ABSTRACT Most conceptual hydrological models do not treat vegetation as a dynamic component. This study focuses on understanding the impact of model structural complexity on the sensitivity of hydrologic models to potential evapotranspiration forcing data. To achieve this, two classes of hydrologic models are examined: (1) lumped, conceptual rainfall–runoff models and (2) eco-hydrologic models. A sample of 57 US catchments, covering eight eco-regions, included in the MOPEX dataset is used. While streamflow simulation performance in complex models did not exhibit increased sensitivity to PET, actual evapotranspiration simulation performance showed greater sensitivity in energy-limited catchments. This analysis warns against using over-simplistic PET estimations in energy-limited catchments for eco-hydrologic models and for more complex conceptual hydrologic models. This is particularly true for streamflow-only calibrations that commonly fail to properly constrain physically based parameters. Ultimately, these results have the potential to inform data collection and model selection efforts to yield the greatest benefit.

中文翻译：

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了解水文模型结构对蒸散驱动敏感性的作用

摘要 大多数概念性水文模型并未将植被视为动态组件。本研究侧重于了解模型结构复杂性对水文模型对潜在蒸散强迫数据的敏感性的影响。为实现这一目标，研究了两类水文模型：(1) 集总、概念性降雨-径流模型和 (2) 生态水文模型。使用 MOPEX 数据集中包含的 57 个美国集水区样本，涵盖八个生态区。虽然复杂模型中的流量模拟性能没有表现出对 PET 的敏感性增加，但实际的蒸散模拟性能在能量有限的集水区表现出更高的敏感性。该分析警告不要在能源有限的流域中对生态水文模型和更复杂的概念水文模型使用过于简单的 PET 估计。对于通常无法正确约束基于物理的参数的仅流校准尤其如此。最终，这些结果有可能为数据收集和模型选择工作提供信息，以产生最大的收益。