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A weakly-constrained data assimilation approach to address rainfall runoff model structural inadequacy in streamflow prediction

机译:一种弱约束数据同化方法,以解决径流预测中降雨径流模型结构不足的问题

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This paper presents a simple yet effective weakly-constrained (WC) data assimilation (DA) approach for hydrologic models which accounts for model structural inadequacies associated with rainfall-runoff transformation processes. Compared to the strongly-constrained (SC) DA, WC DA adjusts the control variables less while producing similarly or more accurate analysis. Hence the adjusted model states are dynamically more consistent with those of the base model. The inadequacy of a rainfall-runoff model was modeled as an additive error to runoff components prior to routing and penalized in the objective function. Two example modeling applications, distributed and lumped, were carried out to investigate the effects of the WC DA approach on DA results. For distributed modeling, the distributed Sacramento Soil Moisture Accounting (SAC-SMA) model was applied to the TIFM7 Basin in Missouri, USA For lumped modeling, the lumped SAC-SMA model was applied to nineteen basins in Texas. In both cases, the variational DA (VAR) technique was used to assimilate discharge data at the basin outlet. For distributed SAC-SMA, spatially homogeneous error modeling yielded updated states that are spatially much more similar to the a priori states, as quantified by Earth Mover's Distance (EMD), than spatially heterogeneous error modeling by up to,10 times. DA experiments using both lumped and distributed SAC-SMA modeling indicated that assimilating outlet flow using the WC approach generally produce smaller mean absolute difference as well as higher correlation between the a priori and the updated states than the SC approach, while producing similar or smaller root mean square error of streamflow analysis and prediction. Large differences were found in both lumped and distributed modeling cases between the updated and the a priori lower zone tension and primary free water contents for both WC and SC approaches, indicating possible model structural deficiency in describing low flows or evapotranspiration processes for the catchments studied. Also presented are the findings from this study and key issues relevant to WC DA approaches using hydrologic models. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文提出了一种简单而有效的水文模型弱约束(WC)数据同化(DA)方法,该方法解决了与降雨径流转换过程相关的模型结构不足之处。与强约束(SC)DA相比,WC DA对控制变量的调整更少,而产生相似或更准确的分析。因此,调整后的模型状态在动态上与基本模型的状态更加一致。降雨径流模型的不足之处被建模为径流分量在路由之前的附加误差,并在目标函数中受到了惩罚。进行了两个示例建模应用程序(分布式和集总),以研究WC DA方法对DA结果的影响。对于分布式建模,将分布式萨克拉曼多土壤湿度会计(SAC-SMA)模型应用于美国密苏里州的TIFM7盆地。对于集总建模,将集总SAC-SMA模型应用于德克萨斯州的十九个盆地。在这两种情况下,均使用变分DA(VAR)技术来吸收流域出口处的流量数据。对于分布式SAC-SMA,空间均质误差建模所产生的更新状态在空间上与先验状态(通过地球移动器距离(EMD)进行量化)相近,比空间异质误差建模最多10倍。使用集总和分布式SAC-SMA建模的DA实验表明,与WC方法相比,使用WC方法吸收出口流量通常会产生更小的平均绝对差以及先验状态与更新状态之间的相关性,同时产生相似或较小的根流量分析和预测的均方误差。在集水模型和分布式模型案例中,对于WC和SC方法而言,更新后的和先验的较低区域张力和主要自由水含量之间存在较大差异,这表明在描述所研究流域的低流量或蒸散过程时可能存在模型结构缺陷。还介绍了这项研究的发现以及与使用水文模型的WC DA方法有关的关键问题。 (C)2016 Elsevier B.V.保留所有权利。

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