Hydrological Modeling of Extreme Rainfall Events in the Gandaki River Basin Using HEC-HMS

Hydrological modeling is categorized into lumped, semi-distributed, and distributed models, and with the semi-distributed model dividing a basin into sub-basins to estimate runoff and compute stream flow at the outlet. This study applies the semi-distributed HEC-HMS model to assess the impact of channel geometry on hydrological modeling in the Narayani River Basin, Nepal. Different channel geometries were simulated to analyze their effects on stream flow. Results indicate that the trapezoidal channel section provides the most accurate representation, closely matching observed discharge. The model was calibrated using 2004-2005 rainfall-runoff data and validated with 2006 data. The findings suggest that trapezoidal channels are the most effective for flood forecasting and continuous simulation. Future research should incorporate high-resolution data sets to enhance accuracy and improve model performance.

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Publication Details

Journal
Geographical Journal of Nepal
Published
2025-03-26
DOI
https://doi.org/10.3126/gjn.v18i1.77067
Primary Topic
Hydrological Forecasting Using AI
Type
article
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article

Hydrological Modeling of Extreme Rainfall Events in the Gandaki River Basin Using HEC-HMS

Narayan Prasad Gautam
Geographical Journal of Nepal
Hydrological Forecasting Using AI
article

Hydrological Modeling of Extreme Rainfall Events in the Gandaki River Basin Using HEC-HMS

Narayan Prasad Gautam
article en

Abstract

Hydrological modeling is categorized into lumped, semi-distributed, and distributed models, and with the semi-distributed model dividing a basin into sub-basins to estimate runoff and compute stream flow at the outlet. This study applies the semi-distributed HEC-HMS model to assess the impact of channel geometry on hydrological modeling in the Narayani River Basin, Nepal. Different channel geometries were simulated to analyze their effects on stream flow. Results indicate that the trapezoidal channel section provides the most accurate representation, closely matching observed discharge. The model was calibrated using 2004-2005 rainfall-runoff data and validated with 2006 data. The findings suggest that trapezoidal channels are the most effective for flood forecasting and continuous simulation. Future research should incorporate high-resolution data sets to enhance accuracy and improve model performance.

Geographical Journal of NepalVol. 18(1)
Tribhuvan University (NP)
Openalex Percentile: Top 94%
Hydrological Forecasting Using AI
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