Modeling and analysis of effects of precipitation and vegetation coverage on runoff and sediment yield in Jinsha River Basin

This paper focuses on the effects of precipitation and vegetation coverage on runoff and sediment yield in the Jinsha River Basin. Results of regression analysis were taken as input variables to investigate the applicability of the adaptive network-based fuzzy inference system （ANFIS） to simulating annual runoff and sediment yield. Correlation analysis indicates that runoff and sediment yield are positively correlated with the precipitation indices, while negatively correlated with the vegetation indices. Furthermore, the results of stepwise regression show that annual precipitation is the most important factor influencing the variation of runoff, followed by forest coverage, and their contributions to the variation ofrunoffare 69.8% and 17.3%, respectively. For sediment yield, rainfall erosivity is the most important factor, followed by forest coverage, and their contributions to the variation of sediment yield are 49.3% and 24.2%, respectively. The ANFIS model is of high precision in runoff forecasting, with a relative error of less than 5%, but of poor precision in sediment yield forecasting, indicating that precipitation and vegetation coverage can explain only part of the variation of sediment yield, and that other impact factors, such as human activities, should be sufficiently considered as well.

Antecedent snowmelt and orographic precipitation contributions to water supply of Pakistan disastrous floods,2022

In 2022,the Pakistan witnessed the hottest spring and wettest summer in history.And devastating floods inundated a large portion of Pakistan and caused enormous damages.However,the primary water source and its contributions to these unprecedented floods remain unclear.Based on the reservoir inflow measurements,Multi-Source Weighted-Ensemble Precipitation(MSWEP),the fifth generation ECMWF atmospheric reanalysis(ERA5)products,this study quantified the contributions of monsoon precipitation,antecedent snow-melts,and orographic precipitation enhancement to floods in Pakistan.We found that the Indus experienced at least four inflow up-rushes,which was mainly supplied by precipitation and snowmelt;In upper Indus,abnormally high temperature continued to influence the whole summer and lead to large amounts of snowmelts which not only was a key water supply to the flood but also provided favorable soil moisture conditions for the latter precipitation.Before July,the snowmelt has higher contributions than the precipitation to the streamflow of Indus River,with contribution value of more than 60%.Moreover,the snowmelt could still supply 20%-40%water to the lower Indus in July and August;The leading driver of 2022 mega-floods over the southern Pakistan in July and August was dominated by the precipitation,where terrain disturbance induced precipitation account to approximately 33%over the southern Pakistan.The results help to understand the mechanisms of flood formation,and to better predict future flood risks over complex terrain regions.