pstrongAbstract./strong Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1–10span class="thinspace"/spankm) to global-scale (over 50span class="thinspace"/spankm) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales./p.
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机译：> >摘要。地表和水文模型（LSMs / HMs）用于不同的空间分辨率，范围从集水规模（1＆ndash; 10 class =“ thinspace”> km ）到全球范围（超过50 class =“ thinspace”> km）的应用程序。在不同的空间尺度上应用相同的模型结构要求模型估算与所选分辨率无关的相似通量，即满足跨尺度的通量匹配条件。对最新的LSM和HM的分析表明，大多数LSM和HM的水文参数字段不一致。使用mHM，Noah-MP，PCR-GLOBWB和WaterGAP模型进行的多次实验表明，当前在大多数操作模型中使用的参数设置不足的做法存在陷阱，不足以满足通量匹配条件。这些示例表明，J。Dooge 1982年关于这些模型中未解决的参数化问题的说法仍然正确。基于对现有参数区域化技术的回顾，我们假设多尺度参数区域化（MPR）技术提供了一种实用且健壮的方法，可提供跨尺度的一致（无缝）参数和通量场。本文中，我们开发了一种通用的模型协议来描述如何将MPR应用于特定模型，并使用PCR-GLOBWB模型展示示例应用。最后，我们讨论了MPR在获得跨空间尺度的水文通量和状态的无缝预测中的潜在优势和局限性。
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