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The Soil and Water Assessment Tool (SWAT) enables the simulation of watershed and river basin quantity and quality of surface and ground water under the influence of land use, management, and climate change. It can be used to monitor and control soil erosion, non-point source pollution and basin management. The recent version (SWAT+) was implemented by a dedicated QGIS plugin (QSWAT) widening the userbase and the potential modelling application worldwide. QSWAT, along with additional software for preparing the input dataset and for performing the calibration/validation phase, further extends the watershed modelling capabilities. Such tools and the growing diffusion of public open geospatial datasets are expected to increase the range of applications especially with the availability climate projections datasets. The latter will enable users to simulate all the watersoil phenomena at watershed level under future conditions to better understand and plan suitable action for preserving the natural resources. [ABSTRACT FROM AUTHOR]

The occurrence of water shortages ascribed to projected climate change, especially in the Mediterranean region, fosters the interest in remote sensing (RS) applications to optimize water use in agriculture. Remote sensing evapotranspiration and water demand estimation over large cultivated areas were used to manage irrigation to minimize losses during the crop growing cycle. The research aimed to explore the potential of the MultiSpectral Instrument (MSI) sensor on board Sentinel-2A to estimate crop parameters, mainly surface albedo (α) and Leaf Area Index (LAI) that influence the dynamics of potential evapotranspiration (ET p ) and Irrigation Water Requirements (IWR) of processing tomato crop ( Solanum lycopersicum L.). Maximum tomato ET p was calculated according to the FAO Penman-Monteith equation (FAO-56 PM) using appropriate values of canopy parameters derived by processing Sentinel-2A data in combination with daily weather information. For comparison, we used the actual crop evapotranspiration (ET a ) derived from the soil water balance (SWB) module in the Environmental Policy Integrated Climate (EPIC) model and calibrated with in-situ Root Zone Soil Moisture (RZSM). The experiment was set up in a privately-owned farm located in the Tarquinia irrigation district (Central Italy) during two growing seasons, within the framework of the EU Project FATIMA (FArming Tools for external nutrient Inputs and water Management). The results showed that canopy growth, maximum evapotranspiration (ET p ) and IWR were accurately inferred from satellite observations following seasonal rainfall and air temperature patterns. The net estimated IWR from satellite observations for the two-growing seasons was about 272 and 338 mm in 2016 and 2017, respectively. Such estimated requirement was lower compared with the actual amount supplied by the farmer with sprinkler and drip micro-irrigation system in both growing seasons resulting in 364 (276 mm drip micro-irrigation, and 88 mm sprinkler) and 662 (574 mm drip micro-irrigation, and 88 mm sprinkler) mm, respectively. Our findings indicated the suitability of Sentinel-2A to predict tomato water demand at field level, providing useful information for optimizing the irrigation over extended farmland. [ABSTRACT FROM AUTHOR]