Modeling of water scarcity for spatial analysis using Water Poverty Index and fuzzy-MCDM technique

The study focuses on the spatial distribution of water scarcity and its influencing factors that affect sustainable livelihoods at the provincial scale. However, the limitation of spatial heterogeneity representation makes it difficult to reveal the complexity of phenomena in practice. Therefore, to solve this problem, this study aims to develop a Water Poverty Index (WPI) from a set of water-related indicators as a comprehensive quantitative approach that integrates the expert knowledge and physical data of water scarcity assessment. With the support of the Fuzzy-Analytic Hierarchy Process (Fuzzy-AHP), GIS-based modeling in WPI measurement for Nghe An province, Vietnam, is done from 05 components with 15 corresponding criteria. The weighted result with high accuracy illustrates that annual precipitation plays the highest role in the hierarchy level (WR1 = 0.279); by contrast, the weight of criterion for children mortality under 05 years is the lowest role (WC2 = 0.005). The spatial analysis results show that 13.34% (2135.68 km2) of the study area is at very high risk of water poverty, while most of them (26.28%) are located in the east and southeast regions with a high-risk level (4221.67 km2). The medium, low, and very low-risk levels correspond to 19.8% (3168.47 km2), 22.13% (3540.98 km2), and 18.329% (2932.47 km2). The differences in the level of WPI values form a spatial divergence for water scarcity with different dominant factors. This approach could provide a useful multi-level risk assessment for local planning as well as water resource management in the future.