Palaeoflood hydrology of the fluvial continental records of western India: A synthesis

Abstract

Palaeoflood hydrology has emerged as an important tool to infer quantitative and qualitative aspects of ungauged floods based on their physical evidence. Palaeoflood studies in India have largely been undertaken in the rivers of Peninsular India, western India, Ganga plains and the Himalayas to determine the magnitude and age of extreme floods and their connection to variations in the monsoon intensity. Usually, the alluvial domains are unfavourable for the occurrence and preservation of flood deposits and related discharge estimation. However, the alluvial rivers of western India owing to their semi–confined banks comprising late Pleistocene sediments provide an opportunity for investigating both, the high magnitude flood events as well as average flow conditions. In this synthesis we concisely review the recent palaeohydrological studies in western India in terms of flood magnitude, occurrence of extreme events and its relation to the southwest monsoon variability over various time scales. Based on palaeo–fluvial reconstructions, the sedimentation pattern during late Pleistocene appears to be related to changes in channel gradient and the water surface width rather than to discharge variability. On the other hand, the aggradation in channels during early Holocene was largely controlled by the huge sediment influx and the incision that followed was in response to the increase in the discharge and competence of the river flow. The slackwater records from the bedrock channels have revealed that the large magnitude flood events occurred during wet climate phases during the last two millennia. A clustering of high magnitude events at climatic transitions and arid periods during mid–late Holocene has been surmised. Further the flood associated deposits delimited within Quaternary fluvial landforms and channel morphology are vital as these allow quantification of past flood discharges, velocities and stage levels and thus improve the future flood predictions.