Urban Flood Management Through Optimization-Simulation Framework for Low Impact Development Controls
Abstract
Increased urbanization stresses urban stormwater management systems and consequently urban watersheds. Development alters the water balance, decreasing infiltration and consequently groundwater recharge while also increasing stormwater runoff. A changing climate magnifies these impacts as increased rainfall creates increased runoff that directly enters the stormsewer system.
The conventional approach to urban stormwater management has been to convey the stormwater through a centralized system as quickly and safely as possible. This approach generally does not contribute to sustainable urban development. The objectives of modern stormwater management are changing to include protecting water quality, maintaining the health of aquatic ecosystems and utilizing stormwater as a resource. This is consistent with a desire for development which is ecologically, economically, and socially sustainable. Low impact development (LID) is an approach to stormwater management, which is gaining popularity, especially as a climate change adaptation strategy. LID provides improvements in stormwater management and when used in combination with current stormwater infrastructure can help restore developed areas to their pre-development hydrologic conditions. The LID philosophy incorporates various types of green infrastructure, natural features, and ecologically considerate development planning in order to improve hydrological systems impacted by urban stormwater. The objective of this research was to develop a mathematical model to optimize low impact development alternatives to improve the resilience of stormwater infrastructure against climate change conditions and thus further their application in urban developments. To accomplish this an optimization-simulation model was created by coupling a stormwater management model (PCSWMM) with a genetic algorithm. Genetic algorithms can be linked to simulation models and are used to optimize multiple objectives. For this study the Borg Multiobjective Evolutionary Algorithm (Borg MOEA) was used. The results from this research can contribute to the development of optimal designs for stormwater management combined with green infrastructure. These results with also assist in improving environmental sustainability of critical infrastructure.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H43J2610M
- Keywords:
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- 1821 Floods;
- HYDROLOGYDE: 1834 Human impacts;
- HYDROLOGYDE: 1840 Hydrometeorology;
- HYDROLOGYDE: 1847 Modeling;
- HYDROLOGY