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Error analysis for the evaluation of model performance: rainfall–runoff event summary variables
Author(s) -
Pebesma Edzer J.,
Switzer Paul,
Loague Keith
Publication year - 2007
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.6529
Subject(s) - surface runoff , discretization , environmental science , runoff model , hydrology (agriculture) , computer science , event (particle physics) , statistics , hydrological modelling , continuous simulation , mathematics , simulation , geology , mathematical analysis , ecology , physics , climatology , biology , geotechnical engineering , quantum mechanics
This paper provides a procedure for the evaluation of model performance for rainfall–runoff event summary variables, such as total discharge or peak runoff. The procedure is based on the analysis of model errors, defined as the differences between observed values and values predicted by a simulation model. Model errors can (i) indicate whether and where the model can be improved, (ii) be used to measure the performance of a model, and (iii) be used to compare model simulations. In this paper, both statistical and graphical methods are used to characterize model errors. We explore model recalibration by relating model errors to the model predictions, and to external, independent variables. The R‐5 catchment data sets that we used in this study include summary variables for 72 rainfall–runoff events. The simulations used in this study were previously conducted with the quasi‐physically based rainfall–runoff model QPBRRM for 11 different characterizations of the R‐5 catchment, each with increasing information or a refined spatial discretization of the overland flow planes. This paper is about proposing model diagnostics and not about procedures for using diagnostics for model modification. Copyright © 2007 John Wiley & Sons, Ltd.