GSHP: Global database of soil hydraulic properties

1 Supplement to “Global soil water characteristics datasets and parameters” (https://doi.org/10.5281/zenodo.5547338) Surya Gupta1, Andreas Papritz1, Peter Lehmann1, Tomislav Hengl2,3, Sara Bonetti4, Dani Or1,5 1. Soil and Terrestrial Environmental Physics, Department of Environmental Systems Science, ETH, Zurich, Switzerland 2. OpenGeoHub Foundation, Wageningen, the Netherlands 3. EnvirometriX, Wageningen, the Netherlands 4. Soil Physics and Land Management Group, Wageningen University, Wageningen, The Netherlands 5. Division of Hydrologic Sciences, Desert Research Institute, Reno, NV, USA 1. Licence Creative Commons Attribution 4.0 International License (CC BY 4.0) 2. Citation When using the data please cite: Gupta, S., Papritz, A., Lehmann, P., Hengl, T., Bonetti, S., and Or, D.: Supplement to “GSHP: Global database of soil hydraulic properties”, Zenodo, https://doi.org/10.5281/zenodo.5547338, 2021. The data are supplementary material to: (if applicable) Gupta, S., Papritz, A., Lehmann, P., Hengl, T., Bonetti, S., and Or, D. (2022): Global soil water characteristics datasets and parameters. Scientific Data, accepted. 3. Data Description The representation of land surface processes in hydrological and climatic models is critically dependent on the soil water characteristics curve (SWCC) that defines the hydrological behavior of the unsaturated soil layers. The SWCC depends not only on soil texture but is also a function of soil structure (aggregates, biopores) and clay mineral type. Despite the availability of SWCC datasets in the literature, significant efforts are required to harmonize and fill in gaps in data before parameters can be determined and implemented in modeling applications. In this work, 15,259 SWCCs from 2,702 sites were assembled from published literature and other sources, standardized, and quality-checked to obtain global database of soil hydraulic properties (GSHP). The GSHP database covers most regions across the globe, with the 2 highest number of curves from North America followed by Africa, Europe, Asia, South America, Australia/Oceania. In addition to SWCCs, other soil variables such as soil texture (12,233 measurements), bulk density (15,125 measurements), and soil organic carbon (2,255 measurements) are also listed in the database. The data is arranged in one file. The “WRC_dataset_surya_et_al_2021_final.csv” presents the soil water characteristics curves data (SWCC), saturated hydraulic conductivity data, soil physical and chemical properties. Note that the SWCC data were fitted with the model of van Genuchten (VG) using “soilhypfit” package (Papritz, 2021). Papritz, A. soilhypfit: Modelling of Soil Water Retention and Hydraulic Conductivity Data (2022). R package version 0.1-5. 3.1 Description of file “WRC_dataset_surya_et_al_2021_final.csv” Table 1: Description and units of the variables listed in the database WRC_dataset_surya_et_al_2021_final.csv (layer_id, disturbed/undisturbed samples, climate classes, profile_id, reference, DOIs_URLs, methods used, longitude and latitude (decimal degree), top and bottom of soil sample (cm), horizon designation, dry and 33 kPa bulk density (g cm−3), soil organic carbon content (%), soil textural class, sand, silt, and clay content (%), soil reaction, saturated hydraulic conductivity measured in lab or field (cm day−1), porosity (m3/m3), gravimetric water content at 33 kPa (kg/kg), lab measured suction head (m) and corresponding volumetric water content (%), field measured suction head (m) and corresponding volumetric water content (m3/m3), soil texture classes to define the limits for vG parameters and source of the data, minimum and maximum value of location accuracy (m), classes for location accuracy, shape parameter and standard error of α (m-1), pore size distribution parameter and standard error of n, residual water content (m3/m3), saturated water content (m3/m3), likelihood-based confidence intervals of α and n for 3 confidence levels (0.5, 0.8, and 0.95), and quality indicator of SWCCs. NA is ‘no value’. Column names are also explained in Table 2 of main paper. Headers Description Units layer_id Unique ID of each SWCC ---- disturbed_undisturbed Sample soil structure disturbed or undisturbed during the analysis ---- climate_classes Climate information (temperate, boreal, tropical, arid etc.) ---- profile_id Unique ID of each profile ---- reference Data reference ---- DOIs_URLs Data DOIs or URLs ---- method Method used to measure the SWCC ---- method_keywords Comments on the methods if applicable ---- 3 latitude_decimal_degrees Ranges up to +90 degrees down to -90 degrees Decimal degree longitude_decimal_degrees Ranges up to +180 degrees Decimal degree 4 down to -180 degrees hzn_desgn Soil horizon designation ---- hzn_top Upper depth of soil sample cm hzn_bot Lower depth of soil sample cm db_33 Bulk density at 3.3 m matric potential g cm −3 db_od Dry bulk density g cm −3 oc Soil organic carbon content % tex_psda Soil texture classes based on USDA ---- sand_tot_psa_percent Mass of soil particle, > 0.05 and < 2 mm for fine earth dekagram/kg silt_tot_psa_percent Mass of soil particle, > 0.05 and < 2 mm for fine earth dekagram/kg clay_tot_psa_percent Mass of soil particles, < 0.002 mm for fine earth dekagram/kg ph_h2o Soil reaction ---- ksat_field Soil saturated hydraulic conductivity from field cm/day ksat_lab Soil saturated hydraulic conductivity from lab cm/day porosity Porosity m3/m3 WG_33kpa Gravimetric water content at 3.3 m matric potential kg/kg lab_head_m Lab measured matric potential m lab_wrc Lab measured volumetric water content m3/m3 field_head_m Field measured matric potential m field_wrc Field measured volumetric water content m3/m3 keywords_total_porosity Extra information regarding porosity ---- SWCC_classes SWCC classes (indicators for presence of wetand dry-end information) ---- source_db Source of the data ---- location_accuracy_min Minimum value of location accuracy m location_accuracy_max Maximum value of location accuracy m broad_accuracy_classes Classes for location accuracy ---- α VG shape parameter m-1 5 se_ α Standard error of α vG shape parameter m-1 n VG shape parameter ---- se_n Standard error of n vG shape parameter ---- θ r Residual water content m3/m3 θ s Saturated water content m3/m3 q2.5_ α 2.5 th percentile of α m-1 q97.5_ α 97.5 th percentile of α m-1 q10_ α 10 th percentile of α m-1 q90_ α 90 th percentile of α m-1 q25_ α 25 th percentile of α m-1 q75_ α 75 th percentile of α m-1 q2.5_ n 2.5th percentile of n ---- q97.5_ n 97.5th percentile of n ---- q10_ n 10th percentile of n ---- q90_ n 90th percentile of n ---- q25_ n 25th percentile of n ---- q75_ n 75th percentile of n ---- data_flag Classes that defines the quality of the vG parameters ---- Database reference: Abedi-Koupai, J., Sohrab, F., and Swarbrick, G.: Evaluation of hydrogel application on soil water retention characteristics. 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