Inferring the spatiotemporal interdependency of soil moisture–rainfall Coincidences over the Indian region

The increased climatic variability in the present scenario intensifies the coupled interaction of land-atmosphere component extremes. Spatiotemporal dependence of soil moisture (SM) and rainfall forms a crucial aspect of this interaction, which contributes to extreme events such as floods. Rainfall creates distinct signatures of SM throughout various soil profile, leading to antecedent SM that influence surface runoff. This underscores the need for a deeper understanding of SM– precipitation preconditioning, particularly in regions of high flood risk. In this study, we investigate the SM-precipitation coupling over India using an event-based, non-parametric Event Coincidence Analysis (ECA) approach. The analysis is carried out for the year 2017, using the surface and root-zone SM (RZSM) data from the Global Land Evaporation Amsterdam Model and corresponding rainfall data from the India Meteorological Department (IMD). Extreme events of SM and rainfall across specific locations inside major river basins within different Indian regions (as per the IMD- based precipitation categories) are marked using the 95 ^th percentile threshold. The strength of coincidence between the two event-series was subsequently inferred using the two statistical ECA parameters: precursor (r _p) and trigger (r _t) coincidence rate. Results reveals a strong directional relationship of SM event that triggers rainfall extremes over the southern peninsular and central India, as indicated by their high trigger rate (r _t =0.842 to 0.895) and moderate precursor rate (r _p = 0.526 to 0.579). in contrast, northern India (both eastern and western region), exhibits a low EC (0.263–0.368), indicating an inconsistent time lag between the two extreme event series. Additionally, the RZSM demonstrates a comparatively moderate triggering and preconditioning effect on precipitation extremes in most of the regions, except for the Northwest, which reveals a lower coincidence value. Notably, this observation was revealed in one of the key locations within the Yamuna River basin which showed an identical r _p and r _t values of 0.053. Altogether, the present study enhances our understanding of SM-precipitation dynamics, offering critical insights for flood risk assessment. The findings of this study significantly contribute to disaster management over one of the globally recognized flood risk regions.