融雪径流模型及变化响应机制研究综述

    Review on snowmelt runoff model and variation response mechanism

    • 摘要: 融雪径流作为水循环的关键环节,其变化对水资源分布、流域生态具有重要影响。为深入理解其在雪水文过程中的作用,从模型构建和改进、不确定性分析、风吹雪影响、径流分割、地形和植被、气候变化等多角度,系统综述了融雪径流模型、融雪径流变化响应机制的研究进展。研究表明:①集总式模型与分布式模型具有互补性,前者适用于大尺度快速评估,后者适用于区域精细化模拟。②模型改进增强了不同区域和气候条件下模型的适用性,但改进策略主要聚焦于温度和降水对积雪相变机制的描述,对下垫面异质性表征不足。③模型的不确定性主要源于参数,研究方法应遵循“量化分析—敏感性排序—动态优化”的递进框架,其中气候条件引发的参数不确定性极为关键,且参数不确定性存在地理差异。④风吹雪通过升华和再分布改变积雪数据输入特征来影响融雪径流,但当前理论仅适用于稳态环境。⑤时间序列分割和同位素示踪是目前融雪径流分割的主流方法,能够有效揭示径流组分中融雪径流占比及影响因子的滞后效应。⑥在下垫面因素中,地形以坡度为主,植被以冠层和类型为主,持续影响融雪产流过程。⑦随着温度升高,融雪对径流的贡献将大于降水,未来呈两极分化趋势,且两者共同作用将导致融雪径流发生浮动。在综合融雪径流研究进展的基础上提出未来应从模型优化、风吹雪过程、下垫面、气候变化等方面进一步开展深入研究,以期为雪水文研究和灾害预警提供参考。

       

      Abstract: As a pivotal component of the water cycle, snowmelt runoff exerts significant impacts on water resource distribution and watershed ecosystems. To deepen the understanding of its role in snow hydrology, this study systematically reviewed research advancements in snowmelt runoff modeling and its variation response mechanisms from multiple perspectives: model development and refinement, uncertainty analysis, blowing snow effects, runoff partitioning, topography and vegetation impacts, and climate variation. The following research results are obtained: ① Lumped and distributed models exhibit complementary advantages, the former suitable for large-scale rapid assessments and the latter enabling refined regional simulations. ② Model improvements enhance applicability across diverse regions and climatic conditions, though current refinement strategies predominantly focus on thermal-precipitation phase change mechanisms while inadequately addressing underlying surface heterogeneity. ③ Parameter-induced uncertainty predominates, with research methodologies following a progressive framework of "quantitative analysis-sensitivity ranking-dynamic optimization". Climate-driven parameter uncertainties prove particularly critical, exhibiting distinct geographical variations. ④ Blowing snow alters snowpack input characteristics through sublimation and redistribution mechanisms, though existing theories remain confined to steady-state environments. ⑤ Time series decomposition and isotopic tracer techniques constitute mainstream approaches for runoff partitioning, effectively revealing snowmelt contribution ratios and the delayed effects of influencing factors. ⑥ Among surface characteristics, slope gradient dominates topographic influences, while canopy structure and vegetation types persistently affect snowmelt generation processes. ⑦ RCP scenario simulations consistently demonstrate that temperature elevation will amplify snowmelt′s runoff contribution beyond precipitation effects, projecting future polarization trends. The combined impacts of temperature and precipitation will induce snowmelt runoff fluctuations. Based on the research progress of snowmelt runoff, it is proposed that further in-depth research should be carried out from the aspects of model optimization, blowing snow processes, underlying surface characteristics, and climate change, so as to provide a reference for snow hydrology research and disaster warning.

       

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