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Climate change poses significant challenges to agricultural systems in the Mediterranean region, with Italy being significantly affected. This literature scoping review aims to examine existing research on the impact of climate change on yield and income on the three agri-food value chains in Italy: viticulture, fruit and vegetables, and dairy cattle. By analysing the available literature, this study seeks to outline the pros and cons, knowledge gaps, and potential areas for future research. A systematic search of scientific databases was conducted to identify relevant articles published between 2000 and 2022. The search terms included climate change, agriculture, Italy, yield, income, and related keywords. Articles were screened based on predetermined inclusion and exclusion criteria, resulting in a final selection of studies. Quantitative information was collected and organized into descriptive tables. The review encompassed 44 studies that investigated the impact of climate change on yield and income in various agricultural sectors across different regions of Italy. The findings indicate that climate change is already impacting crop productivity and income levels, with increased temperature, changes in precipitation patterns, and extreme weather events being identified as the primary drivers. Additionally, disparities were observed between different agricultural regions, crops, and farming systems, highlighting the need for location-specific and crop-specific assessments. The scoping review provides a prospective overview of the existing literature on climate change impacts on yield and income within the Italian agriculture system. It underscores the urgency for targeted adaptation strategies to minimize the negative consequences of climate change. Further research should focus on understanding the complex interactions between climate change, agricultural practices, socio-economic factors, and policy interventions to develop context-specific solutions for sustainable agriculture in Italy. [ABSTRACT FROM AUTHOR]

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 consequences of climate change on food security in arid and semi-arid regions can be serious. Understanding climate change impacts on water balance is critical to assess future crop performance and develop sustainable adaptation strategies. This paper presents a climate change impact study on the water balance components of an agricultural watershed in the Mediterranean region. The restructured version of the Soil and Water Assessment Tool (SWAT+) model was used to simulate the hydrological components in the Sulcis watershed (Sardinia, Italy) for the baseline period and compared to future climate projections at the end of the 21st century. The model was forced using data from two Regional Climate Models under the representative concentration pathways RCP4.5 and RCP8.5 scenarios developed at a high resolution over the European domain. River discharge data were used to calibrate and validate the SWAT+ model for the baseline period, while the future hydrological response was evaluated for the mid-century (2006–2050) and late-century (2051–2098). The model simulations indicated a future increase in temperature, decrease in precipitation, and consequently increase in potential evapotranspiration in both RCP scenarios. Results show that these changes will significantly decrease water yield, surface runoff, groundwater recharge, and baseflow. These results highlight how hydrological components alteration by climate change can benefit from modelling high-resolution future scenarios that are useful for planning mitigation measures in agricultural semi-arid Mediterranean regions. [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]