An Intelligent Decision Support System for Management of Floods |
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Authors: | Sajjad Ahmad Slobodan P Simonovic |
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Affiliation: | (1) Department of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, FL, 33146-0630, U.S.A.;(2) Department of Civil and Environmental Engineering, University of Western Ontario, London, ON, N6A 5B9, Canada |
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Abstract: | Integrating human knowledge with modeling tools, an intelligent decision support system (DSS) is developed to assist decision
makers during different phases of flood management. The DSS is developed as a virtual planning tool and can address both engineering
and non-engineering issues related to flood management. Different models (hydrodynamic, forecasting, and economic) that are
part of the DSS share data and communicate with each other by providing feedback. The DSS is able to assist in: selecting
suitable flood damage reduction options (using an expert system approach); forecasting floods (using artificial neural networks
approach); modeling the operation of flood control structures; and describing the impacts (area flooded and damage) of floods
in time and space. The proposed DSS is implemented for the Red River Basin in Manitoba, Canada. The results from the test
application of DSS for 1997 flood in the Red River Basin are very promising. The DSS is able to predict the peak flows with
2% error and reveals that with revised operating rules the contribution of Assiniboine River to the flooding of Winnipeg city
can be significantly reduced. The decision support environment allows a number of “what-if” type questions to be asked and
answered, thus, multiple decisions can be tried without having to deal with the real life consequences. |
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Keywords: | artificial neural networks decision support system flood forecasting flood management reservoir operation Red River system dynamics |
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