This research explores a new methodological framework that blends the TOPSIS (technique for order of preference by similarity to ideal solution) and Mahalanobis Distance methods, allowing for the prioritization of nine major watersheds in China based on the integration of multi-dimensional drought indicators. This integrated approach offers a robust prioritization model by accounting for spatial dependencies between indices, a feature not commonly addressed in traditional multi-criteria decision-making applications in drought studies. This study utilized three drought indices—the Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Health Index (VHI), and Palmer Drought Severity Index (PDSI). Over years of significant drought prevalence, three types of droughts occurred simultaneously across various watersheds in multiple years, particularly in 2001, 2002, 2006, and 2009, with respective counts of 16, 17, 19, and 18 concurrent episodes. The weights derived from Shannon’s entropy emphasize the importance of the Potential Drought Severity Index (PDSI) in evaluating drought conditions, with PDSI-D (drought duration) assigned the highest weight of 0.267, closely followed by VHI-D (Vegetation Health Index under drought conditions) at 0.232 and SPEI-F (drought frequency) at 0.183. The results demonstrated considerable spatial variability in drought conditions across the watersheds, with Watersheds 1 and 4 exhibiting the highest drought vulnerability in terms of meteorological and agricultural droughts, while Watersheds 6 and 3 showed significant resilience to hydrological drought after 2012. In particular, the severe meteorological drought conditions at Watershed 1 highlight the urgent need for rainwater harvesting and strict water use policies, and in contrast, the conditions at Watershed 4 show the need for the modernization of irrigation to mitigate agricultural drought impacts. This integrated framework allows for targeted drought management solutions that directly relate to the specific contexts of the watersheds, while being more conducive to planning and prioritizing resource allocations for regions facing the highest drought vulnerability.
