 1 sector component No - LL is idenfied as the primary market segment Greece (4) Tourism, Water management, Transportaon, Energy 3 ers of analysis Quantave for 2 sectors and qualitave for 2 sectors Yes - Full Market Analysis (focus on two sectors: tourism and water) Georgia Water sector with various end-users 3 ers of analysis Quanfied gains for 2 end user types and qualitave assessment for 2 end user types No - LL is idenfied as the primary market segment for now, CS is not yet commercially viable D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 95 LL Sectors/segments addressed business model storylines adopting a user-focused approach Added value evalua- on 4rth step – beyond the defined boundaries Lesotho (2) agriculture and general public 2 ers of analysis + a preparaon for the 3rd er preparaon for the 3rd er No - The primary objecve of CS in the Lesotho LL is not to develop a marketable product but to strengthen resilience and improve decision-making through ancipatory acons Draing the storylines across the I-CISK Living Labs, several governance-related barriers emerge as challenges to the uptake and sustainability of climate services. Established procedures and bureaucrac rounes may limit the capacity of public instuons to adopt innovave tools. This inera is oen reinforced by a lack of regulatory incenves or mandates that would encourage integraon of new decision-support systems. Closely related to this, in regions where water/environmental management or climate adaptaon responsibilies are dispersed across mulple agencies and administrave layers, coordinaon becomes complex and slow. This fragmentaon can stall decision-making processes and make the deployment of integrated services, like those developed within the I-CISK Living Labs, more difficult. Funding gaps also play a crical role. Even when interest in the services is high, instuons may face budgetary constraints, long and rigid procurement cycles, and uncertainty in accessing or sustaining necessary financial resources. These limitaons would parcularly affect resource-constrained administraons and reduce their ability to commit to long-term service adopon or infrastructure investments. One effecve approach to address the above challenges and barriers could be embedding the climate services into exisng governance and regulatory frameworks, such as regional adaptaon and resilience plans or naonal monitoring protocols. This alignment not only increases instuonal legimacy but also eases bureaucrac adopon. Addionally, leveraging exisng public funding programs (e.g. those available through the EU’s funding mechanisms or regional development funds) could prove to be a pragmac way to cover operaonal costs without requiring new financial mechanisms. Further, the co-development process within Mul-Actor Plaorms (MAPs) helps reduce resistance by fostering shared ownership and ensuring that the services are tailored to real administrave needs. This parcipatory model builds trust and makes instuons more inclined to incorporate the services into their operaons. These business model storylines provide essenal groundwork for the upcoming exploitaon strategy to be developed under WP6. The insights gained here regarding instuonal contexts, market potenal, and value generaon will directly inform the broader disseminaon and exploitaon acons. In conclusion, the business model storylines developed within I-CISK reflect the diversity of Climate Services co-designed across the Living Labs, ranging from market-ready soluons to those embedded within public governance frameworks. Despite differing commercial potenals, these CSs share key compeve advantages: their alignment with instuonal mandates, the modularity and adaptability of their offerings, and their capacity to support long-term economic and operaonal sustainability. These aributes posion the I-CISK Climate Services well within evolving EU policy landscapes and its tangible funding mechanisms such as the CAP, LIFE, and PSR. As these services mature, their integraon into both market-driven and instuonal ecosystems shall foster climate resilience and reinforce the project’s impact across diverse socio-economic and environmental contexts. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 96 11 References Aaker, David A., and Damien McLoughlin. 2010. Strategic Market Management: Global Perspecves. John Wiley & Sons. Bagli S., P. Mazzoli, V. Luzzi, et al. (2024). Climate Data and Front and Back-End Components of the I-CISK Climate Service Plaorm, , I-CISK Deliverable 5.2, Available online at www.icisk.eu/resources Borzyszkowski, Jacek. (2015). The significance of promoon in Desnaon Management Organizaons' acvies. e-Review of Tourism Research. 