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Development of neuro-fuzzy models to account for temporal and spatial variations in a lumped rainfall-runoff model
Author(s)
Date Issued
2008-02
Date Available
2010-08-03T13:41:25Z
Abstract
For many good and practical reasons, lumped rainfall-runoff models are widely used to represent a catchment‟s response to rainfall. However, they have some acknowledged limitation, some of which are addressed here using a neuro-fuzzy model to combine, in an optimal way, a number of lumped-sub-models. For instance, to address temporal variation, one of the sub-models in the combination may perform well under flood conditions and another under drier conditions and the neuro- fuzzy system would combine their outputs for each time-step in a manner depending on the prevailing conditions. Similarly to address spatial variation, one of the sub-models may perform well for the upland parts of the catchment and another for the lowland parts and again the neuro-fuzzy system is expected to combine the different outputs appropriately. The proposed combination method can use any lumped catchment model, but has been tested here with the Simple Linear model (SLM) and the Soil Moisture and Accounting Routing (SMAR) models. Eleven catchments with different hydrological and meteorological conditions have been used to assess the models with respect to temporal variations in response while one catchment is used to address the effect of spatial variation. The neuro-fuzzy combined-sub-models of SLM and SMAR modelled the temporal and spatial variation in catchment response better than the lumped version of each model. Also the SMAR model significantly outperformed the SLM either as a lumped model or as a sub-model in any of the combinations.
Sponsorship
Other funder
Other Sponsorship
Environmental Protection Agency
Type of Material
Journal Article
Publisher
Elsevier
Journal
Journal of Hydrology
Volume
349
Issue
3-4
Start Page
277
End Page
290
Copyright (Published Version)
2007 Elsevier B.V
Subject – LCSH
Runoff--Computer programs
Neural networks (Computer science)
Fuzzy systems
Hydrologic models
Web versions
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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