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The sustainable management of water resources plays a key role in Mediterranean viticulture, characterized by scarcity and competition of available water. This study focuses on estimating the evapotranspiration and crop coefficients of table grapes vineyards trained on overhead "tendone" systems in the Apulia region (Italy). Maximum vineyard transpiration was estimated by adopting the "direct" methodology for ETp proposed by the Food and Agriculture Organization in Irrigation and Drainage Paper No. 56, with crop parameters estimated from Landsat 8 and RapidEye satellite data in combination with ground-based meteorological data. The modeling results of two growing seasons (2013 and 2014) indicated that canopy growth, seasonal and 10-day sums evapotranspiration values were strictly related to thermal requirements and rainfall events. The estimated values of mean seasonal daily evapotranspiration ranged between 4.2 and 4.1 mm·d-1, while midseason estimated values of crop coefficients ranged from 0.88 to 0.93 in 2013, and 1.02 to 1.04 in 2014, respectively. The experimental evapotranspiration values calculated represent the maximum value in absence of stress, so the resulting crop coefficients should be used with some caution. It is concluded that the retrieval of crop parameters and evapotranspiration derived from remotely-sensed data could be helpful for downscaling to the field the local weather conditions and agronomic practices and thus may be the basis for supporting grape growers and irrigation managers. [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]

Eco-hydrological models, such as SWAT (Soil Water Assessment Tool), are used to simulate complex hydrological processes and LU management in relation to water quality and quantity on a wide range of ecosystems. SWAT, developed by United States Department of Agriculture, is one of the most widely used watershed-scale modelling to assess changes in landscape management practices on water, sediment, and chemical yield. However, the availability of LU maps with good spatial and thematic resolution is one of the limiting factors in watershed modelling. Updated and detailed LU maps are required to grasp the variability and complexity of modelled landscapes. In fact, detailed LU maps with crop types can improve the model's capabilities in simulating evapotranspiration, surface runoff, soil infiltration, nutrient loss, and biomass production. This work reports the achievements in developing an integrated LU map for modelling watershed processes in the Mediterranean context within the Cervaro river basin (900 sq. km ca.), South Italy (Puglia region), with a dominant agricultural LU (Figure 1). Water is a critical natural resource in a Mediterranean country like Italy, vulnerable to risks stemming from climate change such as a related risk of decrease in water availability and crop yields. We applied a methodology for geospatial data integration from the Italian Paying Agency (AGEA) responsible for managing the farmers' subsidies with the Integrated Administration and Control System (IACS) in the framework of the Common Agricultural Policy (CAP). IACS geodata, such as the Land Parcel Identification System (LPIS) and the GeoSpatial Aid Application (GSAA), are the relevant resource on LU parcels managed by Italian farms. This typology of data is one of the best maintained datasets in EU with regular updates and quality controls. Recently, IACS data reusability is becoming a reality thanks to effort of the EU Commission to opening the data within the more general action in "shaping Europe's digital future" by fostering the re-use of government-held data (Directive (EU) 2019/1024). LPIS contains homogeneous land use/cover areas digitized from ortho-imagery with high spatial resolution, resulting in a wall-to-wall map including Italian agricultural and non-agricultural areas with a full update every three years. GSAAcontains digitized on-screen parcels for which an aid is requested yearly by Italian farmers and modified/updated by the paying agency after controls to ensure accuracy. Thematic details on agriculture within GSAA is dramatically higher than the LPIS thanks to the availability of crops classes detailed with a 5-level nomenclature. Within the LPIS an additional geographical layer is also available reporting the cadastral parcels with updated LU information deriving from in-situ field checks and other administrative sources. The conflation method for integrating the three vector layers (two LPIS and GSAA) followed different steps: conversion to a common projection system, topology and geometry checks, aggregation of small polygons and nomenclatures matching (from IACS to SWAT classes) through semantic analysis. Geometric and attributes processing allowed to reduce dimensionality of the "hybrid layer": from 300k to 50k ca. polygons and from 33k LU combinations to 57 SWAT LU classes (Table 1). The "hybrid layer" (Figure 2) enables accurate modelling with SWAT to understand the relationship between LU management and water quality as an important opportunity in the context of both the reformed CAP and the Farm to Fork strategy aiming to reduce the environmental and climate footprint of the EU food system by preserving and restoring the land and freshwater resources. The spatial details coming from very high-resolution imagery and thematic details enhanced by administrative controls and farmers declarations provides much higher performances compared to classical LU maps. The EU-wide data availability, the yearly updates of information and the detailed attributes (e.g., crops typology, greening and organic practices, crop rotation, conservation tillage, etc.) can shift upward the accuracy of the eco-hydrological modelling. [ABSTRACT FROM AUTHOR]