Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–² Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-2161 Peer reviewed articles 2020 José A. Gómez, Gema Guzmán, Arsenio Toloza, Christian Resch, Roberto García-Ruíz, Lionel Mabit Variation of soil organic carbon, stable isotopes, and soil quality indicators across an erosion–deposition catena in a historical Spanish olive orchard SOIL 10.5194/soil-6-179-2020 Uncategorized Natural Water Bodies Abstract. This study compares the distribution of bulk soil organic carbon (SOC), its fractions (unprotected and physically, chemically, and biochemically protected), available phosphorus (Pavail), organic nitrogen (Norg), and stable isotope (δ15N and δ13C) signatures at four soil depths (0–10, 10–20, 20–30, and 30–40 cm) between a nearby open forest reference area and a historical olive orchard (established in 1856) located in southern Spain. In addition, these soil properties, as well as water stable aggregates (Wsagg), were contrasted at eroding and deposition areas within the olive orchard, previously determined using 137Cs. SOC stock in the olive orchard (about 40 t C ha−1) was only 25 % of that in the forested area (about 160 t C ha−1) in the upper 40 cm of soil, and the reduction was especially severe in the unprotected organic carbon. The reference and the orchard soils also showed significant differences in the δ13C and δ15N signals, likely due to the different vegetation composition and N dynamics in both areas. Soil properties along a catena, from erosion to deposition areas within the old olive orchard, showed large differences. Soil Corg, Pavail and Norg content, and δ15N at the deposition were significantly higher than those of the erosion area, defining two distinct areas with a different soil quality status. These overall results indicate that the proper understanding of Corg content and soil quality in olive orchards requires the consideration of the spatial variability induced by erosion–deposition processes for a convenient appraisal at the farm scale. 773903
publications-2162 Peer reviewed articles 2019 Francesco Novelli, Heide Spiegel, Taru Sandén, Francesco Vuolo Assimilation of Sentinel-2 Leaf Area Index Data into a Physically-Based Crop Growth Model for Yield Estimation Agronomy 10.3390/agronomy9050255 Uncategorized River Basins Remote sensing data, crop growth models, and optimization routines constitute a toolset that can be used together to map crop yield over large areas when access to field data is limited. In this study, Leaf Area Index (LAI) data from the Copernicus Sentinel-2 satellite were combined with the Environmental Policy Integrated Climate (EPIC) model to estimate crop yield using a re-calibration data assimilation approach. The experiment was implemented for a winter wheat crop during two growing seasons (2016 and 2017) under four different fertilization management strategies. A number of field measurements were conducted spanning from LAI to biomass and crop yields. LAI showed a good correlation between the Sentinel-2 estimates and the ground measurements using non-destructive method. A correlating fit between satellite LAI curves and EPIC modelled LAI curves was also observed. The assimilation of LAI in EPIC provided an improvement in yield estimation in both years even though in 2017 strong underestimations were observed. The diverging results obtained in the two years indicated that the assimilation framework has to be tested under different environmental conditions before being applied on a larger scale with limited field data. 773903
publications-2163 Peer reviewed articles 2021 Xun Wu, Jianchu Shi, Qiang Zuo, Mo Zhang, Xuzhang Xue, Lichun Wang, Ting Zhang, Alon Ben-Gal Parameterization of the water stress reduction function based on soil–plant water relations Irrigation Science 10.1007/s00271-020-00689-w Uncategorized Natural Water Bodies No abstract available 773903
publications-2164 Peer reviewed articles 2020 Xun Wu, Qiang Zuo, Jianchu Shi, Lichun Wang, Xuzhang Xue, Alon Ben-Gal Introducing water stress hysteresis to the Feddes empirical macroscopic root water uptake model Agricultural Water Management 10.1016/j.agwat.2020.106293 Uncategorized River Basins No abstract available 773903
publications-2165 Peer reviewed articles 2021 José A. Gómez, Ana Sánchez Montero, Gema Guzmán, María-Auxiliadora Soriano In-depth analysis of soil management and farmers’ perceptions of related risks in two olive grove areas in southern Spain International Soil and Water Conservation Research 10.1016/j.iswcr.2021.01.003 Data Management & Analytics Natural Water Bodies No abstract available 773903
