Drought Risk in the Mahanadi River Basin: A Multidimensional Approach for Integrated Urban-Rural Drought Management Strategies

Droughts are one of the most spatially complex geohazards, having a significant impact on the economic status of any region. To mitigate drought risks, a comprehensive drought management plan is required, and the first step toward that goal is to assess the various aspects of drought risks in the preparation of a drought risk map. To produce an integrated drought risk map for the Mahanadi River basin, India, the current study combines geospatial methodologies with the Analytical Hierarchy Process (AHP) technique to assess various dimensions, viz., hydrological, meteorological, agricultural, and socio-economic drought risk in the region in view of integrated rural-urban management strategies. A total of 17 criteria from different aspects were taken into consideration in different groups. Each parameter was given its own spatial layer, which was then normalized by the AHP eigenvector. The weighting of each factor was measured by constructing pair-wise comparison matrices using AHP. For validation, we used a receiver operating characteristic (ROC) curve, which indicates both methods are very useful in drought risk assessment. The five drought risk classes were finally categorised across the Mahanadi River basin, using the weighted overlay approach to create multi-dimensional and integrated drought risk maps. The results showed that the districts like Raipur, Bilaspur, Durg, and Ragnandgaon faced extreme drought conditions. The combining assessments of agriculture, water resources, socioeconomic factors, and weather patterns reveal varying levels of risk across the region. According to the findings, 22.01% of the region is vulnerable to extreme drought, and 31.64% of the area is suffering from severe drought. Furthermore, statistical criteria such as the area under the Receiver Operating Characteristics curves were utilized to validate the method, which indicates about 72.4% accuracy of the model output. The results indicate that the technique used for identifying the region's susceptibility to drought is effective, which will help planners develop strategies for mitigating drought.