Regionalization of runoff models derived by genetic programming

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F17%3A73285" target="_blank" >RIV/60460709:41330/17:73285 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.jhydrol.2017.02.018" target="_blank" >http://dx.doi.org/10.1016/j.jhydrol.2017.02.018</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jhydrol.2017.02.018" target="_blank" >10.1016/j.jhydrol.2017.02.018</a>

Result language
angličtina
Original language name
Regionalization of runoff models derived by genetic programming
Original language description
The aim of this study is to assess the potential of hydrological models derived by genetic programming (GP) to estimate runoff at ungauged catchments by regionalization. A set of 176 catchments from the MOPEX (Model Parameter Estimation Experiment) project was used for our analysis. Runoff models for each catchment were derived by genetic programming (hereafter GP models). A comparison of efficiency was made between GP models and three conceptual models (SAC-SMA, BTOPMC, GR4J). The efficiency of the GP models was in general comparable with that of the SAC-SMA and BTOPMC models but slightly lower (up to 10% for calibration and 15% in validation) than for the GR4J model. The relationship between the efficiency of the GP models and catchment descriptors (CDs) was investigated. From 13 available CDs the aridity index and mean catchment elevation explained most of the variation in the efficiency of the GP models. The runoff for each catchment was then estimated considering GP models from single or multip
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10501 - Hydrology

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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