Towards efficient Low Impact Development: A multi-scale simulation-optimization approach for nutrient removal at the urban watershed
Towards efficient Low Impact Development: A multi-scale simulation-optimization approach for nutrient removal at the urban watershed
复制标题
迈向高效低影响发展：城市流域养分去除的多尺度模拟优化方法
DOI：
10.1016/j.jclepro.2020.122295
复制
发表时间：
2020-10-01
影响因子：
11.1
通讯作者：
Guo, Huaicheng
中科院分区：
文献类型：
--
作者：
Dong, Feifei;Zhang, Zhenzhen;Guo, Huaicheng
在这项研究中，我们提出了一个低影响开发（LID）的多尺度建模框架，通过整合(i)地方尺度的低影响开发（LID）成本效益分析，（ii）景观尺度的管理类别（MC）分类和LID选择，以及（iii）宏观尺度的综合决策。滇池是中国三大富营养化湖泊之一，昆明市区域流域向滇池排放了大量城市面源污染，利用该框架减少了该流域的总磷（TP）损失。使用城市雨水处理和分析集成系统（SUSTAIN）工具进行局地尺度模拟优化，以优化候选LID实践的规模和数量。采用非支配排序遗传算法II （NSGA-II）求解优化问题。地方尺度的LID策略最终在宏观尺度上得到整合，符合水质标准。我们的分析表明，由于边际效益递减规律，实施LID的边际效益随着TP减少的增加而急剧下降。由于单位成本变异系数（cv）大多在10%以下，同一MC下不同情景的面积成本-效果曲线具有相似性。不同流域的覆盖率在2.3% ~ 24.7%之间，而不同流域的覆盖率在不同的面积范围内基本一致，因此，LID实施的空间变异性受景观差异的影响比受流域面积差异的影响更显著。与传统的全流域模拟优化相比，多尺度决策框架将模型运行次数从923次减少到23次，显著提高了计算效率。(C) 2020 Elsevier Ltd.版权所有。
In this study, we proposed a multi-scale modelling framework for Low Impact Development (LID) by integrating (i) local-scale LID cost-effectiveness analysis, (ii) landscape-scale Management Category (MC) classification and LID selection, and (iii) macro-scale integrative decision making. The framework was used for sitting LID to reduce Total Phosphorus (TP) loss in the City Kunming regional watershed, which discharges massive urban Non-Point Source (NPS) pollution to Lake Dianchi, one of the three most eutrophic large lakes in China. Local-scale simulation-optimization was performed to optimize the sizes and quantities of the candidate LID practices with the System for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) tool. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used to solve the optimization problem. The local-scale LID strategies were ultimately integrated at the macro scale in compliance with the water quality standards. Our analysis suggests that the marginal benefits of LID implementation decline dramatically with increasing TP abatement attributed to the law of Diminishing Marginal Benefits. The areal cost-effectiveness curves of different scenarios resemble each other for the same MC since the Coefficients of Variation (CVs) of unit costs are mostly below 10%. Spatial variability of LID implementation is more prominently affected by disparities of landscapes than drainage area sizes because the coverage ratios among different MCs vary from 2.3% to 24.7% whereas they resemble each other among different area sizes. The multi-scale decision-making framework could dramatically improve computational efficiency by reducing the model runs from 923 to 23 compared to the conventional full-watershed simulation-optimization. (C) 2020 Elsevier Ltd. All rights reserved.