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Model calibration and uncertainty analysis for runoff in the Chao River Basin using sequential uncertainty fitting

机译:潮流流域径流模型校准与不确定性分析,使用顺序不确定性配件

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The Chao River is one of the most important surface water sources for drinking water in Beijing. Due to the impacts of human activities and climate change, the Chao River basin is facing water scarcity. Therefore, it is very important to effectively manage water resources, while the distributed watershed model is the useful and effective tool. Soil and Water Assessment Tool (SWAT) was selected to set up hydrological model in the Chao River basin. Model calibration and uncertainty analysis were performed with Sequential Uncertainty Fitting (SUFI-2), which is one of the programs integrated with SWAT in the package SWAT-CUP (SWAT Calibration and Uncertainty Programs). Results showed that the p-factor was 0.85 and the r-factor was 1.12 in calibration period (1995-1999) while the p-factor was 0.83 and the r-factor was 2.15 in validation period (2000-2002). When values of p-factor and r-factor are accepted, further goodness of fit can be quantified by the coefficient of determination (R~2) and Nash-Sutcliffe coefficient (NS) between the observed and the final best simulated data. The results indicated that R~2 was 0.90 and NS was 0.88 in calibration period, while R~2 was 0.77 and NS was 0.74 in validation period. The results of calibration and uncertainty analysis were satisfactory.
机译:该潮河是最重要的地表水源在北京饮用水之一。由于人类活动和气候变化的影响,在潮河流域面临缺水。因此,有效地管理水资源是非常重要的,而分布式流域模型是有用和有效的工具。土壤和水评估工具(SWAT),被选中设立水文模型在潮河流域。模型校准和不确定性分析用连续不确定接头(SUFI-2),这是在包装SWAT-CUP(SWAT校准和不确定性的程序)与SWAT集成的程序之一执行。结果表明,P-因子为0.85和R因子是在校准期间(1995- 1999年)1.12而p因子为0.83和R因子是在验证期间2.15(2000- 2002年)。当p型因子和r因子值被接受,拟合优度进一步可以通过所观察到的和最终的最佳模拟数据之间确定(R〜2)和Nash-萨克利夫系数(NS)的系数进行量化。结果表明,R〜2为0.90和NS是在校准期间0.88,而R〜2为0.77和NS是在验证期间0.74。校准和不确定性分析的结果是令人满意的。

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