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Evaluation of outputs from automated baseflow separation methods against simulated baseflow from a physically based, surface water-groundwater flow model

机译:针对基于物理的地表水-地下水流模型的模拟基础流,评估自动基础流分离方法的输出

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摘要

Summary Baseflow is often considered to be the groundwater discharge component of streamflow. It is commonly estimated using conceptual models, recursive filters or a combination of the two. However, it is difficult to validate these methods due to the current challenges of measuring baseflow in the field. In this study, simulation of a synthetic catchment’s response to rainfall is carried out using a fully integrated surface water-groundwater flow model. A series of rainfall events with differing recovery periods and varied antecedent moisture conditions is considered to span a range of different streamflow generation dynamics. Baseflow is estimated for the outlet hydrograph of the synthetic catchment using a selection of commonly used automated baseflow separation methods. These estimates are compared to the baseflow signal obtained from the numerical model, which serves as the control experiment. Results from these comparisons show that depending on the method used, automated baseflow separation underestimates the simulated baseflow by as much as 28%, or overestimates it by up to 74%, during rainfall events. No separation method is found to be clearly superior to the others, as the performance of the various methods varies with different soil types, antecedent moisture conditions and rainfall events. The differences between the various approaches clearly demonstrate that the baseflow separation methods investigated are not universally applicable.
机译:总结基流通常被认为是水流的地下水排放成分。通常使用概念模型,递归过滤器或两者的组合进行估算。但是,由于当前在现场测量基准流的挑战,很难验证这些方法。在这项研究中,使用完全集成的地表水-地下水流模型对人工流域对降雨的响应进行了模拟。一系列具有不同恢复期和不同前期湿度条件的降雨事件被认为涵盖了一系列不同的径流产生动力学。使用一系列常用的自动基础流分离方法,可以估算出合成流域出口水位的基础流。将这些估计值与从数值模型获得的基本流量信号进行比较,以作为控制实验。这些比较的结果表明,在降雨事件发生期间,根据所使用的方法,自动基流分离会低估模拟基流多达28%,或高估多达74%。没有发现分离方法明显优于其他分离方法,因为各种方法的性能会随土壤类型,先前的湿度条件和降雨事件而变化。各种方法之间的差异清楚地表明,所研究的底流分离方法并非普遍适用。

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