Projection of flood seasonality Changes in the Himalayan Region River due to global warming, taking the Garhwal Himalayas river basin as an example

The impact of a warming climate on snow- and rain-dominated river basins such as the Garhwal Himalayas basin constitutes both a major research challenge and the potential of a severe socio-economic risk. The particular combination at the Garhwal, of hydrometeorological and hydrographic conditions entails merging and superposing two presently distinct seasonal phenomena: snowmelt induced spring floods and rainfall generated summer floods. This study focuses on the projection of seasonality changes in floods in a Garhwal Himalayas basin under global warming. The research in this context is rather uncertain in the proposed study area of the Himalayas, mainly due to the scarcity and unavailability of long-term and high-resolution meteorological data in that region. But after setting up Automatic Weather Stations and Gauge and Discharge sites in the Garhwal region in 2016, the observed data of the past five years lay the basis for understanding the different flood generating regimes. We have analysed the IMD historical maximum monthly rainfall (1901-2020) and maximum temperature (1951-2020) over the study region and found evidence of shifting of maximum rainfall peak backward up to the month of June and maximum temperature peak shifting forward to June (earlier triggering snowmelt induced peak then); if warmer climate scenarios are experienced in future. We also compared the different precipitation datasets available with respect to the observed data at daily, monthly, quarterly and yearly time scales. Those data are crucial for any analysis of possible changes in seasonal hydro-meteorological conditions. We found that the IMD precipitation dataset matches best the observations and the projected climate ensemble of chosen dataset (NEX-GDDP) required significant correction with respect to observed data to counter underestimation. Therefore, we have used quantile-based mapping to adjust the biased projected climate dataset of NEX-GDDP. Also, the corrected projected precipitation of time window 2071-2099 of RCP 4.5 and 8.5 scenarios is found to be magnitude wise higher than that of the corrected historical time window 1971-2000. This clearly indicates the possible occurrences of changes in floods, though we are well aware about the high uncertainties of projected future precipitation conditions. Thus, our analysis poses the potential of bridging the gaps of understanding different flood generating regimes and their future possibilities for better preparedness against natural hazards in the Himalayan region.