Development of a modular streamflow model to quantify runoff contributions from different land uses in tropical urban environments using Genetic Programming

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@Article{Meshgi:2015:JH,
  author =       "Ali Meshgi and Petra Schmitter and 
                 Ting Fong May Chui and Vladan Babovic",
  title =        "Development of a modular streamflow model to quantify
                 runoff contributions from different land uses in
                 tropical urban environments using Genetic Programming",
  journal =      "Journal of Hydrology",
  volume =       "525",
  pages =        "711--723",
  year =         "2015",
  ISSN =         "0022-1694",
  DOI =          "doi:10.1016/j.jhydrol.2015.04.032",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0022169415002917",
  abstract =     "Summary The decrease of pervious areas during
                 urbanization has severely altered the hydrological
                 cycle, diminishing infiltration and therefore
                 sub-surface flows during rainfall events, and further
                 increasing peak discharges in urban drainage
                 infrastructure. Designing appropriate waster sensitive
                 infrastructure that reduces peak discharges requires a
                 better understanding of land use specific contributions
                 towards surface and sub-surface processes. However, to
                 date, such understanding in tropical urban environments
                 is still limited. On the other hand, the
                 rainfall-runoff process in tropical urban systems
                 experiences a high degree of non-linearity and
                 heterogeneity. Therefore, this study used Genetic
                 Programming to establish a physically interpretable
                 modular model consisting of two sub-models: (i) a
                 baseflow module and (ii) a quick flow module to
                 simulate the two hydrograph flow components. The
                 relationship between the input variables in the model
                 (i.e. meteorological data and catchment initial
                 conditions) and its overall structure can be explained
                 in terms of catchment hydrological processes.
                 Therefore, the model is a partial greying of what is
                 often a black-box approach in catchment modelling. The
                 model was further generalized to the sub-catchments of
                 the main catchment, extending the potential for more
                 widespread applications. Subsequently, this study used
                 the modular model to predict both flow components of
                 events as well as time series, and applied optimization
                 techniques to estimate the contributions of various
                 land uses (i.e. impervious, steep grassland, grassland
                 on mild slope, mixed grasses and trees and relatively
                 natural vegetation) towards baseflow and quickflow in
                 tropical urban systems. The sub-catchment containing
                 the highest portion of impervious surfaces (40percent
                 of the area) contributed the least towards the baseflow
                 (6.3percent) while the sub-catchment covered with
                 87percent of relatively natural vegetation contributed
                 the most (34.9percent). The results from the quickflow
                 module revealed average runoff coefficients between
                 0.12 and 0.80 for the various land uses and decreased
                 from impervious (0.80), grass on steep slopes (0.56),
                 grass on mild slopes (0.48), mixed grasses and trees
                 (0.42) to relatively natural vegetation (0.12). The
                 established modular model, reflecting the driving
                 hydrological processes, enables the quantification of
                 land use specific contributions towards the baseflow
                 and quickflow components. This quantification
                 facilitates the integration of water sensitive urban
                 infrastructure for the sustainable development of water
                 in tropical megacities.",
  keywords =     "genetic algorithms, genetic programming, Modular
                 approach, Baseflow, Quickflow, Land use contribution,
                 Tropical urban environments",
}

Genetic Programming entries for Ali Meshgi Petra Schmitter Ting Fong May Chui Vladan Babovic

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