Estimation of Probable Maximum Flood from Probable Maximum Precipitation in the Kaligandaki River Basin, Nepal

The Kaligandaki River Basin in Nepal is highly vulnerable to flooding due to significant variability in precipitation. This study estimates the Probable Maximum Flood (PMF) from Probable Maximum Precipitation (PMP) utilizing the HEC-HMS hydrological model. The basin was segmented into eight sub-basins, and PMP was determined using the Hershfield method, with values ranging from 368 mm to 816 mm. The HEC-HMS model was calibrated and validated using daily data from 1989 to 2017, demonstrating satisfactory performance across most sub-basins. The simulated PMF values were 4,590 m³/s, 3,640 m³/s, and 45,548 m³/s for the Mayagdhi, Modi, and Kaligandaki basins, respectively. When compared to floods with a 10,000-year return period, the PMF was approximately two to three times greater in magnitude. These findings offer a framework for PMP/PMF estimation in Nepalese rivers, thereby aiding in the design of flood-resilient infrastructure.The Kaligandaki River Basin in Nepal faces significant flood risks due to its highly variable precipitation patterns. This study employs a comprehensive approach to estimate the Probable Maximum Flood (PMF) using the Probable Maximum Precipitation (PMP) and the HEC-HMS hydrological model. By dividing the basin into eight sub-basins and applying the Hershfield method, researchers determined PMP values ranging from 368 mm to 816 mm. The model’s calibration and validation process, utilizing daily data spanning nearly three decades (1989-2017), demonstrated satisfactory performance across most sub-basins, lending credibility to the results. The study’s findings reveal substantial PMF values for the Mayagdhi, Modi, and Kaligandaki basins, at 4,590 m³/s, 3,640 m³/s, and 45,548 m³/s, respectively. These estimates are particularly noteworthy when compared to floods with a 10,000-year return period, as the PMF values are approximately two to three times greater in magnitude. This significant difference underscores the importance of considering extreme flood scenarios in infrastructure planning and design. By providing a robust framework for PMP/PMF estimation in Nepalese rivers, this research contributes valuable insights for developing flood-resilient infrastructure, potentially mitigating the impact of extreme flooding events on local communities and ecosystems in the Kaligandaki River Basin and similar regions.