Research on optimization method for LID controls distribution of greenspace in shallow mountain based on D8 and NSGA-Ⅱ algorithm
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摘要:
目的 雨洪问题已经成为浅山区发展的关键制约因素，绿地低影响开发是解决浅山区雨洪问题的重要手段，构建一套面向径流控制效果、建设成本等多元目标的低影响开发设施的布局优化方法，能够为浅山区雨洪问题的高效解决提供重要技术支持，有助于浅山区的未来高质量发展。 方法 研究从浅山区绿地规划设计特征与径流特点入手，耦合D8与NSGA-Ⅱ算法，构建基于栅格数据的低影响开发布局优化平台，实现了协同径流控制效果与建设成本优化的低影响开发设施类型、规模空间量化布局，并将石家庄西山郊野公园作为实验对象，以验证方法的可行性。 结果 分别在重现期5、10和20年2 h降雨模拟情景中，得到实验对象低影响开发设施布局优化解集24、30和30个，并识别得到各模拟情景LID设施建设的“理想投资上限点”：7 514.1、6 634.4和6 065.1万元；在ArcGIS可视化各模拟情景所得“理想投资上限点”对应的LID设施布局方案，发现雨水花园、透水铺装、调蓄水体呈散点状分布，植草沟呈分散的小规模线性分布。 结论 D8与NSGA-Ⅱ耦合算法能够良好地匹配浅山区绿地的低影响开发情景，简化了传统绿地低影响开发繁琐的设计流程；实验结果表明，径流峰值流量与LID设施成本存在边际递减效益，且随着降雨重现期增大，边际递减效益加快；相对其他LID设施，透水铺装与雨水花园的建设性价更高；实验对象的可视化模拟结果基本符合设计原理与真实设计情景，能够良好地指导规划设计；未来应重点探究低影响开发设施布局优化与绿地规划设计的协同方法，同步规划设计方案以置入必要的约束条件，从而提升设施布置结果的合理性和指导性。 Abstract:Objective The stormwater problem has become a key restrictive factor for the development of shallow mountain areas and the low impact development (LID) of green space is an important means to solve such problem in shallow mountain areas. Forming an optimization method for LID controls distribution, for multi-objective such as runoff control and cost, can provide important technical support for the efficient solution of stormwater problems in shallow mountain areas, and contribute to the future high-quality development of this areas. Method Based on the characteristics of green space planning and design and runoff in shallow mountain area, the study forms a platform for optimal distribution of LID controls by D8 and NSGA-Ⅱ coupled algorithm, which realizes spatial quantitative optimization of the type and scale of LID controls based on collaborative optimization of runoff control and cost, in addition, Westmount country park in Shijiazhuang city is taken as the experimental object to verify the feasibility of the method. Result 24, 30 and 30 optimal solution sets for the optimal distribution of LID controls of experimental object are got in the simulated2-hour rainfall event under return periods of 5-year, 10-year and 20-year; The ‘ideal investment upper limit point’ of each simulated rainfall event is 75.141 million yuan, 66.344 million yuan and 60.651 million yuan respectively; Visual results of the distribution of most efficient cost based on ArcGIS show that raingarden, permeable pavement and water are scattered, and vegetative swale is scattered in small-scale linear distribution. Conclusion D8 and NSGA-Ⅱ coupled algorithm can well match the LID of green space in shallow mountain area, and simplify the cumbersome design process of LID in traditional green space; there is marginal diminishing benefit between peak flow of runoff and LID controls cost, which accelerates with the increase of rainfall return period; the permeable pavement and raingarden have more cost performance than other LID controls; the visual simulation results of the experimental object basically accord with the principle and pattern in real design, which verifies the feasibility and rationality of the method; in order to improve the rationality and guidance of simulated results of distribution, the further research should focus on the collaborative method for optimal distribution of LID controls and green space planning and design. -
Key words:
- shallow mountain /
- LID /
- multi-objective optimization method /
- NSGA-Ⅱ /
- landscape architecture
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图 3 基于NSGA-Ⅱ的LID设施优化布局选择
Figure 3. Decision-making of optimal distribution of LID controls
图 6 不同2 h降雨模拟情景LID设施优化布局解集
Figure 6. Solution set of optimal distribution of LID controls of different 2 hour-rainfall simulated event
图 7 不同2 h降雨情景LID设施建设理想投资区间
Figure 7. Ideal investment interval of LID controls of different 2 hour-rainfall simulated event
图 8 不同2 h降雨模拟情景成本最优LID设施布局结果
Figure 8. Results of distribution of LID controls of most cost-effective of different 2 hour-rainfall simulated event .
表 1 下游栅格坐标换算表
Table 1. Coordinate conversion table of downstream raster
坐标 coordinate 上游栅格
upstream raster下游栅格 downstream raster 正东
east正南
south正西
west正北
north东南
southeast东北
northeast西南
southwest西北
southwest横坐标X coordinate X x x + a x x − a x x + a x + a x − a x − a 纵坐标Y coordinate Y y y y − a y y + a y − a y + a y − a y + a 注：a为单位栅格精度。Note: a is the unit raster size. 
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表 2 LID设施参数设置表
Table 2. Table of parament of LID controls
LID设施名称
LID controlLID设施主要SWMM模型参数
Main parament of LID controls in SWMM单位成本/（元·m−2）
Unit cost /(yuan·m−2)雨水花园
Raingarden表面
Surface深度400 mm 植被覆盖0.3 表面粗糙系数0.4 表面坡度0.3Height 400 mm Vegetation volume fraction 0.3 Surface roughness 0.1 Surface slope 0.3 600 土壤
Soil厚度300 mm 孔隙率0.5 产水能力0.2 枯萎点0.1 导水率10 mm/h 导水坡度10 吸水头88.9 mmThickness 300 mm Porosity 0.5 Field capacity 0.2 Wilting point 0.1 Conductivity 10 Conductivity slope 10 suction head 88.9 透水铺装
Permeable pavement表面
Surface深度5 mm 表面粗糙系数0.01 表面坡度0.3Height 5 mm Surface roughness 0.01 Surface slope 0.3 260 土壤
Soil厚度150 mm孔隙率0.25导水率800 mm/hThickness 150 mm Porosity 0.25 Conductivity 800 mm/h 蓄水
Storage厚度300 mm 孔隙比0.5 渗透率1.8 mm/hThickness 300 mm Void ratio 0.5 Seepage rate 1.8 mm/h 调蓄水体
Water蓄水
Storage深度 300 mm
Height 300 mm530 植草沟
Vegetative swale表面
Surface深度300 mm 植被覆盖0.2 表面粗糙系数0.3 表面坡度0.3Height 300 mm Vegetation volume fraction 0.2 Surface roughness 0.3 Surface slope 0.3 150 土壤
Soil厚度300 mm
Thickness 300 mm
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