Pathania et al. (2025) Analysing flood resilience in the anthropocene: Integrated insights from a multi-scalar extreme event in the himalayas

Identification

• Journal: The Science of The Total Environment
• Year: 2025
• Date: 2025-12-30
• Authors: Ashish Pathania, Saran Raaj, Gopal Krishan, Dan Lapworth, Bentje Brauns, Alan MacDonald, Vivek Gupta, Donald John MacAllister
• DOI: 10.1016/j.scitotenv.2025.181289

Research Groups

• Indian Institute of Technology Mandi, Himachal Pradesh, India
• National Institute of Hydrology Roorkee, Uttarakhand, India
• British Geological Survey, United Kingdom

Short Summary

This study analyzes the hydrometeorological drivers, dam operations, hydrological responses, and socioeconomic impacts of the August 2023 Punjab floods. It found that antecedent July rainfall increased flood susceptibility, and controlled releases from Pong Dam significantly reduced downstream population exposure, though vulnerable groups faced disproportionate impacts.

Objective

• To analyze the multifaceted drivers, including hydrometeorological conditions, dam operations, hydrological responses, and socioeconomic impacts, of the August 2023 extreme flood event in Punjab, India.

Study Configuration

• Spatial Scale: Punjab, India, specifically the region affected by the August 2023 floods downstream of the Pong Dam.
• Temporal Scale: July–August 2023, focusing on antecedent rainfall in July and the flood event in August.

Methodology and Data

• Models used: HEC-RAS hydrodynamic modeling, Genetic Algorithm (GA) for reservoir operation optimization.
• Data sources: Spatiotemporal meteorological analysis data, high-resolution demographic data (2011 village-level census data).

Main Results

• Heavy and very heavy rainfall events in July significantly elevated antecedent soil moisture levels, increasing the region's flood susceptibility in August despite seasonal rainfall deficits.
• Controlled releases from Pong Dam reduced downstream population exposure by approximately 78.7 % compared to unregulated conditions.
• A deterministic population exposure assessment revealed disproportionate impacts on vulnerable groups: flood exposure rose by approximately 49 % among children (0–6 years), 46 % among women, and 47 % among non-working populations between August 15–17.
• Genetic Algorithm-based optimization with a piecewise penalty function improved the balance between flood mitigation and water conservation.

Contributions

• Provides an integrated, multi-scalar analysis of an extreme flood event, combining hydrometeorological, dam operation, hydrological, and socioeconomic perspectives.
• Quantifies the critical role of dam operations in mitigating flood impacts and reducing population exposure during extreme events.
• Identifies and quantifies the disproportionate flood impacts on vulnerable socioeconomic groups, highlighting specific demographic vulnerabilities.
• Demonstrates the utility of Genetic Algorithm-based optimization for balancing flood control and water storage needs in reservoir management.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Pathania2025Analysing,
  author = {Pathania, Ashish and Raaj, Saran and Krishan, Gopal and Lapworth, Dan and Brauns, Bentje and MacDonald, Alan and Gupta, Vivek and MacAllister, Donald John},
  title = {Analysing flood resilience in the anthropocene: Integrated insights from a multi-scalar extreme event in the himalayas},
  journal = {The Science of The Total Environment},
  year = {2025},
  doi = {10.1016/j.scitotenv.2025.181289},
  url = {https://doi.org/10.1016/j.scitotenv.2025.181289}
}