期刊
WATER RESOURCES RESEARCH
卷 46, 期 -, 页码 -出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2009WR007845
关键词
-
资金
- UK Defra [PE0120]
- UK BBSRC
- UK NERC [NE/E002242/1]
- UK Research Council [RES-229-25-0009-A]
- NERC [NE/E002242/1] Funding Source: UKRI
- Natural Environment Research Council [NE/E002242/1, ceh010010] Funding Source: researchfish
It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a leaking of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据