Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 66706
Title Identifying scale-dependent models : The case of overland flow at the hillslope
Author(s) Loon, E.E. van; Keesman, K.J.
Source Water Resources Research 36 (2000)1. - ISSN 0043-1397 - p. 243 - 254.
Department(s) Systems and Control Group
Publication type Refereed Article in a scientific journal
Publication year 2000
Keyword(s) oppervlakkige afvoer - hydrologie - hydraulisch geleidingsvermogen - modellen - hellingen - runoff - hydrology - hydraulic conductivity - models - slopes
Categories Hydrology
Abstract The hydrological problem to correctly partition rainfall at various scales may require scale dependent models. This study introduces a new method to identify scale dependent state space models in a hydrological context. In addition it investigates relations between model structure, resolution and uncertainty for the case of overland flow from a hillslope. The main strengths of the method are the ability to evaluate a very large set of candidate models, general applicability, the possibility to interpret identified models in a physical sense, and computational simplicity. Weaknesses are the possibly complex models that result, computation time required, and the relative poor fit of models as compared to methods with more strict assumptions on errors. For these reasons the method is mainly suitable as a first stage in an identification procedure, leading to the selection of a limited number of candidate models. For the case of overland flow at the hillslope scale it was found that model structure, resolution and uncertainty are closely related. When compared to the total set of calibrated models the fittest (best) models are characterised by a small average parameter uncertainty and a constant number of parameters. However, marked structural model differences exist for equally fit models at different spatial and temporal resolutions. Considering the whole spectrum of spatial and temporal resolutions covered by calibrated models, the fittest models are found in a narrow range.
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