Regionalization of runoff models derived by genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Hermanovsky:2017:JH,
  author =       "M. Hermanovsky and V. Havlicek and M. Hanel and 
                 P. Pech",
  title =        "Regionalization of runoff models derived by genetic
                 programming",
  journal =      "Journal of Hydrology",
  volume =       "547",
  pages =        "544--556",
  year =         "2017",
  ISSN =         "0022-1694",
  DOI =          "doi:10.1016/j.jhydrol.2017.02.018",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0022169417300951",
  abstract =     "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 10percent for calibration and
                 15percent 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 multiple physically similar catchments
                 (donors). Better results were obtained with multiple
                 donor catchments. Increasing the number of CDs used for
                 quantification of physical similarity improves the
                 efficiency of the GP models in runoff simulation. The
                 best regionalization results were obtained with 6 CDs
                 together with 6 donors. Our results show that transfer
                 of the GP models is possible and leads to satisfactory
                 results when applied at physically similar catchments.
                 The GP models can be therefore used as an alternative
                 for runoff modelling at ungauged catchments if similar
                 gauged catchments can be identified and successfully
                 simulated.",
  keywords =     "genetic algorithms, genetic programming, Physical
                 similarity, PUB, Regionalization, Runoff modelling",
}

Genetic Programming entries for Martin Hermanovsky Vojtech Havlicek Martin Hanel Pavel Pech

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