Modelling of long term low water level in mountain river catchments area

Modelling of long term low water level in the mountain river catchments area Marek T. Kopacz 1) , Zbigniew Kowalewski 1) , Luis Santos 2) , Robert Mazur 1) , Vasco Lopes 3) , Agnieszka Kowalczyk 4) , Dominika Bar-Michalczyk 4) 1) AGH University of Science and Technology, Faculty of Mining Surveying and Environmental Engineering, Mickiewicza 30, 30-059, Kraków, Poland 2) Polytechnic Institute of Tomar, Departamento Arqueologia, Conservação e Restauro e Património, Portugal 3) Polytechnic Institute of Tomar, School of Technology, Portugal 4) Institute of Technology and Life Sciences – National Research Institute, Falenty, Hrabska Av. 3, 09-090 Raszyn, Poland RECEIVED 28.10.2021 REVIEWED 10.11.2021 ACCEPTED 10.12.2021 Abstract: Changing atmospheric conditions, including above all the deepening extreme weather phenomena, are increasing from year to year. This, in consequence, causes an increase in the incidence of low outflows. The study compares low water levels for two catchments: Biała Woda and Czarna Woda, and phosphorus and nitrogen load using the Nutrient Delivery Ratio (NDR) model in InVEST software. The objective of the NDR is to map nutrient sources from catchment area and transfer to the river bed. The nutrient loads (nitrogen and phosphorus) spread across the landscape are determined based on a land use (LULC) map and associated loading rates described in literature. The studies have shown that low water levels have been more common recently and pose the greatest threat to the biological life in the aquatic ecosystems. The structure of land use is also of great importance, with a significant impact on the runoff and nitrogen and phosphorus load. Phosphorus and runoff from surface sources to the water of Biała Woda and Czarna Woda catchments area has been reduced in forested areas. Only higher run-offs are observed in the residential buildings zone. The nitrogen load was also greater in the lower (estuary) parts of both catchments, where residential buildings dominate. Keywords: land use changes, low water level, nitrogen load, phosphorus load, small mountain catchments INTRODUCTION Mountain regions with harsh environmental conditions, steep, sloping sides, diversified habitats and low human occupation, play an important role a complete range of Ecosystem Services (ES), with freshwater being one of the most important services [EGAN, PRICE (eds.) 2017; GAGLIO et al. 2019]. Low environmental impact on such regions is paramount to maintain healthy ES in freshwater sources, however human occupation and activities such as agriculture and other land occupation changes ecosystem upstream and create pressures on artificial water reservoirs where nutrients are stored in the sediment bed due to hydrologic lotic to lentic modification of freshwater habitats [MAAVARA et al. 2020; LEHNER et al. 2011; MUHAMMED et al. 2021]. Climate change, in particular already detected extreme weather phenomena, affect mountain habitats altering hydrologic regimes and biogeochemical cycles. They include, but are not limited to short-lived torrential rains, which are followed by a frequent periods of no-rain. This, in consequence, causes an extensive low runoff periods and an increase in the incidence of low water levels [KOSMOWSKA et al. 2016; KOSTUCH 2003; YERDELEN et al. 2021], and leads to the reduction of water in catchment area. Water scarcity impairs ES [BYCZKOWSKI 1996]. The combination of land use pattern modification and climate change related torrential rains followed by no rain periods contribute to JOURNAL OF WATER AND LAND DEVELOPMENT e-ISSN 2083-4535 Polish Academy of Sciences (PAN) Institute of Technology and Life Sciences – National Research Institute (ITP – PIB) JOURNAL OF WATER AND LAND DEVELOPMENT DOI: 10.24425/jwld.2021.139033 2021, No. 51 (X–XII): 225–232 © 2021. The Authors. Published by Polish Academy of Sciences (PAN) and Institute of Technology and Life Sciences – National Research Institute (ITP – PIB). This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/3.0/) deterioration of reservoir water quality and ecosystems, mostly associated with P and N accumulation in reservoirs [BOIX-FAYOS et al. 2020; KISTNER et al. 2013]. Many regions of the world depend on mountains to provide the minimum supply of water. With climate change and population growth, countries which have never experienced severe ES degradation, are now facing serious challenges while attempting to recover from many years of inadequate land management practices. In the study, use of the new technology contributes to the quick and free of charge analysis providing monitoring tools and solution design strategies. The Millenium Ecosystem Assessment [CARPENTER et al. 2009] raised several red flags and from the gathered data an open source software programmes were produced such as Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) [Stanford University undated]. It offers a suite of models used to map and value the “goods and services” from nature that sustain and fulfil human life. Based on the longterm hydrological and chemical parameters monitoring the model of total phosphorus and nitrogen delivery ratio from surface area in small mountain catchments has been simulated. The Nutrient Delivery Ratio (NDR) from InVEST freshwater models will allows to evaluate the delivery of three ecosystem services in the basin: one supply (water), and two regulating (erosion control and water purification). They are essential services. A water scarcity can limit industrial activity, human water consumption and agriculture activities which also contribute to the degradation of water quality [GAGLIO et al. 2019; KALICKI et al. 2020; SALLUSTIO et al. 2017]. Erosion is also a major concern, and is expected to increase due to increasing land-use changes and flood frequency [LLENA et al. 2019]. The study aimed to analyse the frequency of low water occurrences in two small mountain catchments and its impact on the ecosystem services. It also helped to determine what parts of the basin are mostly impacted by the observed changes of hydrology and land use. The study creates the basis for mitigation strategies in the future. The assessment of the nitrogen and phosphorus loads introduced from the catchment area to the surface waters forms important part of the study. STUDY MATERIAL AND METHODS RESEARCH AREA The research area is within the Polish Western Carpathians, in particular the two adjacent upland catchments of the Biała Woda and Czarna Woda streams located on the right-bank of the Dunajec River, as part of the Grajcarek hydrographic basin (Fig. 1). The areas of both catchments are similar in size 10.91 km 2 and 11.66 km 2 respectively (Tab. 1). © 2021. The Authors. Published by Polish Academy of Sciences (PAN) and Institute of Technology and Life Sciences – National Research Institute (ITP – PIB). This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/3.0/) Fig. 1. Catchments of Biała Woda and Czarna Woda – Grajcarek, source: own elaboration Table 1. Basic morphometric parameters of catchment No Catchment stream Area (km 2 ) Average slope inclination (%) Average elevation 1) (m a.s.l.) Average stream slope (%) Density of river network (km·km –2 ) Stream lenght (km) 1 Biała Woda 10.91 24 842 4.43 3.15 7.93 2 Czarna Woda 11.66 31 895 7.51 2.38 6.95 1) KUREK, PAWLIK-DOBROWOLSKI [1990]. Source: own study. 226 Modelling of long term low water level in the mountain river catchments area Table 1 shows the basic morphometric features of both catchments, sharing similar characteristics, being the major difference the average slope decrease of the watercourse which is 4.43% for the Biała Woda catchment and 7.51% for the Czarna Woda. The average slope of the watercourse parameter is important when analysing the drainage flow depth and velocity. The landcover of the Biała Woda and Czarna Woda drainage basins is a mostly forest and pastures [TWARDY et al. 2002], where both these landuse forms account for over 90% of the total area of