Wildfire Severity and Post-Fire Hydrological Responses in a Central Himalayan Watershed: Integrating Remote Sensing and SWAT

Wildfires critically alter hydrological regimes in Himalayan watersheds, yet their quantitative impacts remain poorly understood. This study integrates remote sensing–derived burn severity data with the SWAT model to assess postfire hydrological responses in the Central Himalayan Kosi River Basin (2013–2019). Burn severity information derived from Landsat-8 Operational Land Imager (OLI) imagery was used to update leaf area index (LAI) and curve number (CN) parameters within SWAT model to represent fire-induced surface modifications. The model showed satisfactory performance (R² = 0.67 calibration; 0.66 validation). Results indicated that extensive burns, particularly in 2013 and 2016, increased surface runoff by 20–34% and water yield by 13–20%, while reducing evapotranspiration by 17–24% and recharge by up to 7%. The findings highlight that Subbasin 16 experienced repeated moderate-to high-severity burns throughout 2013–2019 and exhibited the most intense and consistent fire effects. This subbasin is hydrologically more sensitive and likely contribute disproportionately to surface runoff and erosion during postfire periods. Therefore, targeted reforestation and soil stabilization efforts should be prioritized to reduce postfire runoff and erosion. These findings collectively emphasize ongoing postfire hydrological changes caused by vegetation loss and soil degradation, highlighting the importance of remote sensing–SWAT integration for postfire watershed management amid rising wildfire frequency.