1166. Bosello F., E. Delpoazzo and contribung Authors (2021). In-dept assessment of the economic value of CLARA services for the endusers, CLARA Deliverable 4.2, the CLARA project, Grant Agreement no. 730482 Day, George. (2007). Is it real? Can we win? Is it worth doing? Managing risk and reward in an innovaon porolio. Harvard business review. 85. 110-20, 146. hps://www.researchgate.net/publicaon/5568092_Is_it_real_Can_we_win_Is_it_worth_doing_Managing_ risk_and_reward_in_an_innovaon_porolio De Stefano, L., Ropero Szymañska, N., Hernández-Mora, N., et al., 2023: User-centred validaon of the integraon of climate acon informaon, I-CISK Deliverable 2.6, Available online at www.icisk.eu/resources Rossi, L., Wens, M., De Moel, H., Co, D., Sabino Siemons, A., Tore, A., Maetens, W., Masante, D., Van Loon, A., Hagenlocher, M., Rudari, R., Naumann, G., Meroni, M., Avanzi, F., Isabellon, M. and Barbosa, P., European Drought Risk Atlas, Publicaons Office of the European Union, Luxembourg, 2023, doi:10.2760/608737, JRC135215. hps://publicaons.jrc.ec.europa.eu/repository/handle/JRC135215 D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 97 Annex A – Assessments on Value esƟmaƟon from the Budapest LL Approach to Quanfying Benefits This secon highlights praccal methods to moneze these benefits, ranging from direct cost–benefit esmaons to survey-based valuaons such as WTP (Willingness to Pay) analysis. - Economic Benefits and Avoided Costs: The primary focus is on direct or indirect financial gains—such as reduced operaonal costs or increased revenue—that can be traced back to the heat and microclimate mapping service. Where feasible, monetary values are assigned to benefits like energy savings, improved tourism revenues, or decreased health expenditures. However, due to the lack of direct figures from stakeholders, assumpons are necessary. - Another methodology for this kind of monezaon is a Willingness to Pay (WTP) analysis. In essence, WTP studies aempt to measure the maximum amount that different stakeholders—local residents, municipal authories, or even business communies—are prepared to pay for a parcular service via a survey or interview-based approach. This direct reflecon of users’ preferences helps quanfy “nonmarket” advantages, such as enhanced comfort, fewer health complaints, or overall support for climate adaptaon. - In addion, the Benefit Transfer Method can be applied as a complementary or alternave approach when primary data is scarce. This method involves transferring economic values esmated in previous studies of similar services to the current context, aer making necessary adjustments for demographic, economic, and environmental differences. Willingness to Pay (WTP) approach Within the Budapest Living Lab context, a WTP survey could in principle idenfy how much local residents, tourists, or municipal enes deem affordable and jusfied for accessing microclimate-monitoring and forecasng tools. Willingness to pay (WTP) analysis faces several challenges in the context of the Budapest LL climate service. Urban climate adaptaon measures typically work together, making it difficult to determine the exact contribuon of a single climate service. Addionally, percepon gaps and limited awareness of heat monitoring may lead to misaligned WTP esmates. Self-reported data can further distort results, complicang the aribuon of value to the Budapest LL climate service within a broader package of climate iniaves. To conduct a WTP analysis for the Budapest LL climate service, we would begin by designing a Conngent Valuaon Survey (CVM) that use double-bounded WTP quesons, along with socio-demographic and atudinal items to capture respondents’ profiles and environmental awareness. A representave sample of residents would be targeted to achieve 400–600 valid responses, preceded by a pilot study of 50–100 respondents to refine bid levels and survey logic. Finally, the data would be analyzed using a double-bounded logit/probit model that incorporates covariates (including local microclimate data when available) to derive mean or median WTP esmates, which would then be aggregated. In the ICISK project, the core focus was on developing and tesng the climate service rather than formally assessing its economic or financial benefits (including indirect effects). Hence, no comprehensive WTP surveys or monezaon exercises were conducted under the project, largely due to me and resource constraints—a common scenario in research and development iniaves where technological or methodological innovaon is the primary goal rather than market-based valuaon. Direct cost approach In the Budapest Living Lab (LL), we applied a direct cost (avoided cost) approach to esmate the potenal economic benefits of urban heat migaon strategies. The analysis is based on three main intervenon scenarios designed to reduce surface temperatures and improve urban liveability: 1. White roofs (high-albedo roofs): Applicaon of reflecve paint or materials on rooops, facades, and paved surfaces to lower surface temperatures at relavely low cost. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 98 2. Light streets and green infrastructure (high albedo at street level): Includes green roofs, planng of trees, and the whitening of pavements to create more liveable and resilient microclimates. 3. Targeted implementaon based on microclimate data: The locaon and scale of intervenons are determined using high-resoluon spaal data—such as satellite or drone-based thermal maps and insitu monitoring networks—allowing resources to be focused on areas with the highest heat stress. This data-driven approach also supports the selecon of opmal measures, whether reflecve coangs or greening, based on where the greatest temperature reducons and cost savings can be achieved. For scenario dimensioning, we calculated the total surface areas eligible for intervenon using 24 disnct surface types: 12 derived from street-level data and 12 from rooop orthoimagery. For each category, we determined its spaal coverage within the district and associated average surface temperature. These values are extracted from the ortho and thermal photo GIS layers of our climate service (see Error! Reference source not found. and Error! Reference source not found.). D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 99 Figure 48: Ortho and thermal photo GIS layers of Budapest LL climate service: 1st column pavements and roads in VII district; 2nd column pavements and roads in VI district. Figure 49: Coverage percentages and Temperature distribuon, as esmated through the Budapest LL climate service: 1st column pavements and roads in VII district; 2nd column pavements and roads in VI district. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 100 These are the potenal temperature reducons achievable through reflecve surface coangs at street level— expressed in terms of their impact on the average surface temperature of the enre district:  Maximum temperature reducon for Budapest District 6 (streets): 2.39°C  Maximum temperature reducon for Budapest District 7 (streets): 1.52°C These are the potenal temperature reducons achievable through roof coangs—expressed in terms of their impact on the average surface temperature of the enre district (of course, for individual buildings the improvement can be significantly higher, around 3–5°C, which may result in a noceable effect on thermal comfort):  Maximum temperature reducon for Budapest District 6 (roofs): 1.71°C  Maximum temperature reducon for Budapest District 7 (roofs): 0.94°C Net Present Value (NPV) calculaon for district 7 CBA Parameters for district 7, Budapest  Total Area: 1,634,784 m² (building and street area together)  Unit Cost: €10/m²  Inial Implementaon Cost (Year 0):  Coang Lifespan: 10 years  Reapplicaon: 50% of the inial cost at Year 10 and Year 20  Annual Benefit (Years 1–30): €2,000,000 per year (energy savings, extended infrastructure life, health benefits, etc.) + unknow € (mortality)  Discount Rate (r): 4%  Evaluaon Horizon: 30 years Reducon in heat stress-related mortality and morbidity: Studies have shown that the impact of heat on mortality and hospital admissions can be significant, especially during heatwaves. High temperatures can directly lead to health problems such as heat exhauson and dehydraon, increasing mortality rates, especially among vulnerable populaons, but studies have also shown the significant impact of heat stress in sports and exercise. A 5°C increase in average daily temperature above 25°C increased all-cause mortality by 10%. in Budapest. Based on this, a 3-level HHAS was developed in 2005. The characteriscs of excess mortality during heat alerts and its associaon with the severity of influenza epidemics are presented. The excess mortality was 27%, 36%, and 23% during the first summer heatwave in 2012, 2013, and 2014, years characterized by mild influenza epidemics. In years when excess mortality during influenza epidemics was high, mortality during August heat waves was relavely high (15-20%) (Anna Paldy et al. ) Improving heat data knowledge can reduce the risk of heat-related illnesses:  With accurate heat maps, the city knows where the need for intervenon is most acute, so it can target more resources there (e.g. more efficient cooling soluons, pavement replacement, greening).  