both catchments. However, differing significantly in forest cover, where in the Czarna Woda catchment, between 1950 and 1960, it was twice as large as the Biała Woda catchment. Recently this difference has narrowed to around 26%, though still significant. Meadows and pastures predominate in the Biała Woda catchment, where their area is 3.5 times larger than in Czarna Woda catchment. Other forms of land use occupy minor areas (Tab. 2). Analysing the landuse structure of both catchments for the last half-century (Tab. 2), significant changes in the proportion between forest area and grassland are observed, which for its often-non-agricultural role are considered grasslands. Both catchments display significant changes in landuse, where secondary succession processes contributed to the increase in forest cover in the Czarna and Biała Woda catchment areas. STUDY METHODS This work uses 67 years of landuse (1950–2017) from Corine Landcover and the Polish Institute of technology and Life Sciences data, together with 48 years of hydrologic data (1971– 2018), from the Polish Institute of Technology and Life Sciences for 2 watersheds in Poland sharing similar characteristics, though with different historical landuse. The studies covered the historical period, hydrological years 1971–2018, a full 48 years (data from Research Station in Jaworki – Institute of Technology and Life Sciences, Malopolska Research Centre). In selected analyses, the entire study period was divided into six equal eight-year intervals that corresponded to the hydrological cycles of low water occurrence in both studied catchments. The intervals of hydrological years: 1971–1978 (period 1); 1979–1986 (period 2); 1987–1994 (period 3); 1995– 2002 (period 4); 2003–2010 (period 5) and 2011–2018 (period 6). The average unit runoff from the Biała Woda catchment area for many years is 16.98 dm –3 ·s –1 ·km –2 , while from Czarna Woda is 19.50 dm –3 ·s –1 ·km –2 (Tab. 3). The identification of low waters required the setting of equal criteria. The shallow low waters limit value was adopted at the level of the upper limit of low unit outflows for the superior catchment – the Grajcarek stream [BAJKIEWICZ-GRABOWSKA, MIKULSKI 1999]. After conversion – low flows concern all unit outflows smaller than 5.17 dm –3 ·s –1 ·km –2 from the Biała Woda catchment area and less than 8.35 dm –3 ·s –1 ·km –2 from the Czarna Woda catchment [KOSTUCH 2003]. In these ranges of unit outflows, they were called shallow low waters. The drain hydrographs were analysed with a minimum duration of 7 days [DYNOWSKA 1971]. The low waters also include the period between neighbouring shallow low waters with an outflow greater than low waters, but smaller than the average unit outflow from many years, if its duration did not exceed two days [OZGA-ZIELIŃSKA 1990; OZGA-ZIELIŃSKA, BRZEZIŃSKI, 1997]. The outflow hydrographs are shown as periods of low flows, which correspond to low water levels. Low waters can be divided into shallow and deep. Shallow low waters occur when the water levels in the river change between the lower limit of medium and medium-low levels for at least several days. Deep low waters are those for which water levels are below medium-low states [BAJKIEWICZ-GRABOWSKA, MIKULSKI 1999]. In turn, the limit values for deep low waters were adopted at the level of the average low unit outflow, which for the Biała Woda stream is 2.57 dm –3 ·s –1 ·km –2 , and for the Czarna Woda stream 4.85 dm –3 ·s –1 ·km –2 . The minimum duration of the outflow for deep low waters was 11 days. Table. 