The Soil and Water Assessment Tool （SWAT） was implemented in a small forested watershed of the Soan River Basin innorthern Pakistan through application of the sequential uncertainty fitting （SUFI-2） method to inve...The Soil and Water Assessment Tool （SWAT） was implemented in a small forested watershed of the Soan River Basin innorthern Pakistan through application of the sequential uncertainty fitting （SUFI-2） method to investigate the associateduncertainty in runoff and sediment load estimation. The model was calibrated for a 10-year period （1991–2000） with aninitial 4-year warm-up period （1987–1990）, and was validated for the subsequent 10-year period （2001–2010）. Themodel evaluation indices R2 （the coefficient of determination）, NS （the Nash-Sutcliffe efficiency）, and PBIAS （percentbias） for stream flows simulation indicated that there was a good agreement between the measured and simulated flows.To assess the uncertainty in the model outputs, p-factor （a 95% prediction uncertainty, 95PPU） and r-factors （averagewideness width of the 95PPU band divided by the standard deviation of the observed values） were taken into account.The 95PPU band bracketed 72% of the observed data during the calibration and 67% during the validation. The r-factorwas 0.81 during the calibration and 0.68 during the validation. For monthly sediment yield, the model evaluation coefficients（R2 and NS） for the calibration were computed as 0.81 and 0.79, respectively; for validation, they were 0.78and 0.74, respectively. Meanwhile, the 95PPU covered more than 60% of the observed sediment data during calibrationand validation. Moreover, improved model prediction and parameter estimation were observed with the increasednumber of iterations. However, the model performance became worse after the fourth iterations due to an unreasonableparameter estimation. Overall results indicated the applicability of the SWAT model with moderate levels of uncertaintyduring the calibration and high levels during the validation. Thus, this calibrated SWAT model can be used for assessmentof water balance components, climate change studies, and land use management practices.展开更多
地理信息系统（GIS）支持下的SWAT（Soil and Water Assessment Tool）分布式水文模型以流域离散化空间参数来描述流域水文变化特性,从物理意义上表达流域内的水文过程,但众多不确定的参数影响了模型的应用效果,因此有必要对参数进行敏...地理信息系统（GIS）支持下的SWAT（Soil and Water Assessment Tool）分布式水文模型以流域离散化空间参数来描述流域水文变化特性,从物理意义上表达流域内的水文过程,但众多不确定的参数影响了模型的应用效果,因此有必要对参数进行敏感性分析。将SWAT模型应用到祁连山黑河上游山区流域,进行了11年（1990-2000年）逐日径流模拟,通过一个简便的敏感性分析方法,将模型影响水文过程的参数分成4类敏感级别,最后确定模型的参数。在11年的逐日模拟中,1990-1995年为参数敏感性分析期和模型率定期,1996-2000年为模型的检验期,模拟结果显示,在黑河山区流域,丰水年逐日出山径流的模型效率系数R2达到0.8以上,平水年和枯水年R2在0.51-0.79之间。展开更多
水文模型是模拟流域水文过程的重要工具,其参数的不确定性降低了模拟精度。为了定量探究参数不确定性对径流模拟的影响,文章基于构建的子午河流域SWAT(soil and water assessment tool)模型,采用析因分析方差分解方法评估其影响。结果表...水文模型是模拟流域水文过程的重要工具,其参数的不确定性降低了模拟精度。为了定量探究参数不确定性对径流模拟的影响,文章基于构建的子午河流域SWAT(soil and water assessment tool)模型,采用析因分析方差分解方法评估其影响。结果表明:不同流量下参数不确定性对径流模拟影响差异明显,低流量时参数不确定性影响大,高流量时其影响小;对水文响应最敏感的参数依次为主河道传输损失流量进入深层含水层的比例系数、主河道河床有效导水率和土壤饱和导水。主河道传输损失流量进入深层含水层的比例系数与土壤饱和导水率之间的交互作用,主河道河床有效导水率与土壤饱和导水率之间的交互作用对径流模拟影响显著。结果可为降低水文模型参数不确定性的影响提供参考。展开更多
基金supported by the Centre of Excellence in Water Resources Engineering, University of Engineering and Technology Lahore, and local authorities in Pakistan
文摘The Soil and Water Assessment Tool （SWAT） was implemented in a small forested watershed of the Soan River Basin innorthern Pakistan through application of the sequential uncertainty fitting （SUFI-2） method to investigate the associateduncertainty in runoff and sediment load estimation. The model was calibrated for a 10-year period （1991–2000） with aninitial 4-year warm-up period （1987–1990）, and was validated for the subsequent 10-year period （2001–2010）. Themodel evaluation indices R2 （the coefficient of determination）, NS （the Nash-Sutcliffe efficiency）, and PBIAS （percentbias） for stream flows simulation indicated that there was a good agreement between the measured and simulated flows.To assess the uncertainty in the model outputs, p-factor （a 95% prediction uncertainty, 95PPU） and r-factors （averagewideness width of the 95PPU band divided by the standard deviation of the observed values） were taken into account.The 95PPU band bracketed 72% of the observed data during the calibration and 67% during the validation. The r-factorwas 0.81 during the calibration and 0.68 during the validation. For monthly sediment yield, the model evaluation coefficients（R2 and NS） for the calibration were computed as 0.81 and 0.79, respectively; for validation, they were 0.78and 0.74, respectively. Meanwhile, the 95PPU covered more than 60% of the observed sediment data during calibrationand validation. Moreover, improved model prediction and parameter estimation were observed with the increasednumber of iterations. However, the model performance became worse after the fourth iterations due to an unreasonableparameter estimation. Overall results indicated the applicability of the SWAT model with moderate levels of uncertaintyduring the calibration and high levels during the validation. Thus, this calibrated SWAT model can be used for assessmentof water balance components, climate change studies, and land use management practices.
文摘地理信息系统（GIS）支持下的SWAT（Soil and Water Assessment Tool）分布式水文模型以流域离散化空间参数来描述流域水文变化特性,从物理意义上表达流域内的水文过程,但众多不确定的参数影响了模型的应用效果,因此有必要对参数进行敏感性分析。将SWAT模型应用到祁连山黑河上游山区流域,进行了11年（1990-2000年）逐日径流模拟,通过一个简便的敏感性分析方法,将模型影响水文过程的参数分成4类敏感级别,最后确定模型的参数。在11年的逐日模拟中,1990-1995年为参数敏感性分析期和模型率定期,1996-2000年为模型的检验期,模拟结果显示,在黑河山区流域,丰水年逐日出山径流的模型效率系数R2达到0.8以上,平水年和枯水年R2在0.51-0.79之间。
文摘水文模型是模拟流域水文过程的重要工具,其参数的不确定性降低了模拟精度。为了定量探究参数不确定性对径流模拟的影响,文章基于构建的子午河流域SWAT(soil and water assessment tool)模型,采用析因分析方差分解方法评估其影响。结果表明:不同流量下参数不确定性对径流模拟影响差异明显,低流量时参数不确定性影响大,高流量时其影响小;对水文响应最敏感的参数依次为主河道传输损失流量进入深层含水层的比例系数、主河道河床有效导水率和土壤饱和导水。主河道传输损失流量进入深层含水层的比例系数与土壤饱和导水率之间的交互作用,主河道河床有效导水率与土壤饱和导水率之间的交互作用对径流模拟影响显著。结果可为降低水文模型参数不确定性的影响提供参考。
