Article

Modeling and Risk Analysis for Floods due to Failure of Water Control Infrastructures

Associate Director and Research Professor, NCCHE, The University of Mississippi Carrier Hall, P.O. Box 1848; University, 38677, MS, USA; Graduate Student, NCCHE, The University of Mississippi Carrier Hall, P.O. Box 1848; University, 38677, MS, USA; Graduate Student, The University of Mississippi Carrier Hall, P.O. Box 1848, 38677, University, NCCHE, MS, USA; Graduate Student, The University of Mississippi Carrier Hall, P.O. Box 1848, NCCHE; University, 38677, MS, USA
01/2008;

ABSTRACT There are currently about 79,000 dams in the USA. Of these, about 14% are high-hazard dams and 16% are classified as significant hazard dams. Their failure may cause loss-of-life as well as damage to property and infrastructures. According to the National Inventory of Dams (NID), 92% of high-hazard and 67% of significant-hazard dams are required to have an Emergency Action Plan (EAP). Unfortunately, at the moment 48% of high hazard dams and 71% of significant hazard dams do not yet have an EAP. There is an urgent need for the development of efficient, robust, and accurate numerical tools that can be reliably used to perform risk and vulnerability studies for dams by making use of the recent developments in GIS and remote sensing technologies. Most of the dam safety studies to investigate the consequences of catastrophic floods due to failure of water control infrastructures are currently carried out using one-dimensional steady and/or unsteady hydraulic models. A standard approach based on two-dimensional (2D) flood modeling has not yet been adopted. This paper presents an integrated GIS-based Decision Support System (DSS), which uses the results of 2D flood simulation due to dam/levee break/breach simulations to estimate loss-of-life, urban and agricultural property damage by taking into account various types of uncertainties that are involved. Developed at the National Center for Computational Hydroscience and Engineering of the University of Mississippi, this DSS also has additional modules to rank flood management alternatives by using spatial compromise programming, and to track cascading infrastructure failures.

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Jun 5, 2014