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首页> 外文期刊>Journal of the American Water Resources Association >Assessing Parameter Uncertainty of a Semi-Distributed Hydrology Model for a Shallow Aquifer Dominated Environmental System
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Assessing Parameter Uncertainty of a Semi-Distributed Hydrology Model for a Shallow Aquifer Dominated Environmental System

机译：浅层含水层主导环境系统半分布式水文模型参数不确定性评估

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This paper examines the performance of a semi-distributed hydrology model (i.e., Soil and Water Assessment Tool [SWAT]) using Sequential Uncertainty FItting (SUFI-2), generalized likelihood uncertainty estimation (GLUE), parameter solution (ParaSol), and particle swarm optimization (PSO). We applied SWAT to the Waccamaw watershed, a shallow aquifer dominated Coastal Plain watershed in the Southeastern United States (U.S.). The model was calibrated (2003-2005) and validated (2006-2007) at two U.S. Geological Survey gaging stations, using significant parameters related to surface hydrology, hydrogeology, hydraulics, and physical properties. SWAT performed best during intervals with wet and normal antecedent conditions with varying sensitivity to effluent channel shape and characteristics. In addition, the calibration of all algorithms depended mostly on Manning's n-value for the tributary channels as the surface friction resistance factor to generate runoff. SUFI-2 and PSO simulated the same relative probability distribution tails to those observed at an upstream outlet, while all methods (except ParaSol) exhibited longer tails at a downstream outlet. The ParaSol model exhibited large skewness suggesting a global search algorithm was less capable of characterizing parameter uncertainty. Our findings provide insights regarding parameter sensitivity and uncertainty as well as modeling diagnostic analysis that can improve hydrologic theory and prediction in complex watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.
机译：本文研究了使用顺序不确定度拟合（SUFI-2），广义似然不确定性估计（GLUE），参数解（ParaSol）和粒子的半分布式水文模型（即土壤和水评估工具[SWAT]）的性能群优化（PSO）。我们对Waccamaw分水岭应用了SWAT，Waccamaw分水岭是美国东南部（美国）一个以浅水层为主的沿海平原流域。使用与地表水文学，水文地质学，水力学和物理特性相关的重要参数，在两个美国地质调查站对模型进行了校准（2003-2005年）和验证（2006-2007年）。在潮湿和正常的前期条件下，对废水通道的形状和特性的敏感性各不相同，因此，SWAT的效果最佳。另外，所有算法的校准主要取决于支流通道的Manning的n值，作为产生径流的表面摩擦阻力因子。 SUFI-2和PSO模拟的相对概率分布尾巴与上游出口处观察到的相对概率分布尾巴相同，而所有方法（ParaSol除外）在下游出口处均显示出较长的尾巴。 ParaSol模型显示出较大的偏度，表明全局搜索算法无法表征参数不确定性。我们的发现提供了有关参数敏感性和不确定性以及建模诊断分析的见解，可以改善复杂流域的水文理论和预测。编者注：本文是针对新兴水文和水质挑战的SWAT应用程序精选系列的一部分。有关该系列的简介和背景信息，请参见2017年2月号。

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