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,
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author = "Ali Meshgi and Petra Schmitter and
Ting Fong May Chui and Vladan Babovic",
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title = "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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journal = "Journal of Hydrology",
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volume = "525",
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pages = "711--723",
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year = "2015",
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ISSN = "0022-1694",
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DOI = "doi:10.1016/j.jhydrol.2015.04.032",
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URL = "http://www.sciencedirect.com/science/article/pii/S0022169415002917",
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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.",
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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