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Watershed Planning within a Quantitative Scenario Analysis Framework
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A multi-source data-driven framework for probabilistic flood risk assessment using cascade machine learning models:

Yan Lu1,2, Ying Huang3, Xiaoling Liu4,5

  • 1Research Center for Pacific Island Countries, Liaocheng University, Liaocheng, 252000, Shandong, China. luyan@lcu.edu.cn.

Scientific Reports
|July 22, 2025
PubMed
Summary
This summary is machine-generated.

Climate change is increasing flood risks in China's Sichuan Basin. Projections show a doubling of extreme flood events by century's end, necessitating urgent adaptation and mitigation strategies.

Keywords:
Climate changeFlood frequency analysisPhysics-informed sequential modeling frameworkSVM-based machine learning modelSichuan basin

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Area of Science:

  • Climate Science
  • Hydrology
  • Environmental Science

Background:

  • Global climate change is increasing the frequency and severity of extreme weather events, leading to more frequent and severe flood disasters.
  • Urbanization contributes to increased impervious surfaces, exacerbating flood risks.
  • The Sichuan Basin, China's most flood-vulnerable region, faces recurrent catastrophic flooding.

Purpose of the Study:

  • To quantify climate-driven changes in flood recurrence intervals in three key hotspots within the Sichuan Basin.
  • To assess how climate change and anthropogenic factors influence flood disaster probabilities in this monsoon-dominated region.

Main Methods:

  • Utilized Coupled Model Intercomparison Project Phase 6 (CMIP6) projections under various Shared Socioeconomic Pathways (SSPs) scenarios.
  • Developed a physics-informed, process-based modeling framework incorporating statistical downscaling and extreme value adjustments.
  • Conducted flood frequency analysis to understand changes in hydrological regimes.

Main Results:

  • Projected temperature increase of approximately 1.7°C and a 9.4% increase in precipitation by the end of the century.
  • Anticipated doubling of the likelihood of extreme flood disaster events in the study area.
  • Demonstrated amplification of extreme event probabilities due to anthropogenically modified hydrological regimes.

Conclusions:

  • The Sichuan Basin faces a significantly heightened risk of extreme flood disasters due to climate change.
  • Robust climate adaptation and disaster mitigation strategies are imperative for the region.
  • The study highlights the critical need for integrated approaches to manage flood risks in vulnerable basins.