Climate-driven sedimentation projections using spatially distributed sediment delivery modeling for the Kulekhani Reservoir, Nepal

ABSTRACT The Kulekhani Reservoir is Nepal's sole seasonal storage hydropower project and has accumulated sediment continuously since commissioning in 1982 without a single flushing operation. This study presents the first integration of the InVEST Sediment Delivery Ratio (SDR) model, the TerrSet Land Change Modeler (LCM), and a 10-member bias-corrected CMIP6 ensemble to deliver a unified, long-term sedimentation assessment for a Himalayan storage reservoir. The InVEST SDR model achieved a cumulative percent bias of −4.4% and explained 60% of annual variance. The linear regression of annual rainfall-sediment (R2 =0.94) indicates precipitation to be the dominant factor in interannual sediment variability. The land cover change analysis showed forest cover expansion from 59 to 71% between 2000 and 2021, with projections reaching 80% in 2031 and 86% in 2041. Yet, projected scenarios' intensifying monsoon rainfall is expected to override land-cover benefits. The reservoir storage is projected to decline to 52.29 Mm3 (SSP245) and 51.08 Mm3 (SSP585) by 2050, with decreasing trap efficiency. These results illustrate the need for active sediment management measures like check-dam construction and turbine protection to sustain hydropower productivity irrespective of watershed rehabilitation alone.