areas which are not recommended for the installaon of outdoor air condioning units, as this could lead to addional heat emissions, can be adenfied. Co-benefits of green infrastructure:  A nicer, more liveable environment, improved air quality, increased biodiversity, increased property D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 101 values, increased public sasfacon. Cash Flows by Year for disnct 7, Budapest  Year 0: –€16,347,840 (inial cost)  Years 1–9: +€2,000,000/year +  Year 10: +€2,000,000 – €8,173,920 = –€6,173,920  Years 11–19: +€2,000,000/year  Year 20: +€2,000,000 – €8,173,920 = –€6,173,920  Years 21–30: +€2,000,000/year Cost–Benefit Analysis (CBA): In this step, each intervenon scenario (e.g., White City, Green City, or a combined approach) is evaluated by comparing total discounted benefits and costs over a chosen me horizon (commonly 30years). The Net Present Value (NPV) is calculated as: [𝑁𝑃𝑉  ∑ 󰇛 𝐵_𝑡 - 𝐶_𝑡 󰇜 / 󰇛1  𝑟󰇜^𝑡 𝐵𝐶𝑅  ∑ 󰇛 𝐵_𝑡 / 󰇛1  𝑟󰇜^𝑡 󰇜 / ∑ 󰇛 𝐶_𝑡 / 󰇛1  𝑟󰇜^𝑡 󰇜 where ( B_t ) denotes benefits and ( C_t ) denotes costs at me ( t ), and ( r ) is the social discount rate (e.g., 4%). By comparing these metrics across scenarios, analysts can determine whether ancipated gains (such as fewer heat Discounted Cash Flow (DCF) and NPV Each year’s net cash flow is discounted back to present value using: The Net Present Value (NPV) is the sum of all discounted cash flows from Year 0 to Year 30: Result: 1. Posive NPV: This indicates that, with the assumed values, the project’s present value of benefits outweighs the present value of costs by roughly €9 million. 2. Sensivity: The final NPV can vary significantly depending on several factors. For example:  If the annual benefit is higher than €2 million—parcularly when accounng for the reducon in heat-related mortality, which was not included in this calculaon—the NPV would increase substanally.  Changes in coang or reapplicaon costs, or deviaons from the assumed 4% discount rate, can also significantly affect the outcome. A posive NPV of about €9 million means the intervenon (coang 1,634,784 m²) is financially aracve under the given assumpons. Summary The Budapest Living Lab’s climate service offers a forward-looking soluon to urban heat-related challenges through a highly localized, data-driven, and user-focused approach. By integrang drone-based thermal imagery, manual temperature measurements, cizen science contribuons, and satellite downscaling, the service delivers accurate, high-resoluon microclimate data and forecasts. These outputs serve mulple D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 108 Thus, in the case of Scenario 2, the total, annual payoff for the CS based state of the world is esmated to be 154.4 against an 73.6 for the b.a.u. case, that is an 80.8 gain and an 110% increase. Figure 53: Scenario 2: (a) States of the world and (b) monthly payoff. (decision periods and forecasng period are marked on the graph). For Scenario 3, the variaon of the state of the world (water volume) is shown in Figure 54a. With the CS decision-based meline, the new state of the world lies more at the lower part of the Normal state in comparison to the b.a.u. case, where the water stored volume fluctuates also in the Flood Contrlol state. That translates to a decrease in payoff, as is clearly shown in Figure 54b. The total payoff values (2-year) are 156.4 for the b.a.u. against a 146.9 for the CS based, i.e. a -6% change (a 9.5 units decrease in payoff). However, the forecast provided the opportunity for a small increase of water abstracons during the main part of tourisc period of the year (from May to September). An in that way, the water abstracon gains increased along with the opportunity for an increase in revenue. The annual water abstracon gains payoff sums up to 15.5. It is noted however that the unfavorable two-years of low inflows (dry years) led also to the need for reducing the abstracons, hence the negave abstracon gains payoff during the second year. Thus, in the case of Scenario 3, the total, 2-year payoff for the CS based state of the world is esmated to be 162.4 against a 156.4 for the b.a.u. case, that is a slim 6 units gain and a 4% increase. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 109 Figure 54: Scenario 3: (a) States of the world and (b) monthly payoff. (decision periods and forecasng period are marked on the graph). The total gains are summarized in Table 17. Scenario 1 is close to a full ulizaon of the reservoir reserves and therefore there is limited room for changes in water abstracon during the tourisc period, when they are needed most. However, the CS demonstrated potenal gains (under the assumpon for a 100% skill of the CS). Scenario 2 provides beer opportunies for maximizing the gain from the CS forecasts because the reservoir is not ulized in its full potenal by the agricultural sector (irrigaon). For Scenario 3, the unfavourable two-years of low inflows (dry years) led also to the need for reducing the abstracons, hence to negave abstracon gains payoff during the second year. However, even under these condions there is sll some room for gains, although based on a 100% skill of the CS. It is noted that the above calculaons are based on 3 scenarios