Gujree et al. (2025) Understanding flood behavior in the Kashmir Himalayas through copula-driven models

Identification

• Journal: Physics and Chemistry of the Earth Parts A/B/C
• Year: 2025
• Date: 2025-11-01
• Authors: Ishfaq Gujree, Shafique Ur Rehman, Joshal Kumar Bansal, Ningsheng Chen, Aijaz Ahmad Reshi, M. Sultan Bhat, Muhammad Atiq Ur Rehman Tariq
• DOI: 10.1016/j.pce.2025.104194

Research Groups

• International Cooperation Center for Mountain Multi-Disasters Prevention and Engineering Safety, Yangtze University, Wuhan, China
• State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
• School of Economics and Management, University of Chinese Academy of Sciences, Beijing, China
• Center of Excellence in Disaster Mitigation and Management, Indian Institute of Technology, Roorkee, India
• Key Lab of Mountain Hazards and Surface Processes, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China
• Department of Computer Science, College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia
• Department of Geography and Disaster Management, University of Kashmir, Srinagar, Jammu and Kashmir, India
• College of Engineering and Science, Victoria University, Melbourne, VIC, Australia
• Institute for Sustainable Industries & Liveable Cities, Victoria University, Melbourne, VIC, Australia

Short Summary

This study introduces a bivariate copula-based framework for flood frequency analysis at three gauging stations along the Jhelum River in Kashmir, India, to determine joint and conditional return periods for flood characteristics, identifying Asham as the most vulnerable station.

Objective

• To introduce and apply a bivariate copula-based framework for flood frequency analysis at three key gauging stations along the Jhelum River in Kashmir, India.
• To determine joint and conditional return periods for flood characteristics (volume, duration, peak) to better understand flood behavior and assess flood severity.

Study Configuration

• Spatial Scale: Jhelum River basin, Kashmir, India, specifically at three gauging stations: Asham, RM Bagh, and Sangam.
• Temporal Scale: Analysis based on annual maximum series of flood characteristics (volume, duration, peak). The specific duration of the historical record is not provided.

Methodology and Data

• Models used: Bivariate copula-based framework; Archimedean copulas (Clayton, Frank, Gumbel) and Student-t copulas for modeling dependence; AIC, Kolmogorov–Smirnov, and Anderson–Darling tests for marginal distribution determination; CDF-based uncertainty analysis.
• Data sources: Historical flood characteristics (volume, duration, peak) extracted using the annual maximum series method from river gauge stations.

Main Results

• Marginal distributions were best fit by Exponential for flood volume, and Gamma for peak and duration.
• Dependence modeling showed Clayton copula best fit Asham pairs, Frank copula fit volume–duration at RM Bagh and Sangam, and Gumbel copula best captured peak–volume relations.
• Joint and conditional return periods were calculated, revealing a significant correlation between flood volume and duration at Asham, and weaker correlations between peak and volume at other stations.
• For a 100-year joint return period:
  • At Asham: Peak flows of 170–200 million cubic metres per day (Mm³/day) with volumes of 1500–2000 million cubic metres (Mm³), or volumes of 1600–2000 Mm³ lasting 30–45 days.
  • At RM Bagh: Peaks of 150–170 Mm³/day with 1000–1200 Mm³ volumes, or 1200–1500 Mm³ over 40–50 days.
  • At Sangam: Peaks of 200–250 Mm³/day with 1000–1300 Mm³ volumes lasting 25–30 days.
• Asham was identified as the most vulnerable station.

Contributions

• First application of copula-based flood frequency analysis across Jhelum River stations, providing both joint and conditional return periods for flood characteristics (volume, duration, peak).
• Demonstrates the practical utility of copula-based models for flood risk management in data-scarce, flood-prone regions like the Kashmir Himalayas.
• Provides specific quantitative thresholds for 100-year joint return periods at key gauging stations, aiding in targeted flood management strategies.

Funding

• Not specified in the provided text.

Citation

@article{Gujree2025Understanding,
  author = {Gujree, Ishfaq and Rehman, Shafique Ur and Bansal, Joshal Kumar and Chen, Ningsheng and Reshi, Aijaz Ahmad and Bhat, M. Sultan and Tariq, Muhammad Atiq Ur Rehman},
  title = {Understanding flood behavior in the Kashmir Himalayas through copula-driven models},
  journal = {Physics and Chemistry of the Earth Parts A/B/C},
  year = {2025},
  doi = {10.1016/j.pce.2025.104194},
  url = {https://doi.org/10.1016/j.pce.2025.104194}
}