Adhikari et al. (2026) Identifying ENSO events and their nexus with precipitation and flood dynamics in the Karnali River Basin, Nepal

Identification

• Journal: Natural Hazards
• Year: 2026
• Date: 2026-03-26
• Authors: Tirtha Raj Adhikari, Binod Baniya, Qiuhong Tang, He Li, Suraj Shrestha, Ram Prasad Awasthi, Paul P. J. Gaffney, Yam Prasad Dhital
• DOI: 10.1007/s11069-026-08076-y

Research Groups

• Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
• College of Applied Sciences-Nepal, Environmental Science, Tribhuvan University, Kirtipur, Kathmandu, Nepal
• Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, Kathmandu, Nepal
• Department of Environmental Science, Patan Multiple Campus, Tribhuvan University, Patandhoka, Lalitpur, Nepal
• University of Chinese Academy of Sciences, Beijing, China
• Institute of Fundamental Research and Studies (InFeRS), Kathmandu, Nepal
• Department of Hydrology and Meteorology, Government of Nepal, Kathmandu, Nepal
• School of Geography and Environmental Science, Guizhou Normal University, Guiyang, China

Short Summary

This study investigates the influence of El Niño Southern Oscillation (ENSO) events on precipitation and flood dynamics in Nepal's transboundary Karnali River Basin (KRB) from 1964 to 2020, revealing a strong positive correlation between basin mean precipitation and discharge, and significant river channel shifts during strong ENSO events.

Objective

• To identify ENSO years (El Niño and La Niña) and their impact on river flooding in the Karnali River Basin.
• To demonstrate monsoonal precipitation patterns, frequency of flood forecasts, and the relationship between rainfall and discharge influenced by ENSO events in the KRB.

Study Configuration

• Spatial Scale: Karnali River Basin (KRB), Nepal, a transboundary basin spanning 46,177.3 km² up to the Indian border, including a China-exclusive zone (3,060.1 km²) and the region from the China border to Chisapani hydrological station (42,890 km²). Elevations range from 114 m to 7,746 m above sea level. The study focuses on the downstream area of KRB (hydrological station No. 280, Chisapani).
• Temporal Scale: Daily data from 1964 to 2020 (56 years). Specific ENSO events analyzed include 1983, 2000, 2014 (La Niña years), and 2015 (strong El Niño year).

Methodology and Data

• Models used:
  • HEC-HMS (Hydrologic Engineering Center’s – Hydrologic Modeling System) for discharge estimation and hydrological modeling.
  • HEC-RAS (Hydrologic Engineering Center’s – River Analysis System) for hydrodynamic modeling, 1D and 2D flood analysis, and channel shifting.
  • Soil Conservation Service (SCS) method integrated within HEC-HMS/HEC-RAS for rainfall-runoff evaluation.
  • Gumbel distribution method for flood frequency analysis.
• Data sources:
  • Daily precipitation, temperature, and discharge data (1964–2020) from the Department of Hydrology and Meteorology (DHM), Government of Nepal (47 precipitation stations, 1 hydrological station at Chisapani No. 280).
  • ENSO data (Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Sea Surface Temperature (SST), and pressure data) from NOAA, NASA Giovanni, and JPL Sea Level.
  • Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) (30 m × 30 m) from NASA Earthdata.
  • Data on social incidents, crop failures, water shortages, damage, and loss for 2014 and 2015 from the Disaster Risk Reduction Portal (DDRRP), Home Ministry of the Government of Nepal.
  • Running mean statistical method (3-year running mean) for long-term trend analysis of rainfall, discharge, and temperature.
  • Intensity–Duration–Frequency (IDF) analysis for precipitation.
  • Correlation and regression analysis between discharge and meteorological variables (SST, pressure, surface temperature, precipitation).

Main Results

• A strong positive correlation (0.59) was established between basin mean precipitation and discharge, indicating precipitation as the primary driver of the KRB's hydrology.
• During the monsoon season, a statistically significant relationship was found among precipitation, Sea Surface Temperature (SST), and discharge, with moderate correlations observed in pre-monsoon and post-monsoon seasons.
• The 2015 El Niño event was characterized by below-average annual precipitation (1,190 mm) and monsoon precipitation (747 mm), leading to decreased base flow discharge and lower flood risk.
• Conversely, La Niña years (e.g., 1983, 2000, 2014) exhibited higher annual precipitation (1,413 mm, 1,596 mm, 1,283 mm, respectively) and monsoon precipitation (960 mm, 1,290 mm, 972 mm, respectively), resulting in increased rainfall intensity and expansive inundation.
• Hydrodynamic modeling (HEC-RAS 1D and 2D) identified significant river channel shifts, particularly along the right bank, occurring at 2,000 m intervals during the 2015 ENSO event.
• For the 2015 El Niño event, the maximum one-day precipitation was 217.6 mm within a 24-hour period. Derived IDF storm precipitation values for 1-hour, 2-hour, 3-hour, 6-hour, 12-hour, and 24-hour intervals were 121.3 mm/hour, 76.2 mm/hour, 49.8 mm/hour, 37.0 mm/hour, 22.6 mm/hour, 12.0 mm/hour, and 9.1 mm/hour, respectively.
• The HEC-HMS model accurately simulated peak transboundary discharges; the observed discharge at Chisapani (3,354.0 m³/s) closely matched the simulated peak (3,365.38 m³/s) for the 2015 El Niño event.
• Model validation showed a percentage validity of -0.34% for estimated peak flood discharge compared to observed, and -6.81% for water levels, with an R² value of 0.67 for observed discharge, indicating satisfactory performance.
• The lowest minimum discharge was recorded in 2015, correlating with the strong El Niño event.

Contributions

• Provides a comprehensive basin-level analysis of ENSO's impact on precipitation and streamflow dynamics in the transboundary Karnali River Basin, addressing a gap in existing literature.
• Integrates hydrological (HEC-HMS) and hydrodynamic (HEC-RAS 1D and 2D) models with long-term observed data to simulate and analyze flood events, including river channel shifts, under different ENSO phases.
• Quantifies the relationship between ENSO events, precipitation intensity-duration-frequency (IDF) curves, and flood response, offering specific insights for water resource management and disaster preparedness in a vulnerable Himalayan region.
• Highlights the importance of considering regional climate phenomena and the amplifying effect of mountainous terrain in translating large-scale climate signals (ENSO) into local flood disasters.
• Offers actionable insights for developing robust flood response strategies, early warning systems, and cross-border data sharing, especially in anticipation of future strong ENSO and El Niño events exacerbated by climate change.

Funding

• President’s International Fellowship Initiative (PIFI) visiting scientist grant for the Chinese Academy of Science's (CAS) international talent (2024VEA0001; 2023VCC0001)
• Third Xinjiang Scientific Expedition Program (Grant No. 2021xjkk0806)

Citation

@article{Adhikari2026Identifying,
  author = {Adhikari, Tirtha Raj and Baniya, Binod and Tang, Qiuhong and Li, He and Shrestha, Suraj and Awasthi, Ram Prasad and Gaffney, Paul P. J. and Dhital, Yam Prasad},
  title = {Identifying ENSO events and their nexus with precipitation and flood dynamics in the Karnali River Basin, Nepal},
  journal = {Natural Hazards},
  year = {2026},
  doi = {10.1007/s11069-026-08076-y},
  url = {https://doi.org/10.1007/s11069-026-08076-y}
}