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首页> 外文期刊>The Science of the Total Environment >Quantifying the space - time variability of water balance components in an agricultural basin using a process-based hydrologic model and the Budyko framework
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Quantifying the space - time variability of water balance components in an agricultural basin using a process-based hydrologic model and the Budyko framework

机译:使用基于过程的水文模型和Budyko框架量化农业盆地中水平衡成分的时空变异。

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Process-based distributed hydrologic models (PBHMs), which link watershed characteristics with process representations, are useful tools to evaluate distributed and ensemble hydrologic responses of a basin to climate inputs. However, complexities associated with parameter interactions and their spatial heterogeneity may introduce high uncertainty in the parameterization of a PBHM. The Budyko curve framework offers an effective approach for evaluating the variability in the water balance components from a PBHM and can be used to explore the link between model performance with parameter heterogeneities and the Budyko curve characteristics. In this work a PBHM was calibrated using a multi-site calibration strategy, which was built upon a step-wise calibration algorithm combined with multiple calibration targets induding river discharges, evapotranspiration and ground water heads, to reduce compensation errors caused by component interactions. This strategy was used for the Kalamazoo River watershed in Michigan, USA, with obvious physiographic and land surface heterogeneities. The Budyko framework characterized the water balance variability at the sub-watershed scale: two empirical methods were used to evaluate the calibrated PBHM parameters using Budyko-estimated values and to assess the physical relevance of the parameters. The relative infiltration capacity is found to play an important role in affecting the spatial variability of the annual water balance of this watershed. This work brings out the importance of optimizing calibration strategies by linking catchment heterogeneities with processes reasoning in order to understand the underlying hydrologic controls. (C) 2019 Elsevier B.V. All rights reserved.
机译:基于过程的分布式水文模型(PBHM)将流域特征与过程表示联系在一起,是评估流域对气候输入的分布式和整体水文响应的有用工具。但是,与参数交互作用及其空间异质性相关的复杂性可能会在PBHM的参数化过程中引入高度不确定性。 Budyko曲线框架为评估PBHM中水平衡成分的可变性提供了有效的方法,可用于探索模型性能与参数异质性和Budyko曲线特征之间的联系。在这项工作中,PBHM是使用多站点校准策略进行校准的,该策略是基于逐步校准算法并结合多个校准目标(包括河流流量,蒸散量和地下水头)来进行校准的,以减少由组件相互作用引起的补偿误差。此策略用于美国密歇根州的卡拉马祖河流域,具有明显的地貌和陆地表面异质性。 Budyko框架描述了在小流域尺度上水平衡的变化:使用两种经验方法使用Budyko估计值评估校准的PBHM参数并评估参数的物理相关性。发现相对入渗能力在影响该流域年水平衡的空间变异性中起着重要作用。这项工作通过将流域的非均质性与过程推理联系起来,以了解潜在的水文控制,提出了优化标定策略的重要性。 (C)2019 Elsevier B.V.保留所有权利。

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