Testing the structure of a hydrological model using Genetic Programming

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@Article{Selle20111,
  author =       "Benny Selle and Nitin Muttil",
  title =        "Testing the structure of a hydrological model using
                 Genetic Programming",
  journal =      "Journal of Hydrology",
  volume =       "397",
  number =       "1-2",
  pages =        "1--9",
  year =         "2011",
  ISSN =         "0022-1694",
  DOI =          "doi:10.1016/j.jhydrol.2010.11.009",
  URL =          "http://www.sciencedirect.com/science/article/B6V6C-51JXFSR-1/2/10682f600e603f8019d0df938a9e5c6f",
  keywords =     "genetic algorithms, genetic programming, Data mining,
                 Machine learning, Diagnostic model evaluation, Model
                 structure uncertainty, Parsimonious inductive model,
                 Data-based modelling, Dominant process concept",
  abstract =     "Genetic Programming is able to systematically explore
                 many alternative model structures of different
                 complexity from available input and response data. We
                 hypothesised that Genetic Programming can be used to
                 test the structure of hydrological models and to
                 identify dominant processes in hydrological systems. To
                 test this, Genetic Programming was used to analyse a
                 data set from a lysimeter experiment in southeastern
                 Australia. The lysimeter experiment was conducted to
                 quantify the deep percolation response under surface
                 irrigated pasture to different soil types, water table
                 depths and water ponding times during surface
                 irrigation. Using Genetic Programming, a simple model
                 of deep percolation was recurrently evolved in multiple
                 Genetic Programming runs. This simple and interpretable
                 model supported the dominant process contributing to
                 deep percolation represented in a conceptual model that
                 was published earlier. Thus, this study shows that
                 Genetic Programming can be used to evaluate the
                 structure of hydrological models and to gain insight
                 about the dominant processes in hydrological systems.",
}

Genetic Programming entries for Benny Selle Nitin Muttil

Citations