Exploring GIS-based modeling for assessing social vulnerability to Ganga Riverbank erosion, India

Abstract

Riverside communities along the lower Ganges in India face significant threats like riverbank erosion, floods, and climate change impacts. Despite extensive research on riverbank erosion in the region, a key gap remains in understanding how erosion and climate change jointly affect local communities. Additionally, research prioritizing village-level studies and strategies is urgently needed for effective management of the study area. This study aimed to compute a GIS-based Social Vulnerability Index (SociVI) by assessing 10 components and 31 sub-components at the village level. We used spatial analysis techniques like Moran's I and Getis-Ord G∗ to identify hotspots and clustering patterns among variables and SociVI values. Principal component analysis (PCA) and multi-correlation statistics determined the most significant component. Our fieldwork involved surveying 1641 households, 547 focus group discussions, and 12 key informant interviews across 547 villages. The SociVI analysis revealed that residents on the left bank of the river, particularly in the upper section of the Farakka barrage, and those living in the char villages were highly susceptible to social vulnerability. Scores ranged from 0.67 to 0.88, with 34 villages (6.22%) on the left bank and 8 villages (1.46%) on the right bank showing notably high SociVI values. Furthermore, our hot spot analysis identified 51 villages (9.32%) as hot spots with 99% confidence, 7.13% of which were located on the left bank and 2.19% on the right bank. According to the PCA results, demographics (PC1), riverbank calamities (PC2), displacement of households (PC3), and climatic variability (PC4) emerged as the most significant factors. This study's findings are crucial, highlighting critical areas and villages requiring focused efforts to reduce local vulnerability and bolster adaptation capacities amid these challenges.