Exploring possibilities to reduce climate change induced flood risk and crop production losses using hydrodynamic modelling

Accounting for nearly 30% of all the losses due to natural disasters, flood emerges as one of the most havoc-creating extreme events in the world. Recently, as an adverse effect of climate change, the tropical river basins have witnessed recurring extreme flood events leading to significant devastation of agricultural production. We have studied the climate change-induced flood risk associated with crop damage in a paddy crop-dominated tropical river basin in India. We have considered a 50-year return period design flood and three (2010-2039, 2040-2069 and 2070-2099) future scenarios in the most extreme representative concentration pathway 8.5 conditions in a hydrodynamic modelling framework as the test case. Nine different Global Climate Models (GCMs) are used here. Analysis of the three best performing (HadGEM2-AO, IPSL-CM5A-MR and MIROC-ESM-CHEM) GCM data-driven flood inundation depth and extent, and the associated net loss/benefit from the cultivation of normal rice variety indicates increased flood risk in the projected scenarios as compared to the historical period. In contrast to high water level, occurrence of comparatively low inundation depth but for a longer period of time is found to increase the flood vulnerability of the paddy crops in the future projected time frames. As a significant alteration in the cultivation pattern is highly subjective on the adoption/willingness of the local farmers, we suggest an alternate rice planning, considering cultivation of an alternate rice variety as a probable adaptation strategy to minimize climate change induced flood risk. Considering the near-future period (2010s) and the MIROC-ESM-CHEM model, our study shows that cultivation of shallow, medium deep or deep water rice varieties in high flood inundation areas can reduce the very high flood risk from about 35% to 17%. The methodology adopted herein encourages the application of hydrodynamic modelling in analyzing projected flood-agriculture risk and paves avenues for more novel scientific research.