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Most climate projections predict that average surface temperature and precipitation variability will increase at the global scale, triggering hydrological variations and alterations in river flows and groundwater table levels. Climate change impacts on freshwater resources are likely to affect freshwater availability and quality and by extension, the ability of water systems to support natural processes and ensure population needs. As a result, the vulnerability of water systems to adverse conditions (e.g. water shortages, overexploitation, and quality deterioration) is intensified; hence, methods and tools for vulnerability assessment and identification of adaptation measures are necessary. This paper proposes a comprehensive framework for the assessment of water systems’ vulnerability to adverse water related conditions and the identification of potential adaptation strategies. The proposed methodology is applied in the four study site areas of the FP7 COROADO project (selected river basins in Argentina, Brazil, Chile, and Mexico), and an indicator-based framework is adopted, expressing natural, physical, socio-economic, and institutional attributes of the examined areas. The vulnerability assessment was conducted following a disaggregated analysis (use of proxy indicators). The vulnerability profiles of the four study sites were formulated, describing the factors shaping vulnerability and the aspects that need improvement. Additionally, the anticipated contribution of alternative strategies to vulnerability mitigation was assessed. The systems’ response to alternative strategies (what-if scenarios) was analyzed following an aggregated analysis (estimation of an overall vulnerability index). [ABSTRACT FROM PUBLISHER]

Soil degradation and desertification processes in the Mediterranean basin reflect the interplay between environmental and socioeconomic drivers. An approach to evaluate comparatively the multiple relationships between biophysical variables and socioeconomic factors is illustrated in the present study using the data collected from 586 field sites located in five Mediterranean areas (Spain, Greece, Turkey, Tunisia and Morocco). A total of 47 variables were chosen to illustrate land-use, farm characteristics, population pressure, tourism development, rainfall regime, water availability, soil properties and vegetation cover, among others. A data mining approach incorporating non-parametric inference, principal component analysis and hierarchical clustering was developed to identify candidate syndromes of soil degradation and desertification risk. While field sites in the same study area showed a substantial similarity, the multivariate relationship among variables diverged among study areas. Data mining techniques proved to be a practical tool to identify spatial determinants of soil degradation and desertification risk. Our findings identify the contrasting spatial patterns for biophysical and socioeconomic variables, in turn associated with different responses to land degradation. [ABSTRACT FROM AUTHOR]