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首页> 外文会议>Annual conference of the Canadian Society for Civil Engineering >Comparison of Sequential Uncertainty Fitting Algorithm (SUFI-2) and Parameter Solution (ParaSol) Method for Analyzing Uncertainties in Distributed Hydrological Modeling - A Case Study
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Comparison of Sequential Uncertainty Fitting Algorithm (SUFI-2) and Parameter Solution (ParaSol) Method for Analyzing Uncertainties in Distributed Hydrological Modeling - A Case Study

机译：序列不确定度拟合算法（SUFI-2）与参数解法（ParaSol）方法在分布式水文建模中的不确定性分析比较-案例研究

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摘要

As the distributed hydrological models play a very important role at water resource management, reliable quantification of uncertainty in hydrological modeling results is quite necessary. The purpose of this study is to better understand the hydrology of the study area and help decision making processes for watershed water resource management through scientific uncertainty analysis. In this study, the upstream of the Wenjing River watershed in Western China was selected as the study area. The soil and water assessment tool (SWAT) model was applied to simulate the surface runoff during 1998-2001 and validated by the observed data. After global sensitivity analysis and modeling calibration, the R~2 values of surface runoff for calibration and verification periods were up to 0.724 and 0.921, respectively. Due to less computation efforts and the feasibility to handle complex models, two uncertainty analysis methods were further conducted and compared: 1) the sequential uncertainty fitting algorithm (SUFI-2) and 2) the parameter solution (ParaSol) method. After comparison of evaluation criteria (r-factor and p-factor) and performance of best estimates of uncertainty analysis, SUFI-2 was able to provide more reasonable predictive results than ParaSol.
机译：由于分布式水文模型在水资源管理中起着非常重要的作用，因此有必要对水文模型结果中的不确定性进行可靠的量化。这项研究的目的是通过科学的不确定性分析更好地了解研究区域的水文学，并帮助流域水资源管理的决策过程。在本研究中，选择了中国西部温京河流域的上游作为研究区域。应用土壤和水评估工具（SWAT）模型来模拟1998-2001年期间的地表径流，并通过观测数据进行了验证。经过整体敏感性分析和模型标定，标定和验证期的地表径流R〜2值分别达到0.724和0.921。由于较少的计算工作量和处理复杂模型的可行性，因此进一步进行了两种不确定性分析方法并进行了比较：1）顺序不确定性拟合算法（SUFI-2）和2）参数解（ParaSol）方法。比较评估标准（r因子和p因子）和不确定性分析的最佳估计结果后，SUFI-2能够提供比ParaSol更合理的预测结果。

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