Spatial multicriteria analysis for potential water harvesting sites: a compensatory approach to enhance agriculture resilience

Droughts represent a significant challenge in agricultural water management, and climate change is expected to increase the magnitude and duration of these events in many regions of the world due to rising evaporation rates and decreasing precipitation. Small agricultural reservoirs (SmAR) can serve as an effective adaptation strategy by harvesting water during wet periods. However, determining optimal sites for new SmARs requires consideration of various bio-geo-physical and socio-economic factors to identify agricultural areas where they would provide the greatest benefit. This study introduces a spatial Multiple-Criteria Decision Analysis (MCDA) framework to identify optimal locations for SmARs to enhance water resilience in Italy, also assessing irrigation demands under changing climatic conditions. Our methodology incorporates exclusion criteria, such as steep slopes, snow-covered areas, and regions with irrigation districts. Then, the suitability analysis is further refined by considering on-site natural risks and capacities, such as water availability, soil erosion potential, geological fitness, bluewater demand, surface sealing, and accessibility to facilities. The workflow involves cross-validating existing SMARs detected via remote-sensing against the suitability map derived from MCDA, ensuring robust evaluation of current and potential reservoir sites. To this end, we leveraged the national-scale repositories featuring terrain models, climate datasets, hydrology outputs, and land use/land cover data. Our findings highlight key spatial patterns and potential areas for new reservoir sites, providing actionable insights for sustainable water resource management. The MCDA approach demonstrates its capability to integrate diverse datasets and address complex trade-offs, offering a replicable model for other regions facing similar challenges.

ACKNOWLEDGMENTS

This study was carried out within the CASTLE project and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.1 – D.D. n. 104 02/02/2022 PRIN 2022 project code MUR 2022XSERL4 - CUP  B53D23007590006). The research is also carried out within the RETURN – multi-Risk sciEnce for resilienT comUnities undeR a changiNg climate Extended Partnership and received funding from the  European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005).