SPATIOTEMPORAL ANALYSIS OF SOIL MOISTURE AND PRECIPITATION DEPENDENCE OVER INDIA AND EUROPE

Abstract

Anthropogenic climate change has impacted almost all phases of the global water cycle. Growing consensus asserts that extreme precipitation events will only rise in the years to come. However, an increase in extreme precipitation events does not necessarily correspond to higher flood risk. Much onus lies on the antecedent conditions before the storm events. Despite the importance of Soil Moisture (SM) – Precipitation (P) dependence in runoff generation, relatively few studies have unraveled the SM – P dependence. Previous studies were constrained by the direct trivial relationship existing between SM and P, and hence there is a need to understand direction and dynamical interdependency. We employed Event Coincidence Analysis (ECA) to identify and quantify the preconditioning of P extremes by soil moisture (SM) anomalies. In this work, we first disentangled the SM-P dependence patterns for the major river basins of India. High precursor coincidence rate (>45%) was obtained for traditional flash flood-prone areas over India - Ganga river basin, West-flowing rivers of Kutch and Saurashtra including Luni, inland drainage of Rajasthan and Narmada river basin, indicating the robustness of the approach. The trigger coincidence rate reveals strong SM-P coupling over central India. Our results indicate the applicability of ECA in characterizing the spatiotemporal patterns of SM-P dependence over India. The SM-P covariation relationships are established for the major climatic regions covering Europe in the second part of the thesis work. Our results indicate strong seasonal variations in such SM-P preconditioning over Europe. A significant shift in the magnitude and spatial extent of SM-P coupling is seen within the seasons for the various regions. In winter, strong coincidence is seen in western and central Europe, and the coincidence weakens in summer. We further used the timings of annual maximum discharge (Peak flood values) at a catchment scale from a European flood database to investigate how the seasonal and spatial variations in the timings of floods could be interpreted from the SM-P preconditioning perspective. Our results will strengthen existing flood risk assessment initiatives while providing new avenues and implications for a better understanding and proper representation of preconditioned compound flooding events worldwide.