Analysis of Hydro-climatic extremes in Upper Indus Basin

Abstract

Hindu Kush Himalayan region, a crucial geo-ecological region, comprises one of the world’s most significant mountain systems. The Indus River originates in this region and feeds over 270 million people across six countries, including India. This study analyzed precipitation trends, trends in extremes, and dry and wet spells in the Upper Indus Basin located within latitude 31-37oN and longitude 72-82oE with elevation ranging from 944 m to 8533 m above mean sea level. The analyses of extreme events follow World Meteorological Organization guidelines on analysis of extremes. ETCCDI/CRD climate change indices used to perform dry and wet spell analysis. 1332 station data are analyzed to find the spatial variability throughout the basin. Wavelet coherence and continuous wavelet analysis were on the APHRODITE data with 0.25x0.25 grid resolution daily precipitation (1952-2014). Our study brings out the hidden trend in extreme events in the world’s most susceptible climate region. Nine annual, eight seasonal, and 24 monthly extreme climate indices study calculations are in our research. Then the trend analysis done for the same further part of the study considers wavelet analysis to examine the periodicity and the effect of climate anomalies on the upper Indus Basin. Our results indicate the significant increasing trend in total precipitation for364 stations on an annual basis. Furthermore, the season of a significant increase in precipitation is JJAS, i.e., monsoon. Heavy precipitation for 250 stations and very wet days for 20% of total stations are increasing significantly. Consecutive wet days for 272 stations. The monsoon has an increasing trend of extreme precipitation that increases the wet day of the season, and the dry period's consecutive length is also increased significantly for 137 stations. In July, max 1day precipitation increased significantly for 327 stations. The wavelet coherence analysis significantly correlates with extreme precipitation indices and climate anomalies with different periodicity at different scales.