2. Estimated, simplified structure of land use in research catchments Catchment Mean from years Area (km 2 ) Land use area (% total area) forest grasslands arable land built-up areas others Biała Woda 1950–1960 10.91 29.3 58.0 4.6 0.3 7.8 1995–2005 56.2 39.8 0.8 0.5 2.6 2014–2017 62.5 31.6 0.6 1.4 3.9 Czarna Woda 1950–1960 11.66 63.9 34.4 1.1 0.2 0.4 1995–2005 82.9 15.7 0.5 0.8 0.1 2014–2017 88.3 8.4 0.3 1.8 1.2 Source: own elaboration. Table 3. Characteristic discharges in Grajcarek catchment Characteristic discharges Specific runoffs (dm –3 ·s –1 ·km –2 ) Low <8.0 Medium 8.0–29.9 Medium-high 30.0–59.9 High 60.0–79.9 Very high 80.0–149.9 Extremely high >150.0 Source: own elaboration based on FIGUŁA [1966]. © 2021. The Authors. Published by Polish Academy of Sciences (PAN) and Institute of Technology and Life Sciences – National Research Institute (ITP – PIB). This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/3.0/) Marek T. Kopacz et al. 227 Analysis regarding the incidence of low waters conditions were performed using the R program in version 3.5.1 with the RStudio in version 1.1.456. Data organysation and visualysation took place using the tidy-verse package, date conversion, and analysis was done using the CRHMr and hydrostats packages [BOND 2018; R Core Team 2018; SHOOK 2016; WICKHAM 2017]. Changes in the concentration of total phosphorus and nitrogen load were also analysed and a field model of the nutrient delivery ratio for this element was developed for both catchments. The research used the Nutrient Delivery Ratio (NDR) model in InVEST software, (Freshwater Quality Models) [TALLIS et al. 2011]. InVEST mathematical models are spatially-explicit, using maps (GIS) as information sources and producing maps as outputs. The objective of the NDR is to map nutrient sources from catchment area and their transport to the river bed. In this mathematical model applied a simple material balance approach, describing the transport of a mass of nutrient through the defined area (in the analysed watershed/subwatershed). The size of the load in the model is presented in kg of substance per 1 conventional pixel (kg∙px –1 ). The nutrient loads across the landscape, are determined based on a land use (LULC) map and associated loading rates described in literature [BREUER et al. 2008; ENDRENY, WOOD 2003; HAMEL et al. 2015; HAMEL, GUSWA 2015; HAN et al. 2021; HARMEL et al. 2006; ZHANG et al. 2021]. RESULTS The study analyses changes in the frequency of shallow low waters in both studied catchments. Their seasonal distribution is similar, low water conditions occurred in the months from September to March. An upward trend in low waters is also noted in the summer (July, August) since the 1990s. A clear periodicity of low water occurrence in hydrological years was also observed Figure 2. There is a permanent increase in the number of days during which shallow low water conditions occurred (Fig. 3). In the first period (1971–1978) in the Biała Woda stream, the shallow low waters lasted a total of 442 days (15% of the 8 years). In the Czarna Woda stream, 337 days with shallow low waters were registered during this period (11.5% of the period duration). Over the years, these values increased accordingly – reaching in the sixth-period values for Biała Woda – 857 days (29.3%) and Czarna Woda – up to 1023 days (35% of the entire period). The shape of summary curves shows a significant increase in days with shallow low waters but also characterises their seasonal distribution. In the 70s of the 20th centuries, long, nondiscontinuous periods of several years were recorded (horizontal sum curves, e.g., for time intervals 1 and 2, i.e. for the years 1971– 1986), while the last years were often low waters periods separated by much shorter non-discontinuous periods (short horizontal sum curves – Fig. 3). Deep low waters in the scale of the analysed period occurred much less frequently than shallow low waters (Fig. 4). They mainly concerned autumn and winter months (from September to January) and during the 48 years; they occurred sporadically. Deep low waters were recorded in the months from November to March only in the hydrological years 1985 and 1987. However, it is worrying that deep low waters were recorded mainly in recent years (e.g. 2004, 2012, 2013), both in the winter and summerautumn months, which, given the increasing number of shallow low waters, gives a quite pessimistic picture of future hydrological changes in both catchments. After analysing the