水量平衡模型是目前水文及环境分析中最常用的工具和手段之一,半干旱地区的水文模拟是目前水文科学研究中的难点。以内蒙古地区的锡林河流域为研究对象,开展了考虑融雪的水量平衡模型(Snowmelt-based Water Balance Model,SWBM模型)的拓展性应用研究。结果表明:锡林河流域气候干旱,产流受降水和融雪驱动,流域降水量及实测径流量均呈现弱减少趋势。SWBM模型对对月径流过程具有较好的模拟效果,率定期和检验期的模型效率系数均可超过60%,相对误差小于8%,说明该模型可以用于研究气候变化对半干旱地区的影响评价。
Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1) a screening method (Morris) for qualitative ranking of parameters, and (2) a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol). First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM) were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.
