Economic Analysis of Flood Risk Applied to the Rehabilitation of Drainage Networks

Over time, cities have grown, developing various activities and accumulating important economic assets. Floods are a problem that worry city administrators who seek to make cities more resilient and safer. This increase in flood events is due to different causes: poor planning, population increase,...

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Bibliographic Details
Published in:Water (Basel) Vol. 14; no. 18; p. 2901
Main Authors: Bayas-Jiménez, Leonardo, Martínez-Solano, F. Javier, Iglesias-Rey, Pedro L., Boano, Fulvio
Format: Journal Article
Language:English
Published: Basel MDPI AG 16.09.2022
Subjects:
algorithms
climate change
Costs
Drainage
economic analysis
Efficiency
Flood damage
Floods
Genetic algorithms
Hydraulics
Infrastructure
Methods
Optimization
population growth
psychological stress
Rain
Rehabilitation
risk
soil
Storm damage
storms
Urban areas
urbanization
water
ISSN:2073-4441, 2073-4441
Online Access:Get full text
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Summary:Over time, cities have grown, developing various activities and accumulating important economic assets. Floods are a problem that worry city administrators who seek to make cities more resilient and safer. This increase in flood events is due to different causes: poor planning, population increase, aging of networks, etc. However, the two main causes for the increase in urban flooding are the increment in frequency of extreme rainfall, generated mainly by climate change, and the increase in urbanized areas in cities, which reduce green areas, decreasing the percentage of water that seeps naturally into the soil. As a contribution to solve these problems, the work presented shows a method to rehabilitate drainage networks that contemplates implementing different actions in the network: renovation of pipes, construction of storm tanks and installation of hydraulic controls. This work focuses on evaluating the flood risk in economic terms. To achieve this, the expected annual damage from floods and the annual investments in infrastructure to control floods are estimated. These two terms are used to form an objective function to be minimized. To evaluate this objective function, an optimization model is presented that incorporates a genetic algorithm to find the best solutions to the problem; the hydraulic analysis of the network is performed with the SWMM model. This work also presents a strategy to reduce computation times by reducing the search space focused mainly on large networks. This is intended to show a complete and robust methodology that can be used by managers and administrators of drainage networks in cities.
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ISSN:2073-4441
2073-4441
DOI:10.3390/w14182901