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Developing a cellular automata model of urban growth to inform spatial policy for flood mitigation

Authors :
Johannes Flacke
Richard Sliuzas
Eduardo Pérez-Molina
Victor Jetten
Department of Urban and Regional Planning and Geo-Information Management
UT-I-ITC-PLUS
University of Twente
Faculty of Geo-Information Science and Earth Observation
Department of Earth Systems Analysis
UT-I-ITC-4DEarth
Source :
Computers, environment and urban systems, 65, 53-65. Elsevier
Publication Year :
2017

Abstract

Urban growth may intensify local flooding problems. Understanding the spatially explicit flood consequences of possible future land cover patterns contributes to inform policy for mitigating these impacts. A cellular automata model has been coupled with the openLISEM integrated flood modeling tool to simulate scenarios of urban growth and their consequent flood; the urban growth model makes use of a continuous response variable (the percentage of built-up area) and a spatially explicit simulation of supply for urban development. The models were calibrated for Upper Lubigi (Kampala, Uganda), a sub-catchment that experienced rapid urban growth during 2004–2010; this data scarce environment was chosen in part to test the model's performance with data inputs that introduced important uncertainty. The cellular automata model was validated in Nalukolongo (Kampala, Uganda). The calibrated modeling ensemble was then used to simulate urban growth scenarios of Upper Lubigi for 2020. Two scenarios, trend conditions and a policy of strict protection of existing wetlands, were simulated. The results of simulated scenarios for Upper Lubigi show how a policy of only protecting wetlands is ineffective; further, a substantial increase of flood impacts, attributable to urban growth, should be expected by 2020. The coupled models are operational with regard to the simulation of dynamic feedbacks between flood and suitability for urban growth. The tool proved useful in generating meaningful scenarios of land cover change and comparing their policy drivers as flood mitigation measures in a data scarce environment.

Details

Language :
English
ISSN :
01989715
Volume :
65
Database :
OpenAIRE
Journal :
Computers, environment and urban systems
Accession number :
edsair.doi.dedup.....2a68bb16733a0575510d1cb00a503460