Impact of urban sprawl on future flooding in Chennai city, India

• Published in: Journal of hydrology (Amsterdam) Vol. 574; pp. 486 - 496
• Main Authors: Nithila Devi, N., Sridharan, B., Kuiry, Soumendra Nath
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2019
• Subjects: ANN; Chennai flood; Climate change; Hydrologic-hydraulic modeling; Open source data; Urban sprawl; Open source data; Climate change; ANN; Hydrologic-hydraulic modeling; Urban sprawl; Chennai flood
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2019.04.041

•Simulation of Chennai flood in 2015.•Construction of urban sprawl scenarios for Chennai city using ANN model.•Impact of urban sprawl and increased rainfall on flooding for the Chennai city. The 2015 Chennai (India) flood event claimed many lives and incurred an economic loss of $2.2 billion. Simulation of such a destructive flood event in an ever growing urban sprawl and changing climate is of great importance for better flood preparedness and management of the city. In that light, this study aims to (a) study the 2015 Chennai flood event and (b) simulate the occurrence of a similar event in future, considering both urban sprawl and increased rainfall resulting from climate change effects. The baseline scenario is generated using freely available hydrologic (HEC-HMS)-hydraulic (HEC-RAS) models and the results are validated with observed flood-mark data. Historical land use and land cover maps of the study area are used to train an Artificial Neural Network model for constructing spatially varying urban sprawl scenarios. The hydrologic model is run for the increased rainfall and urban sprawl scenarios to generate flood hydrographs, which are then used as inputs to the hydraulic model for simulating possible flood inundation patterns. The simulations indicate that the average increase in inundation extent considering the worst possible urban sprawl solely, and that taken together with extreme rainfall, are 20 and 33 percent, respectively. Furthermore, the analysis shows that on an average 1.7 times more number of buildings are exposed to flood hazard under the worst case combined scenario in comparison to the baseline scenario. This study, therefore, demonstrates the importance of considering urban sprawl, in addition to changes in rainfall, for evaluating the worst possible consequences of flooding of a city. Considering the uncertainties involved in the study, the presented results may be considered as “what-if” scenarios for planning suitable flood mitigation measures for the city of Chennai.