An integrated stochastic approach for extreme rainfall analysis in the National Capital Region of India

Abstract

The National Capital Region of India (NCR Delhi) receives around 26 rainy days with majority of short duration high intensity rainfall events. Yet, the city faces severe waterlogging during south-west monsoon, and shortage of water in other seasons due to rapid urbanization and changing hydrological flow patterns. In an uncertain scenario, where spatiotemporal variability of rainfall at local scale is not very well understood, a location-specific robust model applicable for the megacity through interpretation of parameter estimates will improve understanding of extreme rainfall pattern with duration. Identification of the best-fit statistical model for prediction of short duration extreme events is done and parameters of the model are evaluated for different durations. The study finds that the 2-parameter gamma distribution and 3-parameter generalized extreme value (GEV) predict similar return levels of extreme intensity for short durations and short return periods. The shape parameter in GEV and shape and scale parameters in gamma explain the extreme quantile in the distribution responsible for prediction of high magnitude events. The more generic gamma model is robust and applicable at local scale, with pronounced shape parameter variations across durations (1–11.534, 2–8.264, 3–6.609 h). It is concluded that the knowledge of hourly variation in extreme rainfall events will help in informed decision making in this acutely water-stressed region of the world.