deep low waters in the set of time intervals, this unfavourable phenomenon is even more noticeable. A clear increase in the number of days with deep low waters in both analysed streams occurred only recently in the hydrological years 2011–2018 (Fig. 5). For these eight years, there were more days with deep low waters than during the previous five periods, i. e. up to 40 years. Both shallow (Fig. 3) and deep (Fig. 5) occur more frequently in the Czarna Woda stream. Phosphorus and runoff from surface sources to the water of Biała Woda and Czarna Woda catchments area has been reduced in forested areas. Only higher run-offs are observed in the Fig. 2. Occurrence periods of shallow low water level in studied catchments in years 1971–2018: a) Biała Woda stream, b) Czarna Woda stream; source: own study © 2021. The Authors. Published by Polish Academy of Sciences (PAN) and Institute of Technology and Life Sciences – National Research Institute (ITP – PIB). This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/3.0/) 228 Modelling of long term low water level in the mountain river catchments area Fig. 3. Summary of shallow low water level days for studied catchments: a) Biała Woda, b) Czarna Woda; source: own study Fig. 4. Occurrence periods of deep low water level in studied streams in years 1971–2018: a) Biała Woda stream, b) Czarna Woda stream; source: own study Fig. 5. Summary of deep low water level days for studied streams: a) Biała Woda, b) Czarna Woda; source: own study © 2021. The Authors. Published by Polish Academy of Sciences (PAN) and Institute of Technology and Life Sciences – National Research Institute (ITP – PIB). This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/3.0/) Marek T. Kopacz et al. 229 residential buildings zone (Fig. 6). The higher concentrations of phosphorus can be observed in the Biała Woda catchment, in its central and estuary parts, where urbanised areas dominate. The nitrogen load was also greater in the lower (estuary) parts of both catchments, where residential buildings dominate. In the remaining part of the Biała Woda catchment (green areas, rocks, extensively used pastures) the nitrogen load did not exceed 0.006 kg∙px –1 (kilogram per conventional pixel). While the minimum increase in the nitrogen load is observed in the completely forestry central part of the Czarna Woda catchment (Fig. 7). Fig. 6. Model of total phosphorus delivery ratio from surface area in basin of Biała Woda and Czarna Woda; source: own study Fig. 7. Model of total nitrogen delivery ratio from surface area in basin of Biała Woda and Czarna Woda; source: own study © 2021. The Authors. Published by Polish Academy of Sciences (PAN) and Institute of Technology and Life Sciences – National Research Institute (ITP – PIB). This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/3.0/) 230 Modelling of long term low water level in the mountain river catchments area DISCUSSION Small mountain catchments (Carpathian) have specific hydrological characteristics. Hydrograms in mountain streams differ in shape and dynamics compared to lowland rivers [B AILEY et al. 2003]. To a much greater extent, the size and nature of the surface runoff from the catchment area are determined by indirect factors, such as the terrain and the way it is developed [BAJKIEWICZGRABOWSKA 2008]. It is obvious that in mountain basins we register extreme phenomena more often, both floods and low waters conditions. This variability is shaped both in the spatial arrangement, which was analysed on the example of two catchments with different land-use structures, in particular in the proportion of afforestation. Their size and distribution were typical for mountain conditions. The lowest values were recorded in the winter months (from January to March), while the highest was in June and July. The seasonal distribution of low waters in both research catchments was similar, they occurred mainly in the winter, more often in the more forested Czarna Woda catchment. However, since the 1990s, there has been an