E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||9|
|Section||Policy appraisal, investment planning and decision making tools|
|Published online||20 October 2016|
Design criteria for flood-defense structures based on probabilistic cost-benefit optimization with value at risk (VaR) methods. Application to the Choluteca River in Tegucigalpa (Honduras)
1 Environmental Hydraulics Institute “IH Cantabria”. Parque Científico y Tecnológico de Cantabria, C/ Isabel Torres, 15, 39011 Santander, Cantabria. Spain
2 Independent consultant, C/ Honduras 1, 13160 Torralba de Calatrava, Ciudad Real, Spain
a Corresponding author: firstname.lastname@example.org
A probabilistic CBA framework, combined with a Value at risk (VaR) methods, as applied in financial risk management, can be used to select the best mitigation scheme among several alternatives and reliability levels, based on a quantitative and objective procedure. The proposed method looks for the alternative that minimizes the accumulated maximum damage that can be produce by any particular sequence of events, over the life span of the structure, using numerical simulation and possibly including interactions among individual events (two large floods within a short time cannot damage twice the same assets). This is equivalent to a stochastic optimization problem, where the entity to be minimized are the maximum losses. The optimal alternative, based on a VaR criteria (including conditional VaR), differs largely from the one that maximizes the average NPV, and is more stable, compared with the average or a deterministic NPV. To demonstrate the proposed procedure, and show the differences among the three performance indicators (average NPV, VaR and CVaR), the case of the Choluteca River in Tegucigalpa, capital city of Honduras, are used, with real data of economic and human damages provided by a recent study by IDB.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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