Evaluating agricultural risks in Central Italy by coupling drought risk assessment and agro-hydrological modelling

Higher temperatures, less reliable precipitation patterns, and increased occurrence of extreme events such as drought will significantly affect the sustainability of agricultural systems in the Mediterranean region. A multidisciplinary, participatory approach and a large amount of data are required to unravel the complexity of climate change and properly evaluate the impacts and the possible adaptation strategies. The European countries of the Mediterranean are interesting case studies for these processes since there are numerous institutions active on these topics, collecting a high amount of information. The study area selected for this research is composed of coastal watersheds of Central and Southern Tuscany, Italy. The main objective was to study the impacts of climate change and possible adaptation strategies, with a particular focus on drought. Therefore, a drought risk assessment was performed as a preliminary study to assess the hazard, exposure, vulnerability, and risk of agricultural systems. Free, ready- and easy-to-use data were obtained from public databases to calculate the forty-two indicators that were selected to estimate the various components of risk. Finally, archetype analysis, an emerging approach for identifying recurrent patterns within cases and supporting a context-specific generalization of insights, was used to link the study's results with possible adaptation strategies. Then, the hydrological model SWAT+ was applied to the Ombrone watershed, the largest and most representative of the study area, to estimate impacts on both hydrology and crop production and to evaluate possible agronomic adaptation strategies. By using a hydrological model that includes a module to simulate plant growth, it is possible to study these dynamics at a larger scale than the field scale; this is convenient, especially when dealing with the water resource which is better studied at the watershed level. Data from various public databases were used to set up the model; after that, it was calibrated with monthly streamflow and crop yield of the most representative crops of the area. The future risks for agricultural systems were then analysed by using a multi-model ensemble of EURO-CORDEX projections. The impacts related to the water resource were estimated by evaluating the components of the water balance, while those on agriculture by considering crop yield. Then, possible adaptation strategies such as conservation agriculture and supplemental irrigation were simulated. The presented research demonstrates the importance of integrating multiple data sources and methodologies for the study of climate risks in agricultural systems.