upward trend in low waters emergence, which is also more common in summer (July, August). Over the years, the temporal nature of low waters also changed – in the 1970s low waters were separated by long, even several years non-discount periods, while recently low waters periods appear more often and are separated by much shorter non-discount periods. The influence of forest cover on the proportions in the occurrence of low waters is also noted. Even in the 1970s, the barely forested Biała Woda catchment area recorded more low waters than the heavily forested Czarna Woda catchment area. These changes have a positive effect on the stabilysation of the biogeochemical cycles of nutrient elements [POWERS, MARÍNSPIOTTA 2017; WINBOURNE et al. 2018; SZALIŃSKA, DOMINIK 2006]. The reduction of arable and pasture land is associated with a reduction in the export of macro and microelements to the water of both rivers. Evidences from literature, such as the catchment area of Hubbard Brook (USA), proved the role of plant cover in the cycle of elements in nature. Along with controlled logging, the exports of selected elements from the area to the Hubbard Brook River increased significantly [BAILEY et al. 2003; BORMANN, LIKENS 2012; BURTON, LIKENS 1975]. CONCLUSIONS 1. In the last 48 years, there have been slow but consistent hydrological changes in the Carpathian drainage basins. Low water levels occur more and more often and in the last eight years the occurrence of so-called deep low waters, which poses the greatest threat to the biological life of aquatic ecosystems. 2. The increase in the number of days with low water levels in both catchments probably be caused by irregular rainfall, which was not analysed in this study. 3. The impact of afforestation on the incidence of low waters, compared to other factors, is getting smaller, and this phenomenon is noticeable in the entire Western Carpathian region. This is indicated by the studies conducted by the Institute of Technology and Life Sciences in Jaworki. 4. The land use structure in the last several dozen years has a significant influence on the runoff, as well as nitrogen and phosphorus loads. REFERENCES BAILEY A. S. HORNBECK J.W., CAMPBELL J.L., EAGAR C. 2003. Hydrometeorological database for Hubbard Brook Experimental Forest, 1955–2000. General Technical Report NE-305. Delaware, OH. US Department of Agriculture, Forest Service, Northeastern Research Station. DOI 10.2737/NE-GTR-305. BAJKIEWICZ-GRABOWSKA E., MIKULSKI Z. 2008. Hydrologia ogólna [General hydrology]. Warszawa. PWN. ISBN 978-83-01-14579-8 pp. 313. BOIX-FAYOS C., BOERBOOM, L.G.J., JANSSEN R., MARTÍNEZ-MENA M., ALMAGRO M., PÉREZ-CUTILLAS P., EEKHOUT J.P.C., CASTILLO V., DE VENTE J. 2020. Mountain ecosystem services affected by land use changes and hydrological control works in Mediterranean catchments. Ecosystem Services. Vol. 44, 101136. DOI 10.1016/j .ecoser.2020.101136. BOND N. 2018. Hydrostats: Hydrologic indices for daily time series data. R package version 0.2.6 [online]. [Access 31.08.2021]. Available at: https://CRAN.R-project.org/package=hydrostats BORMANN F.H., LIKENS G.E. 2012. Pattern and process in a forested ecosystem: disturbance, development and the steady state based on the Hubbard Brook ecosystem study. Springer Science & Business Media. ISBN 1461262321 pp. 272. BREUER L., VACHÉ K.B., JULICH S., FREDE H.G. 2008. Current concepts in nitrogen dynamics for mesoscale catchments. Hydrological Sciences Journal. Vol. 53 p. 1059–1074. DOI 10.1623/hysj .53.5.1059. BURTON T.M., LIKENS G.E. 1975. Energy flow and nutrient cycling in salamander populations in the Hubbard Brook Experimental Forest, New Hampshire. Ecology. Vol. 56(5) p. 1068–1080. DOI 10.2307/1936147. BYCZKOWSKI A. 1996. Hydrologia [Hydrology]. T. 2. Warszawa. SGGW. ISBN 83-7244-069-7 pp. 356. CARPENTER S.R., MOONEY H.A., AGARD J., CAPISTRANO D., DEFRIES R.S., DÍAZ S., ..., WHYTE A. 2009. Science for managing ecosystem services: Beyond the Millennium Ecosystem Assessment. PNAS. Vol. 106(5) p. 1305–1312. DOI 