publications-2166 Peer reviewed articles 2020 J.M. Ramírez-Cuesta, R.G. Allen, D.S. Intrigliolo, A. Kilic, C.W. Robison, R. Trezza, C. Santos, I.J. Lorite METRIC-GIS: An advanced energy balance model for computing crop evapotranspiration in a GIS environment Environmental Modelling & Software 10.1016/j.envsoft.2020.104770 Data Management & Analytics Uncategorized No abstract available 773903
publications-2167 Peer reviewed articles 2020 Jianchu Shi, Xun Wu, Xiaoyu Wang, Mo Zhang, Le Han, Wenjing Zhang, Wen Liu, Qiang Zuo, Xiaoguang Wu, Hongfei Zhang, Alon Ben-Gal Determining threshold values for root-soil water weighted plant water deficit index based smart irrigation Agricultural Water Management 10.1016/j.agwat.2019.105979 IoT & Sensors Uncategorized No abstract available 773903
publications-2168 Peer reviewed articles 2021 Jerabek & Zumr GEOPHYSICAL SURVEY AS A TOOL TO REVEAL SUBSURFACE STRATIFICATION AT A SMALL AGRICULTURAL HEADWATER CATCHMENT: A CASE STUDY Stavební Obzor - Civil Engineering Journal 10.14311/cej.2021.03.0059 IoT & Sensors Irrigation Systems Catchment drainage area is a basic spatial unit in landscape hydrology within which the authorities estimate a water balance and manage water resources. The catchment drainage area is commonly delineated based on the surface topography, which is determined using a digital elevation model. Therefore, only a flow over the surface is implicitly considered. However, a substantial portion of the rainfall water infiltrates and percolates through the soil profile to the groundwater, where geological structures control the drainage area instead of the topography of the soil surface. The discrepancy between the surface topography-based and bedrock-based drainage area can cause large discrepancies in water balance calculation. It this paper we present an investigation of the subsurface media stratification in a headwater catchment in the central part of the Czech Republic using a geophysical survey method - electrical resistivity tomography (ERT). Results indicate that the complexity of the subsurface geological layers cannot be estimated solely from the land surface topography. Although shallow layers copy the shape of the surface, the deeper layers do not. This finding has a strong implication on the water transport regime since it suggests that the deep drainage may follow different pathways and flow in other directions then the water in shallow soil profile or shallow subsurface structures. 773903
publications-2169 Peer reviewed articles 2022 Busschaert, L; De Roos, S; Thiery, W; Raes, D; De Lannoy, GJM Net irrigation requirement under different climate scenarios using AquaCrop over Europe Hydrology and Earth System Sciences 10.5194/hess-26-3731-2022 Data Management & Analytics Uncategorized Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average, 70 % of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the Food and Agriculture Organization (FAO) crop growth model AquaCrop version 6.1. The model is run at 0.5∘lat×0.5∘long resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the AquaCrop surface soil moisture (SSM) forced with two types of ISIMIP3 historical meteorological datasets is evaluated with satellite-based SSM estimates in two ways. When driven by ISIMIP3a reanalysis meteorology, daily simulated SSM values have an unbiased root mean square difference of 0.08 and 0.06 m3 m−3, with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively, for the years 2015–2016 (2016 is the end year of the reanalysis data). When forced with ISIMIP3b meteorology from five global climate models (GCMs) for the years 2015–2020, the historical simulated SSM climatology closely agrees with the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031–2060 and 2071–2100) is compared to the baseline period of 1985–2014 to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 22 mm per month (+30 %) under a high-emission scenario Shared Socioeconomic Pathway (SSP) 3–7.0. Central and southern Europe are the most impacted, with larger Inet increases. The interannual variability in Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1–2.6), the increase in Inet will stabilize at around 13 mm per month towards the end of the century, and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs. 773903
publications-2170 Peer reviewed articles 2022 Tenreiro, TR; Jerabek, J; Gomez, JA; Zumr, D; Martinez, G; Garcia-Vila, M; Fereres, E Simulating water lateral inflow and its contribution to spatial variations of rainfed wheat yields European Journal of Agronomy 10.1016/j.eja.2022.126515 IoT & Sensors Irrigation Systems No abstract available 773903