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Use of Multi-Objective Evolutionary Algorithm Optimization for Low Impact Development Placement

机译:多目标进化算法优化在低影响开发布局中的应用

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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 Multi-Objective 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.
机译:自然土地覆盖物向城市地区的转变严重改变了流域的水文流态。负面影响包括地表径流的增加和入渗率的降低,这可能导致更频繁,更强烈的洪水事件以及地下水补给的减少。低影响发展(LIDs)是旨在通过促进更高的渗透率和雨水处理来更好地模仿自然流态的策略。 LID结构的示例包括生物花园,绿色屋顶,生物栅栏和透水的人行道。虽然希望在城市集水区扩大LID,但用LID改造大型城市集水区的成本可能会高得令人望而却步。这项研究将水文模拟与多目标进化算法(MOEA)相结合,以在LID设计和城市集水区中的位置方面找到解决方案,从而最大程度地提高环境效益并描述LID性能指标与成本之间的取舍。根据成本,流量峰值和水文足迹驻留(HFR)评估解决方案。 HFR是一种新指标,旨在通过代表淹没区域的动态和洪水波的停留时间来量化城市化对水文状况的影响。该结果为权衡曲线提供了更广泛的设计和布局准则,从而改善了城市集水区的可持续性,为更好的雨水管理和规划提供了基础。

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