Adapting Rainfall Variability to Flood Risk: A Case Study of the Ghaggar River Basin

Abstract

Floods are the most common natural disasters influenced by climatic variables and anthropogenic activities. Ghaggar is a seasonal river of north-western region of India and this basin has been experiencing moderate to high intensity of floods frequently. The present study aims to find out the impact of the rainfall variability on the flooding scenario of this basin using hydrometeorological data. The rainfall data was collected for 12 stations of the basin. The rainfall and extreme rainfall of the Ghaggar basin was determined using innovative trend analysis which was further validated by Mann-Kendall test. The runoff generated from the average annual rainfall and extreme rainfall in terms of rx1day was determined using SCS-CN method. It is found from the analysis that the southwest monsoon is dominant all over the basin and is the main reason for causing the flood. The rx1day rainfall trend is positive at the stations situated in the middle of the basin which is another factor for causing the flood. It is also found that the runoff generated at the uppermost part of the basin due to heavy rainfall at Kalka and Nahan meteorological divisions when combined with runoff generated from middle of basin is creating the flood situation at middle of the basin. Flood hazard mapping was also carried out for vulnerability analysis and found that the basin area is moderate to highly vulnerable to floods.

Rainfall prediction around Sathanur dam by Naive Bayes classifier, logistic regression models and various classification and regression machine learning techniques

“…There is a seasonal river in the northwestern district of India named Ghaggar, which regularly suffers from reasonable to large concentrations of torrents. Recently, Gorai et al (2021) reported that inconsistency in rainfall influences the flooding situation of this basin. This study was carried out using hydrometeorological data.…”