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<p>Runoff is a core component of the hydrological cycle and a key indicator for water resources assessment. Thus, elucidating its evolution patterns is critical for sustainable water management in cold regions. This study utilized monthly runoff series from 1960 to 2022, with 1960–1962 as the warm-up period, and divided the remaining study period into 1963–1990 and 1991–2022. The runoff simulation performance during these two periods was systematically evaluated, and optimal model parameters were employed to quantitatively assess watershed water conservation capacity and project future runoff changes under four climate scenarios. The main findings are as follows: (1) The R², NSE, and KGE coefficients for runoff simulations all exceeded 0.75 in both periods, indicating satisfactory model performance. On a monthly scale, flood season runoff was significantly higher than non-flood season runoff, with the observed peak shifting from July (1963–1990) to August (1991–2022); (2) The long-term average water conservation capacity was 84.94&#xa0;mm, corresponding to a rate of 20.46%, with precipitation identified as the dominant influencing factor; (3) Compared with the historical period, the multi-year average runoff increased under all four climate scenarios, with a significant increase projected under SSP5-8.5, and dry season runoff changes were more pronounced than those in the wet season. These projected future runoff results provide a scientific basis for quantifying the impacts of climate change on water resources and support the development of adaptive regulation and mitigation strategies.</p>

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Runoff Simulation and Prediction with Water Conservation Capacity Assessment in a Cold Region Watershed

  • 期刊论文

  • 发表日期：

    2026年5月30日

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  • Yunying Wang,
  • Zongxing Li,
  • Juan Gui,
  • Xiaoying Liu,
  • Lanping Si

摘要

Runoff is a core component of the hydrological cycle and a key indicator for water resources assessment. Thus, elucidating its evolution patterns is critical for sustainable water management in cold regions. This study utilized monthly runoff series from 1960 to 2022, with 1960–1962 as the warm-up period, and divided the remaining study period into 1963–1990 and 1991–2022. The runoff simulation performance during these two periods was systematically evaluated, and optimal model parameters were employed to quantitatively assess watershed water conservation capacity and project future runoff changes under four climate scenarios. The main findings are as follows: (1) The R², NSE, and KGE coefficients for runoff simulations all exceeded 0.75 in both periods, indicating satisfactory model performance. On a monthly scale, flood season runoff was significantly higher than non-flood season runoff, with the observed peak shifting from July (1963–1990) to August (1991–2022); (2) The long-term average water conservation capacity was 84.94 mm, corresponding to a rate of 20.46%, with precipitation identified as the dominant influencing factor; (3) Compared with the historical period, the multi-year average runoff increased under all four climate scenarios, with a significant increase projected under SSP5-8.5, and dry season runoff changes were more pronounced than those in the wet season. These projected future runoff results provide a scientific basis for quantifying the impacts of climate change on water resources and support the development of adaptive regulation and mitigation strategies.