10.1073/pnas.0808772106. DYNOWSKA I. 1971. Typy reżimów rzecznych w Polsce [Types of river regimes in Poland]. Zeszyty Naukowe Uniwersytetu Jagiellońskiego. Prace Geograficzne. Z. 28 p. 67–81. EGAN P.U., PRICE M.U. (eds.) 2017. Mountain ecosystem services and climate change: A global overview of potential threats and strategies for adaptation [online]. Paris. UNESCO. ISBN 978-923-100225-0 pp. 32. [Access 10.09.2021]. Available at: https:// unesdoc.unesco.org/ark:/48223/pf0000248768news/climatechange-impacts-major-mountainous-regions-world-0 ENDRENY T.A., WOOD E.F. 2003. Watershed weighting of export coefficients to map critical phosphorous loading areas. Journal of the American Water Resources Association. Vol. 39(1) p. 165– 181. DOI 10.1111/j.1752-1688.2003.tb01569.x. FIGUŁA K. 1966. Kształtowanie się odpływów w zlewniach potoków Biała i Czarna Woda. Badania nad gospodarką wodną zlewni górskich zalesionych i niezalesionych [Formation of outflows in the catchments of the Biała and Czarna Woda streams. Research on water management in forested and non-forested mountain catchments]. Cz. 2. Roczniki Nauk Rolniczych. Ser. D. T. 118 p. 51–90. GAGLIO M., ASCHONITIS V., PIERETTI L., SANTOS L., GISSI E., CASTALDELLI G., FANO E. A. 2019. Modelling past, present and future Ecosystem Services supply in a protected floodplain under land use and climate changes. Ecological Modelling. DOI 10.1016/j. ecolmodel.2019.04.019. © 2021. The Authors. Published by Polish Academy of Sciences (PAN) and Institute of Technology and Life Sciences – National Research Institute (ITP – PIB). This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/3.0/) Marek T. Kopacz et al. 231 HAMEL P., CHAPLIN-KRAMER R., SIM S., MUELLER C. 2015. A new approach to modeling the sediment retention service (InVEST 3.0): Case study of the Cape Fear catchment, North Carolina, USA. Science of The Total Environment. Vol. 524–525 p. 166–177. DOI 10.1016/j.scitotenv.2015.04.027. HAMEL P., GUSWA A. J. 2015. Uncertainty analysis of the InVEST 3.0 Nutrient Model: Case study of the Cape Fear Catchment, NC. Hydrology and Earth System Sciences Discussion. Vol. 11 p. 11001–11036. DOI 10.5194/hessd-11-11001-2014. HAN B., REIDY A., LI A. 2021. Modeling nutrient release with compiled data in a typical Midwest watershed. Ecological Indicators. Vol. 121, 107213. DOI 10.1016/j.ecolind.2020.107213. HARMEL D., POTTER S., CASEBOLT P., RECKHOW K. 2006. Compilation of measured nutrient load data for agricultural land uses in the United States. Journal of the American Water Resources Association. Vol. 42(5), 05084 p. 1163–1178. DOI 10.1111/ j.1752-1688.2006.tb05292.x KALICKI T., PRZEPIÓRA P., KUSZTAL P., CHRABĄSZCZ M., FULARCZYK K., KŁUSAKIEWICZ E., FRĄCZEK M. 2020. Historical and present-day human impact on fluvial systems in the Old-Polish Industrial District (Poland). Geomorphology. Vol. 357. DOI 10.1016/j. geomorph.2020.107062. KISTNER I., OLLESCH G., MEISSNER R., RODE M. 2013. Spatial-temporal dynamics of water soluble phosphorus in the topsoil of a low mountain range catchment. Agriculture, Ecosystems and Environment. Vol. 176 p. 24–38. DOI 10.1016/j.agee.2013.05.01. KOSMOWSKA A., ŻELAZNY M., MAŁEK S., SIWEK J. P., JELONKIEWICZ Ł. 2016. Effect of deforestation on stream water chemistry in the Skrzyczne massif (the Beskid Śląski Mountains in southern Poland). Science of The Total Environment. Vol. 568 p. 1044– 1053. DOI 10.1016/j.scitotenv.2016.06.123. KOSTUCH M. 2003. Odpływy podziemne niskie w potokach górskich [Groundwater and low runoffs in mountain sterams]. WodaŚrodowisko-Obszary Wiejskie. T. 3. Z. 1(7) p. 193–203. KUREK S., PAWLIK-DOBROWOLSKI J. 1990. Określenie zmian odpływu w zróżnicowanych warunkach środowiska przyrodniczego małych zlewni w dorzeczu górnego Grajcarka (Doniesienie naukowe) [Determination of changes of falls in different conditions of natural environment the small drainages in drainage area of upper Grajcarek (Scientific report)]. Problemy Zagospodarowania Ziem Górskich. Z. 29 p. 135–141. LEHNER B., LIERMANN C.R., REVENG