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

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@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

Citations