of the climac condions and ulizaon of the reservoir. These scenarios cover some favourable, average and unfavourable condions but it is recognized that other condions may lead to different results. Table 17: Payoff gains under the three scenarios examined. Scenario State of the world gains Payoff water abstracon gains payoff Total payoff gains gains % 1 -5.3 25.7 20.4 26% 2 21.3 59.5 80.8 110% 3 (dry years) -9.5 15.5 6 4% D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 110 Annex C – QuanƟfy the benefits of the CS for the Tourism Sector - Crete Island LL The socio-environmental model presented in (Biella et al. 2024) was adopted as a comprehensive evaluaon framework designed to assess the value of Climate Services (CS) products across five interconnected sectors: tourism, water, transport, energy, and agriculture. This model effecvely demonstrates how the implementaon of CS products can improve informed and sector-specific decision-making processes in these domains. In the tourism sector, for example, it illustrates how CS products facilitate the formulaon of targeted strategies aimed at enhancing tourist inflow. In the energy sector, the model emphasizes the contribuon of CS products to increasing energy availability, thereby enabling beer adaptaon to variable energy demands. In the transport sector, the focus is on enhancing road usability through mely maintenance and the development of new infrastructure. Concerning water resources, the model advocates for the augmentaon of water storage capabilies and the opmizaon of resource reallocaon strategies. In agriculture, it demonstrates how CS products can enhance water allocaon and promong harvesng pracces to support the increasing food requirements, hence moderang food costs. Collecvely, the model elucidates the dynamic roles of CS products in promong advancements across these varying sectors. Moreover, the model incorporates future climate projecons to address fluctuaons in water availability, while human populaon growth is depicted as a gradual and consistent trend (Biella et al. 2024). A pivotal component of this model is the categorizaon of sectors into primary, secondary, and non-targeted levels within the ICISK framework of the co-design, co-development, and co-producon of CS products. In this schema, the tourism sector was idenfied as the primary focus, while water, energy, and transport sectors were classified as secondary. The agricultural sector was designated as the ‘non-targeted’ sector, enabling an assessment of the mulsectoral interconnectedness inherent within socio-environmental dynamics. The simulaon generated by the model produces sector-specific indices that gauge the effect of CS products across the selected sectors. Within the tourism sector, the Accommodaon Cost Index (ACI) is employed as a proxy for the tourism sector. The Energy Scarcity Index (ESI) is ulized to measure the availability of energy resources. In the transport sector, the Road Inaccessibility Index (RII) is adopted to highlight challenges related to road access. For water resources, the Water Scarcity Index (WSI) quanfies the availability of this crical resource. In terms of agriculture, the model includes a Food Cost Index (FCI) that reflects the availability of food commodies. The change of those sector-specific indices will be used as an indicator for quanfying the benefit of the service. Details on the model used, the underlying assumpons and the descripon of the outputs are given in Biella et al. (2024). It is noted here that a basic assumpon made is that the sectors are operang under exisng climate informaon (e.g. from naonal meteorological agencies, through sectoral climate change experiences, sectoral measures to respond to climate change etc). Climate Services (CS) products are therefore regarded as supplementary, tailored climate informaon that builds upon the convenonal climate informaon currently available. As such, the climate informaon accessible to all sectors is uniformly characterized. This pre-exisng climate informaon is assigned a value of 0.3. In contrast, the introducon of CS products results in an enhancement of the climate informaon value from the baseline of 0.3 to 0.7, reflecng an addional value of 0.4 aributed to the tailored nature of the CS products. The provision of these tailored CS products empowers targeted sectors with the precise informaon necessary for making informed decisions and formulang strategies that address their unique challenges and needs. As a result, the availability of CS products is simulated to significantly increase the capacity of these sectors to respond effecvely to the pressures from climate change and populaon growth. D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 111 To quanfy the value of co-produced CS products in the context of the island of Crete (LL), two scenarios were considered:  Scenario 1: This simulaon is based on a convenonal sectoral approach to climate service development, wherein CS products are specifically designed for a single sector, with all other sectors treated as non-targeted (Reed et al. 2019).  