A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Use of Multiobjective Evolutionary Algorithm Optimization for Low-Impact Development Placement
The transformation of natural land cover to urban areas severely alters the hydrologic flow regime of watersheds. The negative impacts include the increase of surface runoff and decrease of infiltration rates, which can result in more frequent and intense flood events and the reduction of groundwater recharge. Low-impact developments (LIDs) are strategies designed to better mimic the natural flow regime by promoting higher infiltration and the treatment of stormwater. Examples of LID structures are bio-gardens, green roofs, bio-swales, and pervious pavements. While the expansion of LIDs in urban catchments would be desirable, retrofitting large urban watersheds with LIDs can be cost prohibitive. This study combines hydrologic simulation with a multiobjective evolutionary algorithm (MOEA) to find solutions in terms of LID design and location in urban catchments that maximize the environmental benefits and characterize the tradeoffs between LID performance indicators and costs. The solutions are evaluated in terms of costs, peak flow, and the hydrologic footprint residence (HFR). The HFR is a new metric designed to quantify the impacts of urbanization in the hydrologic regime by representing the dynamics of inundated areas and residence time of flood waves. The results provide a basis for better stormwater management and planning because tradeoff curves provide a wider spectrum of designs and placement guidelines, improving the sustainability of urban watersheds.
Use of Multiobjective Evolutionary Algorithm Optimization for Low-Impact Development Placement
The transformation of natural land cover to urban areas severely alters the hydrologic flow regime of watersheds. The negative impacts include the increase of surface runoff and decrease of infiltration rates, which can result in more frequent and intense flood events and the reduction of groundwater recharge. Low-impact developments (LIDs) are strategies designed to better mimic the natural flow regime by promoting higher infiltration and the treatment of stormwater. Examples of LID structures are bio-gardens, green roofs, bio-swales, and pervious pavements. While the expansion of LIDs in urban catchments would be desirable, retrofitting large urban watersheds with LIDs can be cost prohibitive. This study combines hydrologic simulation with a multiobjective evolutionary algorithm (MOEA) to find solutions in terms of LID design and location in urban catchments that maximize the environmental benefits and characterize the tradeoffs between LID performance indicators and costs. The solutions are evaluated in terms of costs, peak flow, and the hydrologic footprint residence (HFR). The HFR is a new metric designed to quantify the impacts of urbanization in the hydrologic regime by representing the dynamics of inundated areas and residence time of flood waves. The results provide a basis for better stormwater management and planning because tradeoff curves provide a wider spectrum of designs and placement guidelines, improving the sustainability of urban watersheds.
Use of Multiobjective Evolutionary Algorithm Optimization for Low-Impact Development Placement
Giacomoni, Marcio H. (author)
International Low Impact Development 2015 ; 2015 ; Houston, Texas
2015-01-12
Conference paper
Electronic Resource
English
A multiobjective evolutionary algorithm for surveillance sensor placement
| Online Contents | 2008
| British Library Online Contents | 2009
Adaptive Bilevel Approximation Technique for Multiobjective Evolutionary Optimization
| Online Contents | 2016
Constraint-handling Using an Evolutionary Multiobjective Optimization Technique
| Online Contents | 2000