A document by Poulomi Ganguli. Click on the document to view its contents.

A document by Poulomi Ganguli. Click on the document to view its contents.

A document by Poulomi Ganguli. Click on the document to view its contents.

Compound flooding, characterized by the co-occurrence of multiple drivers is a cause of concern in many world river basins. High river flows accompanied by high rain events are responsible for severe flooding events. Many studies in the recent past have analysed rain and river-flow dominated compound floods. In this study, we assessed the rain and river-flow induced compound flooding scenarios in a large tropical river basin, the Mahanadi River basin, located in eastern India. Since, many high floods have occurred in the past decade in the Mahanadi River basin, we analysed how the historical flood (in the year 2000) will unfold in a projected climate change scenario (in the year 2080) under RCP8.5. We used the bias-corrected hydro-meteorological data of nine Global Climate Models (GCMs) as input forcings to a hydrologic model MIKE11 NAM-HD to simulate the river flows at the head of the Mahanadi delta. The mean areal rainfall for the delta region and the river-flow simulations are forced into a calibrated and validated MIKE FLOOD model to simulate the historical and projected flood inundations. Comparison of the compound floods with the rain-induced and streamflow-induced floods indicate increased compound flooding in the projected scenario. Both historical and projected floods are found to be predominantly influenced by the river flows. Also, both the areal extent and flooding depth are found to be increasing the projected period as compared to the historical counterpart.

Understanding onset of droughts and its potential linkage to resulting responses like severity (deficit volume) is crucial for providing timely information related to drought sectors including the cultivation planning and monitoring crop productivity. Using high-quality daily observed streamflow records from 82 medium-to-large sized catchments over (tropical) peninsular India, we show that the variability in onset timing drives the severity of hydrological droughts. The strength of onset timing-severity relationships using observed records indicate seasonality of rainfall and catchment characteristics mainly modulate hydrological drought responses in peninsular India, which is not readily apparent from land-surface model simulations. The observed trend for mean onset of drought depicts delayed occurrence for more than half of the catchments. Around one-third of the catchments shows a stronger non-linear significant dependency (>0.7) between severity and onset of drought. The findings of the study highlight the need for accounting feedback between drought onset and severity and their concurrent changes for seasonal-to-sub-seasonal predictability of droughts; and contributes to discussions on building resilience to extreme droughts in a changing climate.