PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
September 19, 2025Journal of Advanced College of Engineering and Management3 citationsOpen Access

Applicability of the SWAT Model in Medium-Sized River Basins of Nepal: A Case Study of East Rapti and Kankai River Basin

View Full Paper
TSTej Bahadur ShahiRRRam Krishna RegmiYNYogesh Neupane

Key Points

  • Results indicate that the SWAT model can effectively replicate daily hydrological responses, though high flow events are less accurate.
  • Calibration using the SUFI-2 algorithm produced NSE values between 0.83 and 0.94, demonstrating strong predictive performance.
  • The findings highlight the significance of the groundwater parameter, which was the most sensitive in both basins analyzed.
  • Effective use of the SWAT model in these ungauged river basins may enhance water resource planning and management strategies.

Abstract

Hydrological modeling in data-scarce regions faces challenges that hinder effective water resource planning. Adhering to these challenges, numerous ungauged or poorly monitored basins are present in Nepal, which need a suitable methodology to address these problems. This study examines the applicability of the SWAT model in medium-sized, rain-fed perennial river systems: the East Rapti and the Kankai River Basins. Using the SUFI-2 algorithm in SWAT-CUP, calibration was performed with thirty parameters based on observations at Rajaiya (East Rapti) and Mainachuli (Kankai) station. Results showed that SWAT could replicate the hydrological response at daily scale, except the high flow events. The model performed very well at monthly scale with NSE values ranging from 0.83 to 0.94, R² from 0.86 to 0.96, and PBIAS below 15%. In both river basins, the groundwater parameter (GWQMN) was found to be most sensitive. These findings support water resources availability assessment and resource management at basin-scale.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Shahi et al. (2025) studied this question.

synapsesocial.com/papers/68d466c431b076d99fa65e1bhttps://doi.org/10.3126/jacem.v11i1.84540
Ask AI
Helpful
Bookmark
Share
View Full Paper