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An investigation on stream temperature analysis based on evolutionary computing
Author(s) -
Doglioni A.,
Giustolisi O.,
Savic D. A.,
Webb B. W.
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.6607
Subject(s) - air temperature , environmental science , hydrology (agriculture) , polynomial regression , regression , regression analysis , meteorology , linear regression , mathematics , statistics , geology , geography , geotechnical engineering
The data‐driven technique, evolutionary polynomial regression, has been tested and used for the study of water temperature behaviour in the River Barle (south‐west England). The study aimed to produce multiple models for forecasting water temperature, using air temperature as input. In addition, river discharge data were used to describe the hydrological regime of the study stream, even if they are not involved in the modelling phase. The availability of data sampled at hourly intervals allowed behaviour to be studied at several time scales, including short‐term lags between air temperature and water temperature. The approach to model building differs from previous studies in that the relationship between air temperature and water temperature is not evaluated on the basis of a multi‐parameter regression, nor does it identify particular structures; rather the evolutionary technique identifies the model by itself. In fact, the non‐linear relationship between air temperature and water temperature is investigated by an evolutionary search in the space of particular pseudo‐polynomials structures. Copyright © 2007 John Wiley & Sons, Ltd.