Climate-responsive reservoir operation for the environmental flow management of the proposed Nagmati Dam in the Bagmati basin, Nepal

Study region: The study focuses on the Nagmati catchment of the Bagmati River basin, Nepal, with a focus on the proposed Nagmati Reservoir, in the vicinity of the source of the Bagmati River, located on the hills of Kathmandu valley, draining to downstream Gaurighat gauging station. Study focus: This study evaluates whether calibrated operation of a reservoir can sustain downstream environmental flows (E-flows) under historical and future climates. Mean monthly flows were simulated using the Stanford Watershed Model driven by an ensemble of four CMIP6 climate projections under SSP2–4.5 and SSP5–8.5. Using the Ganga E-flow calculator, E-flow thresholds were defined for six Environmental Management Classes (EMCs). A simple spreadsheet-based reservoir operation model was applied across near future (NF), mid future (MF), and far future (FF) periods, and calibrated to sustain E-flow for EMC C (moderately modified flow) condition. New hydrological insights for the region: Projected ensemble means indicate an overall increase in mean monthly inflows across future periods, with stronger increases under the high-emission scenario. The calibrated and validated model demonstrated strong seasonal flow reproduction (Nash–Sutcliffe and R² > 0.81). The mean monthly inflow to the reservoir for historical period (1995–2020) was calculated to be 0.48 m3/s. Under SSP2–4.5, simulated flows increased to 0.69, 0.74 and 0.73 m3/s for NF, MF and FF, respectively. The SSP5–8.5 simulated further increased flow trajectories of 0.62, 0.75, and 0.93 m³/s for NF, MF and FF, respectively. The reservoir operation model maintained a continuous release of 0.52 m³/s, exceeding the planned hydropower allocation of 0.45 m³/s, and met the environmental flow requirements for an EMC C (moderately modified flow). Results highlight that climate-driven increases in monsoon inflow can provide storage and operational flexibility, but intra-seasonal variability and data limitations require adaptive management and further ecological and water-quality assessments.