Scenario 2: This simulaon operates under the premise of co-producon of CS products as executed on the island of Crete. The stakeholders’ engagement in Crete followed a mul-stakeholder, mul- hazard approach, allowing for the categorizaon of sectors into primary and secondary classificaons (Masih et al. 2022). The differences in sectoral indices explained above (i.e. ACI, ESI, RII, WSI, and FCI), between the two scenarios were systemacally analysed to evaluate the addional value of the CS products within the socioenvironmental system encompassing the five sectors. More details about the model are available in (Biella et al. 2024). Results A comparave analysis of the two scenarios reveals that the co-producon of CS products within a mul- stakeholder framework enhances the adapve capacies of both primary and secondary sectors, with improvements ranging from 24% to 472% (Figure 55A). It is noted that, as ancipated, no measurable impact is observed on the adapve capacity of the non-targeted sector. The influence of CS product co-producon on sectoral efficiencies exhibits substanal variability, parcularly within the secondary sectors, as depicted in Figure 55B. This variability highlights the crical role of mul- sectoral approach in CS products development, as implemented on the island of Crete. Addionally, Figure 55 underscores the limitaons of convenonal sectoral approaches (Scenario 1), as certain sectors already possess substanal adapve capacies and efficiencies. The adopon of a mul-sectoral approach in the development of CS products represents a transformave shi for all targeted sectors. Figure 55: Adapve capacies of the selected sectors (A) and sectoral efficiencies for the selected sectors (B). These capacies are influenced by the availability and relevance of climate services (CS), the meliness of access to CS products, the proximity to CS providers, the type of each sector, and the resources inherent to those sectors. The sectoral efficiencies are determined by the relaonship between the adapve capacies to meet resource demands within each sector against the maximum resource demand (Biella et al. 2024). 24% 472% 161% 242% 0% 0% 250% 500% 0.0 1.0 2.0 3.0 4.0 5.0 6.0 % Change Adaptive capacity value Change Scenario 1 Scenario 2 (A) 23% 298% 60% 114% -36% -200% 0% 200% 400% 0 0.1 0.2 0.3 0.4 0.5 0.6 % Change Sectoral efficency value Change Scenario 1 Scenario 2 (B) D5.5 - Business model storylines for sustainable CS exploitaon in the Living Labs 112 1. The results of model simulaons regarding sectoral scarcity indices demonstrate a posive effect of climate-sensive (CS) products in Scenario 2 relave to Scenario 1 (seeFigure 56). 2. Specifically, the sectoral scarcity indices for the primary and secondary sectors exhibited a reducon (reducƟon means posiƟve impact) ranging from 0.04 to 0.14 units on a scale of 0 to 1, summing up 0.4 points change out of 4 points in the total of the 4 sectors which are taken into account, aributable to the mul-sectoral approach implemented on the island of Crete. 3. The above indicate a 10% increase in the sum of indexes of total value of the sectors addressed by the CS for tourism in Crete. 4. These findings emphasize the crical role of a mul-sectoral approach in maximizing the effecveness of CS products. By integrang climate services across interconnected sectors, this approach enhances adaptaon capacies, reinforcing the necessity of holisc climate resilience strategies. Figure 56: Changes in sectoral scarcity indices. REFERENCES Biella, R., Wamucii, C.N., Mazzoleni, M., Baldassarre, G. Di, De Stefano, L., Hernandez, N. and Zapata, M. 2024. InnovaƟng Climate services through IntegraƟng ScienƟfic and local Knowledge Deliverable 4.3: QuanƟfying long-term paƩerns between adaptaƟon acƟons, socio-economic behaviours, and climate service informaƟon. Masih, I., Van Cauwenbergh, N., et al., 2022. Characterizaon of the I-CISK Living Labs, I-CISK Deliverable 1.1, Available online at www.icisk.eu/resources Reed, J., Barlow, J., Carmenta, R., van Vianen, J. and Sunderland, T. 2019. Engaging mulple stakeholders to reconcile climate, conservaon and development objecves in tropical landscapes. Biological ConservaƟon 238, p. 108229. Available at: hps://linkinghub.elsevier.com/retrieve/pii/S0006320719305737. -0.04 -0.12 -0.14 -0.10 0.27 -0.20 -0.15 -0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Accomodation cost Water scarcity Energy scarcity Roads innaccessibility Food cost Units change Sectoral scarcity indexes Units change Scenario 1 Scenario 2