Genetic programming approach for flood routing in natural channels

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  author =       "C. Sivapragasam and R. Maheswaran and 
                 Veena Venkatesh",
  title =        "Genetic programming approach for flood routing in
                 natural channels",
  journal =      "Hydrological Processes",
  year =         "2007",
  volume =       "22",
  number =       "5",
  pages =        "623--628",
  keywords =     "genetic algorithms, genetic programming, Muskingum
                 method, flood routing",
  DOI =          "doi:10.1002/hyp.6628",
  size =         "6 pages",
  abstract =     "In recognition of the non-linear relationship between
                 storage and discharge existing in most river systems,
                 non-linear forms of the Muskingum model have been
                 proposed, together with methods to calibrate the model
                 parameters. However, most studies have focused only on
                 routing a typical hypothetical flood hydrograph
                 characterised by a single peak. In this study, we
                 demonstrate that the storage-discharge relationship
                 adopted for the non-linear Muskingum model is not
                 adequate for routing flood hydrographs in natural
                 channels, which are often characterized by multiple
                 peaks. As an alternative, an evolutionary
                 algorithm-based modelling approach, i.e. genetic
                 programming (GP), is proposed, which is found to route
                 complex flood hydrographs accurately. The proposed
                 method is applied for constructing a routing model for
                 a channel reach along the Walla Walla River, USA. The
                 GP model performs extremely well with a
                 root-mean-square error (RMSE) of 0.73 m3/s as against
                 an RMSE of 3.26 m3/s for routing the multi-peaked
                 hydrograph. The advantage of GP lies in the fact that,
                 unlike other models, it establishes the routing
                 relationship in an easy and simple mathematical form.",
  notes =        "See also \cite{Alavi:2010:HP}.

                 Department of Civil Engineering, Mepco Schlenk
                 Engineering College, Sivakasi 626 005, Tamilnadu State,
                 India; Department of Civil Engineering, Kalasalingam
                 University, Anand nagar, Krishnan Koil, Srivilliputtur
                 (Taluk), Virudunagar (District), Tamilnadu - 626 190",

Genetic Programming entries for C Sivapragasam Rathinasamy Maheswaran Veena Venkatesh