Hydrological models have proliferated in the past several decades prompting debates on the virtues and shortcomings of various modelling approaches. Rather than critiquing individual models or modelling approaches, the objective here is to address the critical issues of scaling and hydrological process representation in various types of models with suggestions for improving these attributes in a parsimonious manner that captures and explains their functionality as simply as possible. This discussion focuses mostly on conceptual and physical/process-based models where understanding the internal catchment processes and hydrologic pathways is important. Such hydrological models can be improved by using data from advanced remote sensing (both spatial and temporal) and derivatives, applications of machine learning, flexible structures, and informing models through nested catchment studies in which internal catchment processes are elucidated. Incorporating concepts of hydrological connectivity into flexible model structures is a promising approach for improving flow path representation. Also important is consideration of the scale dependency of hydrological parameters to avoid scale mismatch between measured and modelled parameters. Examples are presented from remote high-elevation regions where water sources and pathways differ from temperate and tropical environments where more attention has been focused. The challenge of incorporating spatially and temporally variable water inputs, hydrologically pathways, climate, and land use into hydrological models requires modellers to collaborate with catchment hydrologists to include important processes at relevant scales—i.e. develop smarter hydrological models.

中文翻译：

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更智能的流域水文模型策略：结合缩放和更好的过程表示

在过去的几十年里，水文模型激增，引发了关于各种建模方法的优点和缺点的辩论。这里的目标不是批评单个模型或建模方法，而是解决各种类型模型中缩放和水文过程表示的关键问题，并提出以尽可能简单地捕获和解释其功能的简约方式改进这些属性的建议。该讨论主要集中在基于概念和物理/过程的模型上，在这些模型中，了解内部流域过程和水文路径很重要。这种水文模型可以通过使用来自先进遥感（空间和时间）和衍生物的数据、机器学习的应用、灵活的结构、并通过阐明内部流域过程的嵌套流域研究为模型提供信息。将水文连通性的概念结合到灵活的模型结构中是改善流路表示的一种很有前途的方法。同样重要的是考虑水文参数的尺度依赖性，以避免测量参数和模型参数之间的尺度不匹配。示例来自偏远的高海拔地区，这些地区的水源和路径不同于温带和热带环境，而温带和热带环境受到更多关注。将空间和时间可变的水输入、水文路径、气候和土地利用纳入水文模型的挑战要求建模者与流域水文学家合作以包括相关尺度的重要过程——即