Estimation of the water potential index under dynamic hydromorphological conditions on ephemeral river watersheds

Land morphology and water resources are typically linked through hydromorphological processes, particularly in ephemeral river systems. This study used the Vaigai, Gundar, and Vaippar watersheds in Tamil Nadu, India, as a case study to investigate this link. Land terrain morphology was analysed using the morphometric analysis. Empirical models were developed using morphological parameters to estimate runoff and sediment rates. The water resources, specifically runoff and groundwater, were quantified using an overall water potential index derived from the Multi-Criteria Decision-Making (MCDM) technique. The MCDM technique employed the Analytical Hierarchy Process (AHP) in combination with fuzzy set theory. Seven hydromorphological thematic layers—lithology, lineament density, geomorphology, soil, land use, drainage density, and slope were addressed using the fuzzy-AHP method. Hydrogeological models incoporated available aquifer properties of the subsurface structure, derived from GIS-based weighted overlay and hydrological analysis. A significant finding of morphometric analysis was the identification of high runoff and sediment rates at the smallest sub-watersheds. Furthermore, the water potential index indicated a high surface water (runoff) potential associated with vertisol in the soil and hornblende-biotite gneiss in the lithology, particularly in the Vaippar and Gundar downstream sub-watersheds. The Vaigai and Gundar downstream sub-watersheds had a significant groundwater potential due to their mild slopes and dynamic floodplains. The surface water and groundwater potential indices showed 71% and 87% efficiency, respectively, when compared to runoff from the empirical model and field groundwater recharge. Similar patterns of high potential were observed in downstream watersheds from the hydrogeological models. These findings may help alleviate the depletion of surface and subsurface water resources in sub-watersheds by identifying sites for rainwater harvesting for future climatic scenarios.