Comparative Analysis of Data-Driven and GIS-Based Conceptual Rainfall-Runoff Model

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@Article{Jayawardena:2006:JHE,
  author =       "A. W. Jayawardena and N. Muttil and J. H. W. Lee",
  title =        "Comparative Analysis of Data-Driven and GIS-Based
                 Conceptual Rainfall-Runoff Model",
  journal =      "Journal of Hydrologic Engineering",
  year =         "2006",
  volume =       "11",
  number =       "1",
  pages =        "1--11",
  month =        jan # "/" # feb,
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1061/(ASCE)1084-0699(2006)11:1(1))",
  abstract =     "Modelling of the rainfall-runoff process is important
                 in hydrology. Historically, researchers relied on
                 conventional deterministic modeling techniques based
                 either on the physics of the underlying processes, or
                 on the conceptual systems which may or may not mimic
                 the underlying processes. This study investigates the
                 suitability of a conceptual technique along with a
                 data-driven technique, to model the rainfall-runoff
                 process. The conceptual technique used is based on the
                 Xinanjiang model coupled with geographic information
                 system (GIS) for runoff routing and the data-driven
                 model is based on genetic programming (GP), which was
                 used for rainfall-runoff modelling in the recent past.
                 To verify GP's capability, a simple example with a
                 known relation from fluid mechanics is considered
                 first. For a small, steep-sloped catchment in Hong
                 Kong, it was found that the conceptual model
                 outperformed the data-driven model and provided a
                 better representation of the rainfall-runoff process in
                 general, and better prediction of peak discharge, in
                 particular. To demonstrate the potential of GP as a
                 viable data-driven rainfall-runoff model, it is
                 successfully applied to two catchments located in
                 southern China.",
  notes =        "c ASCE",
}

Genetic Programming entries for A W Jayawardena Nitin Muttil Joseph Hun-wei Lee

Citations