Non-parametric direct mapping of rainfall-runoff relationships : an alternative approach to data analysis and modelling.

Iorgulescu, I. and Beven, Keith J. (2004) Non-parametric direct mapping of rainfall-runoff relationships : an alternative approach to data analysis and modelling. Water Resources Research, 40 (8). W08403. ISSN 0043-1397

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Abstract

We present a new approach for the analysis and modeling of catchment rainfall-runoff relationships that uses as predictor variables input history summary variables only. The latter are defined as linear combinations of inputs at a given number of previous time steps. This transforms the dynamic identification problem into a static one. As the identification algorithm we use regression trees, which act as a nonlinear nonparametric model. The original algorithm is adapted to account for serial correlation in variables. The new method is applied to two subcatchments of the U.S. Department of Agriculture Forest Service Andrews Experimental Forest Watershed (Oregon, United States). Simple and interpretable tree models explain more than 80% of the initial deviance of the observations in both calibration and validation. This suggests that the selected variables have a good predictive power and that further modeling attempts using them are warranted. The models show a distinct pattern of the selected explanatory variables. Applications of the method include data quality control, comparative analysis, assessment of hydrological change, and multicriterion evaluation of parametric hydrological models.

Item Type: Journal Article
Journal or Publication Title: Water Resources Research
Uncontrolled Keywords: /dk/atira/pure/researchoutput/libraryofcongress/ge
Subjects:
Departments: Faculty of Science and Technology > Lancaster Environment Centre
ID Code: 21324
Deposited By: ep_ss_importer
Deposited On: 09 Jan 2009 11:03
Refereed?: Yes
Published?: Published
Last Modified: 15 Aug 2019 02:15
URI: https://eprints.lancs.ac.uk/id/eprint/21324

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