C., VÖRÖSMARTY C., FEKETE B., CROUZET P., ..., WISSER D. 2011. High-resolution mapping of the world’s reservoirs and dams for sustainable river-flow management. Frontiers in Ecology and the Environment. Vol. 9 p. 494– 502. DOI.org/10.1890/100125. LLENA M., VERICAT D., CAVALLI M., CREMA S., SMITH M.W. 2019. The effects of land use and topographic changes on sediment connectivity in mountain catchments. Science of the Total Environment. Vol. 660 p. 899–912. DOI 10.1016/j.scitotenv .2018.12.479. MAAVARA T., CHEN Q., VAN METER K., BROWN L.E., ZHANG J., NI J., ZARFL C. 2020. River dam impacts on biogeochemical cycling. Nature Reviews Earth and Environment. Vol. 1(2) p. 103–116. DOI 10.1038/s43017-019-0019-0. MUHAMMED H.H., MUSTAFA A.M., KOLERSKI T. 2021. Hydrological responses to large-scale changes in land cover of river watershed: Review. Journal of Water and Land Development. No. 50 p. 108– 121. DOI 10.24425/jwld.2021.138166. OZGA-ZIELIŃSKA M. 1990. Niżówki i wezbrania – ich definiowanie i modelowanie [Low flows and raised waters – their characteristics and modeling]. Przegląd Geofizyczny. R. 35. Z. 1–2 p. 33–43. OZGA-ZIELIŃSKA M., BRZEZIŃSKI J. 1997. Hydrologia stosowana [Applied hydrology]. Warszawa. PWN. ISBN 8301121947 pp. 324. POWERS J.S., MARÍN-SPIOTTA E. 2017. Ecosystem processes and biogeochemical cycles in secondary tropical forest succession. Annual Review of Ecology, Evolution, and Systematics. Vol. 48 p. 497–519. R Core Team 2018. The R Project for Statistical Computing. [online]. Vienna, Austria. R Foundation for Statistical Computing. [Access 10.9.2021]. Available at: https://www.R-project.org/ SALLUSTIO L., DE TONI A., STROLLO A., DI FEBBRARO M., GISSI E., CASELLA L., GENELETTI D., MUNAFÒ M., VIZZARRI M., MARCHETTI M. 2017. Assessing habitat quality in relation to the spatial distribution of protected areas in Italy. Journal of Environmental Management. DOI 10.1016/j.jenvman.2017.06.031. SHOOK K. 2016. CRHMr: preand postprocessing for the Cold Regions Hydrological Modelling (CRHM) platform [online]. [Access 10.9.2021]. Available at: https://github.com/CentreForHydrology/CRHMr Stanford University undated. Natural Capital Project. Invest [online]. [Access 10.10.2021]. Available at: https://naturalcapital project. stanford.edu/software/invest SZALIŃSKA E., DOMINIK J. 2006. Water quality changes in the Upper Dunajec Watershed, Southern Poland. Polish Journal of Environmental Studies. Vol. 15(2) p. 327–334. TALLIS H., RICKETTS T.H., DAILY G.C., POLASKY S. 2011. Natural capital: theory and practice of mapping ecosystem services. Oxford University Press. ISBN 9780199588992 pp. 432. DOI 10.1093/ acprof:oso/9780199588992.001.0001. TWARDY S., KOPACZ M., JAGUŚ A. 2002. Charakterystyka przyrodnicza zlewni Grajcarka ze szczególnym uwzględnieniem środowiska wodnego i użytkowania terenu [Natural characteristics of the Grajcarka catchment with particular emphasis on the water environment and land use]. Kraków–Falenty. Wydaw. IMUZ. ISBN 83-88763-14-8 pp. 88. WICKHAM H. 2017. Tidyverse: Easily install and load the ‘Tidyverse’. R package version 1.2.1 [online]. [Access 10.10.2021]. Available at: https://CRAN.R-project.org/package=tidyverse WINBOURNE J.B., FENG A., REYNOLD L., PIOTTO D., HASTINGS M.G., PORDER S. 2018. Nitrogen cycling during secondary succession in Atlantic Forest of Bahia, Brazil. Scientific Reports. Vol. 8(1) p. 1–9. YERDELEN C., ASIKOGLU Ö.L., ABDELKADER M., ERIS E. 2021. Estimation of standard duration maximum rainfall by using regression models. Journal of Water and Land Development. No. 50 p. 281–288. DOI 10.24425/jwld.2021.138184. ZHANG L., HICKEL K., DAWES W.R., CHIEW F.H.S., WESTERN A.W., BRIGGS P.R. 2021. 2.2. 5 NDR: Nutrient Delivery Ratio. InVEST pp. 113. © 2021. The Authors. Published by Polish Academy of Sciences (PAN) and Institute of Technology and Life Sciences – National Research Institute (ITP – PIB). This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/3.0/) 232 Modelling of long term low water level in the mountain river catchments area