Xiang et al. (2026) Estimation of the Hydrological Regime Variability Risk of a Regulated River

Identification

• Journal: Water Resources Management
• Year: 2026
• Date: 2026-01-01
• Authors: Chenguang Xiang, Wei Huang, Chunyu Yao, Le Luo, Rong Zhang, Jing Wang, Pan Yang
• DOI: 10.1007/s11269-025-04412-2

Research Groups

• PowerChina Kunming Engineering Corporation Limited, Kunming, China
• State Key Laboratory of Water Cycle and Water Security, China Institute of Water Resources and Hydropower Research, Beijing, China
• College of Hydrology and Water Resources, Hohai University, Nanjing, China
• College of Water Conservancy and Environment, Three Gorges University, Yichang, China

Short Summary

This study developed an integrated fuzzy-probability-based risk assessment framework to quantify ecological risks from hydrological regime deviations in regulated rivers. Applied to the Pengxi River, the model revealed a significant increase in hydrological risk (from 0.30 to 0.41) post-Three Gorges Reservoir impoundment, primarily driven by altered flow variability and annual mean flow.

Objective

• To develop and apply an integrated, dynamic risk assessment framework that explicitly quantifies deviations from a pre-disturbance natural hydrological baseline using a fuzzy-probability-based model to estimate annual risk time series, requiring only regulated flow magnitude data as input.

Study Configuration

• Spatial Scale: Pengxi River, a tributary of the Three Gorges Reservoir Area, China. The study area covers a total length of 185.626 km with a drainage area of 5225 km². Data was collected from the Xiaojiang Hydrological Station.
• Temporal Scale:
  • Historical baseline (natural flow regime): 1975–1999 (25 years)
  • Study period for risk assessment (regulated flow regime): 2003–2020 (18 years)

Methodology and Data

• Models used:
  • Fuzzy-probability-based risk assessment model (utilizing triangular membership functions for low-flow, high-flow, coefficient of variation, and annual mean flow indices).
  • Mann–Kendall (MK) test for trend detection.
  • Runoff Concentration Degree (RCD) and Runoff Concentration Period (RCP) calculations.
  • Pearson correlation analysis to assess precipitation-runoff relationship.
  • Sobol' method for global sensitivity analysis of risk indices.
• Data sources:
  • Daily runoff and precipitation data from hydrological stations (specifically Xiaojiang Hydrological Station) and statistical yearbooks.
  • Larval fish density monitoring results (for preliminary model validation).

Main Results

• The overall hydrological risk index for the Pengxi River increased by 37%, from an average of 0.30 during the pre-impoundment period (2003–2008) to 0.41 post-impoundment (2009–2020).
• Extreme flow risks decreased post-impoundment: low-flow risk reduced by 41% (from 0.39 to 0.23), and high-flow risk decreased by 43% (from 0.30 to 0.17), indicating a mitigating effect on hydrological extremes.
• Conversely, the Coefficient of Variation (CV) risk increased by 60% (from 0.25 to 0.40), and the Annual Flow (AF) risk increased significantly by 138% (from 0.26 to 0.62) post-impoundment.
• Global sensitivity analysis identified the Variability Index (CVR) as the most sensitive parameter, explaining approximately 58% of the total variance in the risk output (up to 65% including interactions), followed by the Annual Mean Flow Index.
• Pearson correlation between annual precipitation and runoff decreased from 0.842 in the pre-dam period to 0.803 in the post-dam period, highlighting the escalating influence of human regulation on natural hydrological response.
• Preliminary model validation showed a consistent inverse correlation between the high-flow risk index and observed larval fish density, suggesting biological relevance.

Contributions

• Developed a novel, integrated, dynamic, fuzzy-probability-based risk assessment framework that quantifies ecological risks from hydrological regime deviations using only regulated flow magnitude data, addressing a critical gap in comprehensive multidimensional flow characteristic integration.
• Provided a relative risk measure that effectively captures dynamic risks emerging from basin-scale flow regulation, offering a method for evaluating hydrological variability risks without direct ecological endpoint calibration.
• Offered operational insights and specific recommendations for adaptive reservoir management, including spring pulse releases (160–300 m³/s for 3–5 days in May–June), guaranteed dry season flows (≥ 15 m³/s), and mimicking historical seasonal hydrographs to restore flow variability and control magnitude.
• Demonstrated the dualistic nature of reservoir impacts, showing that while regulation can mitigate hydrological extremes (low and high flows), it simultaneously compromises ecological flow diversity by homogenizing the flow regime.

Funding

• National Key R&D Program of China (2023YFC3205901)
• National Natural Science Foundation of China (U2443218)
• Science and Technology Talents and Platform Plan: Technology Innovation Center of Yunnan Province for Digital Water Engineering (202305AK34003)
• Yunnan International Joint R&D Center for Basin-scale Water-Energy-Ecology Regulation (202503AP140045)
• Science and technology project of China Huaneng Group Co., Ltd. (HNKJ22-H107)
• Science and Technology Project of PowerChina Kunming Engineering Corporation Limited (KD-ZDYF2024-085)
• Follow-up Work of the Three-Gorges-Projects Fund (2136703)

Citation

@article{Xiang2026Estimation,
  author = {Xiang, Chenguang and Huang, Wei and Yao, Chunyu and Luo, Le and Zhang, Rong and Wang, Jing and Yang, Pan},
  title = {Estimation of the Hydrological Regime Variability Risk of a Regulated River},
  journal = {Water Resources Management},
  year = {2026},
  doi = {10.1007/s11269-025-04412-2},
  url = {https://doi.org/10.1007/s11269-025-04412-2}
}