Assessing climate change impacts on flood frequency and magnitude using CMIP6 GCMs: a case study of the Likhu River in eastern Nepal

Abstract

Floods are becoming more severe with climate change disrupting the hydrological cycle, undermining the reliability of the historical flood records for future projections. Despite considerable research on large river basins, small to medium-sized basins like Nepal’s Likhu River remain under-researched, particularly in integrating CMIP6 climate models and Shared Socioeconomic Pathways (SSPs). To the best of the authors’ knowledge, this is the first study to apply the CMIP6/SSP framework to a medium-sized Himalayan basin in eastern Nepal, addressing a critical gap in regional climate-hydrology research. This study aims to quantify the future changes in flood magnitude and frequency of the Likhu River basin by linking CMIP6 climate models with an integrated hydrological-statistical approach. Five selected CMIP6 Global Climate Models (GCMs) under SSP245 and SSP585 scenarios were incorporated to drive a calibrated and validated Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) model, with flood frequency analysis performed using Log-Pearson Type III and Generalized Extreme Value (GEV) distributions. The future floods for each GCM and an ensemble model were evaluated for the three time periods: Near Future (2025–2050), Mid Future (2051–2075), and Far Future (2076–2100). Our findings suggest that a 100-year return-period flood estimated using the historical data may occur more frequently, with recurrence intervals shortening to 5–25 years under future climate change scenarios, highlighting the impact of climate change. Results also point out the variability among the different GCMs and necessitate the use of multiple GCMs to capture the range of uncertainties in flood predictions. These findings demonstrate that current design standards and practices for water-related structures need further modifications and improvements to provide safeguards against future flow conditions as monsoon extremes intensify.