Perceptual perplexity and parameter parsimony
Perceptual perplexity and parameter parsimony
复制标题
感知困惑和参数简约
作者：
K. Beven;N. Chappell
本文重新考虑了水文过程感知模型的概念，将其作为为特定流域开发程序模型时应考虑的第一阶段。虽然已经开发了各种实验流域感知模型，但该概念并未广泛用于定义或评估流域模型。这至少部分是因为感知模型中可能存在明显的复杂性以及过程模型结构和参数化的近似性质，特别是在需要参数简约性的情况下。以英格兰西北部坎布里亚郡流域的感知模型为范例，并根据时变分布函数进行说明。解决了两个关键问题：如何在感兴趣的尺度上测试感知模型假设，以及如何在条件预测模型中基于定性感知知识施加约束？有人认为，感知信息是有价值的，特别是在思考预测未来变化的影响时，我们仍然有很多东西需要学习，以从观察和感知的复杂性转向简约的可预测性。
This article reconsiders the concept of a perceptual model of hydrological processes as the first stage to be considered in developing a procedural model for a particular catchment area. While various perceptual models for experimental catchments have been developed, the concept is not widely used in defining or evaluating catchment models. This is, at least in part, because of the evident complexity possible in a perceptual model and the approximate nature of procedural model structures and parameterizations, particularly where there is a requirement for parameter parsimony. A perceptual model for catchments in Cumbria, North‐West England, is developed as an exemplar and illustrated in terms of time varying distribution functions. Two critical questions are addressed: how can perceptual model hypotheses be tested at scales of interest, and how can constraints then be imposed on the basis of qualitative perceptual knowledge in conditioning predictive models? It is suggested that there is value in perceptual information, particularly in thinking about predicting the impacts of future change and that we still have much to learn about moving from observational and perceptual complexity to parsimonious predictability.
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影响因子：
11.4
作者：
Jones, Timothy D.;Chappell, Nick A.;Tych, Wlodek
通讯作者：
Tych, Wlodek
影响因子：
3.2
作者：
K. Beven
通讯作者：
K. Beven
影响因子：
2.7
作者：
Beven, Keith J.;Alcock, Ruth E.
通讯作者：
Alcock, Ruth E.
影响因子：
6.3
作者：
K. Beven
通讯作者：
K. Beven
影响因子：
6
作者：
Dosher B;Lu ZL
通讯作者：
Lu ZL