奎屯河流域春季融雪期SCS-CN模型参数取值方法

水资源是保障我国西北干旱半干旱地区生态环境安全的关键因素。以新疆奎屯河流域为例,通过修正SCS模型土壤持水量及初损率参数计算方法,寻找适用于干旱半干旱地区山区典型流域春季融雪期径流模拟模型,为流域掌握水资源量及生态用水提供决策依据。与以往研究不同之处在于:首先,引入度-日模型修正降水量参数,以满足流域降雨-融雪混合补给径流特征。其次,利用多期MODIS数据驱动的TS/VI特征空间理论结合土壤水分吸收平衡原理计算土壤持水量参数(S);再运用聚类分析法对初损率(λ)取值方法进行改进。通过参数算法改进后的SCS模型,参数率定期和验证期纳什效率系数和相对误差系数分别为0.92和0.64,0.7%和-1.5%。结果表明:1)参数算法改进后SCS模型能实现奎屯河流域春季融雪期日径流模拟。2)利用遥感大尺度地表信息参数化技术反演SCS模型参数,实现了遥感数据为SCS模型提供大尺度空间数据的同时,间接实现了模型参数由点状数据向面状数据转化的可能;3)初损率(λ)多组取值法可有效提高干旱半干旱地区大尺度流域径流模拟精度。

Calibration of SCS model parameters regarding snowmelt season in Xinjiang Kuitun River basin

Water resources are key factors of ecological environmental security in northwest arid region of China. They are also the most important factors for socio-economic development against the background of global warmer, especially in arid regions. It is necessary for arid regions to calculate total water resources because it can provide a reference for the government with which to formulate strategies. Water resources may have a large area and be supplied by runoff from mountain snowmelt and precipitation. The goal of this paper was to determine the suitable method to simulate runoff in arid areas. The Soil Conservation Service Curve Number (SCS-CN) developed by the U.S. Department of Agriculture National Resources Conversion Service (NRCS) is the most popular and widely applied model for direct runoff estimation. This method was modified by accounting for the static portion of infiltration and the antecedent moisture. This model has stimulated a great deal of discussion among scientists and hydrologists. The model is based on the water balance equation and curve number CN, which is derived from the tables given in the National Engineering Handbook for catchment characteristics, such as soil texture, land use, hydrologic condition, and initial soil moisture condition. Based on the spatiotemporal differences among watersheds, international and domestic academics have developed different methods to improve the SCS-CN model. One option is to improve its mechanism and another is to improve the parameter calculation methods. Because there is considerable scope to improve the SCS-CN model, we discuss a parameter algorithm to improve the method for snowmelt and precipitation mix and large-scale basins in arid regions as a solution to a major problem. This study focused on the Kuitun River Valley. We explored the adoption of an SCS model runoff simulation in arid and semi-arid regions with snow-melt and rainfall in spring by modifying the calculation method of SCS model parameters. To satisfy the characteristic of mix supplied runoff, precipitation was revised to represent the sum of rainfall and snowmelt. The snowmelt was calculated by the degree-day model. This was the first time MODIS satellite products with approximately 1km resolution were used to invert the Land Surface Temperature and Normalized Difference Vegetation Index. Then, we used the surface temperature/vegetation index (T_S/VI) constructed in a 2D scatter plot. The combined soil moisture absorption balance principle was used to calculate the moisture-holding capacity of soil. We used cluster analysis to modify the initial abstraction computing methods. The calibration and validation periods of Nash-Sutcliffe efficiency were 0.92 and 0.64, respectively. Relative errors were 0.7% and -1.3%, respectively. This indicated that the improved model was effective in simulating spring runoff in the Kuitun River Valley. Using remote sensing parameter information technology to improve the SCS model can indirectly implement data conversion from point to plane. Establishing a database of the initial abstraction can improve the precision in effectively simulating runoff in large-scale basins in arid and semi-arid regions. To circumvent the bottleneck caused by lack of data, reference to simulated runoff can be used under similar basin conditions in data-lacking regions.