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Urban flood modelling combining cellular automata framework with semi-implicit finite difference numerical formulation

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Urban flood modelling combining cellular automata framework with semi-implicit finite difference numerical formulation. / Nkwunonwo, U. C.; Whitworth, Malcolm; Baily, Brian.

In: Journal of African Earth Sciences, 15.11.2018.

Research output: Contribution to journalArticlepeer-review

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@article{6857f7baf8a043b4889e6035ebcf1a20,
title = "Urban flood modelling combining cellular automata framework with semi-implicit finite difference numerical formulation",
abstract = "Urban flooding is increasingly pervasive, with dreadful impacts on people and development assets. Whilst the frequency of occurrence of this hazard, mainly from pluvial events, is of fundamental importance in climate change and earth sciences research, the severity of its impacts motivates major debates within the context of flood risk management and sustainable urban development. The present study focuses on the development of a novel flood model, as a contribution to meeting the challenges of flood risk assessment within data poor urban areas such as in Nigeria. The new model combines the full functionality of cellular automata (CA) framework with a semi-implicit finite difference numerical scheme (SIFDS), whilst the resulting algorithms were programmed within MATLABTM programming platform. In this study, computation complexity and distributed topographic data requirement, both which are associated with flood modelling, and which tend to present a major limitation to flood modelling in the developing countries (DCs) are being addressed. A highly urbanized area within the Lagos metropolis of Nigeria was chosen as a case study to validate the model and to simulate the July 10th 2011 flooding event. A 2-m horizontal resolution LiDAR DEM, published Manning's friction coefficients and rainfall intensity, were used as data inputs into the new flood model. Simulated results compared well with actual flooding inundations, reported by urban residents, and detailed in some literature and by the media. The Pearson correlation coefficient (r) between predicted flood depth and estimated values is 0.968. It is expected that the challenges of urban flooding in Lagos particularly and in the DCs generally will be better addressed if robust, but low-cost flood models are developed and utilized in the assessment of flood damage.",
keywords = "Urban flooding, Semi-implicit finite difference scheme, Cellular automata, Flood risk assessment, Flood modelling",
author = "Nkwunonwo, {U. C.} and Malcolm Whitworth and Brian Baily",
year = "2018",
month = nov,
day = "15",
doi = "10.1016/j.jafrearsci.2018.10.016",
language = "English",
journal = "Journal of African Earth Sciences",
issn = "1464-343X",
publisher = "Elsevier Limited",

}

RIS

TY - JOUR

T1 - Urban flood modelling combining cellular automata framework with semi-implicit finite difference numerical formulation

AU - Nkwunonwo, U. C.

AU - Whitworth, Malcolm

AU - Baily, Brian

PY - 2018/11/15

Y1 - 2018/11/15

N2 - Urban flooding is increasingly pervasive, with dreadful impacts on people and development assets. Whilst the frequency of occurrence of this hazard, mainly from pluvial events, is of fundamental importance in climate change and earth sciences research, the severity of its impacts motivates major debates within the context of flood risk management and sustainable urban development. The present study focuses on the development of a novel flood model, as a contribution to meeting the challenges of flood risk assessment within data poor urban areas such as in Nigeria. The new model combines the full functionality of cellular automata (CA) framework with a semi-implicit finite difference numerical scheme (SIFDS), whilst the resulting algorithms were programmed within MATLABTM programming platform. In this study, computation complexity and distributed topographic data requirement, both which are associated with flood modelling, and which tend to present a major limitation to flood modelling in the developing countries (DCs) are being addressed. A highly urbanized area within the Lagos metropolis of Nigeria was chosen as a case study to validate the model and to simulate the July 10th 2011 flooding event. A 2-m horizontal resolution LiDAR DEM, published Manning's friction coefficients and rainfall intensity, were used as data inputs into the new flood model. Simulated results compared well with actual flooding inundations, reported by urban residents, and detailed in some literature and by the media. The Pearson correlation coefficient (r) between predicted flood depth and estimated values is 0.968. It is expected that the challenges of urban flooding in Lagos particularly and in the DCs generally will be better addressed if robust, but low-cost flood models are developed and utilized in the assessment of flood damage.

AB - Urban flooding is increasingly pervasive, with dreadful impacts on people and development assets. Whilst the frequency of occurrence of this hazard, mainly from pluvial events, is of fundamental importance in climate change and earth sciences research, the severity of its impacts motivates major debates within the context of flood risk management and sustainable urban development. The present study focuses on the development of a novel flood model, as a contribution to meeting the challenges of flood risk assessment within data poor urban areas such as in Nigeria. The new model combines the full functionality of cellular automata (CA) framework with a semi-implicit finite difference numerical scheme (SIFDS), whilst the resulting algorithms were programmed within MATLABTM programming platform. In this study, computation complexity and distributed topographic data requirement, both which are associated with flood modelling, and which tend to present a major limitation to flood modelling in the developing countries (DCs) are being addressed. A highly urbanized area within the Lagos metropolis of Nigeria was chosen as a case study to validate the model and to simulate the July 10th 2011 flooding event. A 2-m horizontal resolution LiDAR DEM, published Manning's friction coefficients and rainfall intensity, were used as data inputs into the new flood model. Simulated results compared well with actual flooding inundations, reported by urban residents, and detailed in some literature and by the media. The Pearson correlation coefficient (r) between predicted flood depth and estimated values is 0.968. It is expected that the challenges of urban flooding in Lagos particularly and in the DCs generally will be better addressed if robust, but low-cost flood models are developed and utilized in the assessment of flood damage.

KW - Urban flooding

KW - Semi-implicit finite difference scheme

KW - Cellular automata

KW - Flood risk assessment

KW - Flood modelling

U2 - 10.1016/j.jafrearsci.2018.10.016

DO - 10.1016/j.jafrearsci.2018.10.016

M3 - Article

JO - Journal of African Earth Sciences

JF - Journal of African Earth Sciences

SN - 1464-343X

ER -

ID: 12197282