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<p>Reliable flood forecasting in mountainous watersheds remains challenging due to complex topography, variable climatic conditions, and diverse runoff generation mechanisms. Widely used hydrological models such as HEC-HMS, TOPMODEL, Xinanjiang (XAJ), Dahuofang (DHF), and API often show limited cross-climatic transferability, reducing their reliability for regional flood management. This study presents a novel Spatiotemporal Variable Source-Mixed Runoff (SVSMR) model with improved cross-climatic adaptability and mechanistic process representation for reliable flood forecasting mountainous watersheds. The SVSMR model’s performance was evaluated in 15 mountainous watersheds (21.3–427.1&#xa0;km²) spanning semi-arid to humid climatic zones, and compared with the five established hydrological models. Results show that the SVSMR model outperforms all other models in flood simulation across all four evaluation metrics (PBIAS, RMSE, r, and NSE). The SVSMR model exhibits strong cross-climatic adaptability, achieving ‘Good’ agreement between observations and simulations, with success rates of 76.6% in semi-arid/semi-humid regions and 89.0% in humid regions, effectively addressing the main limitations of conventional models. Parameter sensitivity analysis revealed distinct regional patterns: routing and surface runoff parameters were most influential in semi-arid/semi-humid regions, whereas interflow parameters dominated in humid regions. Runoff component analysis further indicated climate-dependent mechanisms, with infiltration-excess runoff prevailing in semi-arid/semi-humid watersheds and saturation-excess runoff coupled with rapid interflow dominating in humid watersheds.</p>

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Enhancing Flood Prediction in Mountainous Watersheds across Diverse Climates Using Spatiotemporal Variable Source-Mixed Runoff Model

  • 期刊论文

  • 发表日期：

    2026年1月3日

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  • Xuantao Zhao,
  • Aidi Huo,
  • Changjun Liu,
  • Xia Jia,
  • Lei Wen,
  • Qi Liu

摘要

Reliable flood forecasting in mountainous watersheds remains challenging due to complex topography, variable climatic conditions, and diverse runoff generation mechanisms. Widely used hydrological models such as HEC-HMS, TOPMODEL, Xinanjiang (XAJ), Dahuofang (DHF), and API often show limited cross-climatic transferability, reducing their reliability for regional flood management. This study presents a novel Spatiotemporal Variable Source-Mixed Runoff (SVSMR) model with improved cross-climatic adaptability and mechanistic process representation for reliable flood forecasting mountainous watersheds. The SVSMR model’s performance was evaluated in 15 mountainous watersheds (21.3–427.1 km²) spanning semi-arid to humid climatic zones, and compared with the five established hydrological models. Results show that the SVSMR model outperforms all other models in flood simulation across all four evaluation metrics (PBIAS, RMSE, r, and NSE). The SVSMR model exhibits strong cross-climatic adaptability, achieving ‘Good’ agreement between observations and simulations, with success rates of 76.6% in semi-arid/semi-humid regions and 89.0% in humid regions, effectively addressing the main limitations of conventional models. Parameter sensitivity analysis revealed distinct regional patterns: routing and surface runoff parameters were most influential in semi-arid/semi-humid regions, whereas interflow parameters dominated in humid regions. Runoff component analysis further indicated climate-dependent mechanisms, with infiltration-excess runoff prevailing in semi-arid/semi-humid watersheds and saturation-excess runoff coupled with rapid interflow dominating in humid watersheds.