A Land-Cover Based Approach To The Statistical Analysis Of Precipitation For Integrating Climate In The Assessment Of Land Degradation Vulnerability

The international community has definitively recognized the urgent need for a holistic understanding of land systems in the context of Global Change. Our approach to the integration of climate information in the assessment of sustainability and land degradation vulnerability is based on the analysis of climate data within the geographical constraints imposed by the land cover heterogeneity. This study uses the CHIRPS dataset (Climate Hazards Group InfraRed Precipitation with Station data) to evaluate potential rainfall impacts in Basilicata (Italy), a very complex Mediterranean area. Two indices, accounting for rainfall erosivity and, by contrast, for the local degree of dryness are integrated in a unique rainfall exposition layer. For each land cover, this information layer enables us to detect the areas most exposed to rainfall erosion risk or to water scarcity and drought. This layer can be profitably used within multivariate analyses for the estimation of land degradation vulnerability.