A new LID spatial allocation optimization system at neighborhood scale: Integrated SWMM with PICEA-g using MATLAB as the platform

Multi-objective optimization of the spatial layout of green infrastructures with cost-effectiveness analysis under climate change scenarios

Green infrastructure (GI) plays a significant role in alleviating urban flooding risk caused by urbanization and climate change. Due to space and financial limitations, the successful implementation of GI relies heavily on its layout design, and there is an increasing trend in using multi-objective optimization to support decision-making in GI planning. However, little is known about the hydrological effects of synchronously optimizing the size, location, and connection of GI under climate change. This study proposed a framework to optimize the size, location, and connection of typical GI facilities under climate change by combining the modified non-dominated sorting genetic algorithm-II (NSGA-II) and storm water management model (SWMM). The results showed that optimizing the size, location, and connection of GI facilities significantly increases the maximum reduction rate of runoff and peak flow by 13.4 %-24.5 % and 3.3 %-18 %, respectively, compared to optimizing only the size and location of GI. In the optimized results, most of the runoff from building roofs flew toward green space. Permeable pavement accounted for the highest average proportion of GI implementation area in optimal layouts, accounting for 29.8 %-54.2 % of road area. The average cost-effectiveness (C/E) values decreased from 16 %/105 Yuan under the historical period scenario to 14.3 %/105 Yuan and 14 %/105 Yuan under the two shared socioeconomic pathways (SSPs), SSP2-4.5 and SSP5-8.5, respectively. These results can help in understanding the optimization layout and cost-effectiveness of GI under climate change, and the proposed framework can enhance the adaptability of cities to climate change by providing specific cost-effective GI layout design.

First flush stormwater pollution in urban catchments: A review of its characterization and quantification towards optimization of control measures

Identification, quantification, and control of First-Flush (FF) are considered extremely crucial in urban stormwater management. This paper reviews the methods for FF phenomenon identification, characteristics of pollutants flushes, technologies for FF pollution control, and the relationships among these factors. It further discusses FF quantification methods and optimization of control measures, aiming to reveal directions for future studies on FF management. Results showed that statistical analyses and Runoff Pollutographs Applying Curve (RPAC) fitting modelling of wash-off processes are the most applicable FF identification methods currently available. Furthermore, deep insights into the pollutant mass flushing of roof runoff may be a critical approach to characterizing FF stormwater. Finally, a novel strategy for FF control is established comprising multi-stage objectives, coupling LID/BMPs optimization schemes and Information Feedback (IF) mechanisms, aiming towards its application for the management of urban stormwater at the watershed scale.

Calculating the Environmental Impacts of Low-Impact Development Using Long-Term Hydrologic Impact Assessment: A Review of Model Applications

Low-impact development (LID) is a planning and design strategy that addresses water quality and quantity while providing co-benefits in the urban and suburban landscape. The Long-Term Hydrologic Impact Assessment (L-THIA) model estimates runoff and pollutant loadings using simple inputs of land use, soil type, and climatic data for the watershed-scale analysis of average annual runoff based on curve number analysis. Using Scopus, Web of Science, and Google Scholar, we screened 303 articles that included the search term "L-THIA", identifying 47 where L-THIA was used as the primary research method. After review, articles were categorized on the basis of the primary purpose of the use of L-THIA, including site screening, future scenarios and long-term impacts, site planning and design, economic impacts, model verification and calibration, and broader applications including policy development or flood mitigation. A growing body of research documents the use of L-THIA models across landscapes in applications such as the simulations of pollutant loadings for land use change scenarios and the evaluation of designs and cost-effectiveness. While the existing literature demonstrates that L-THIA models are a useful tool, future directions should include more innovative applications such as intentional community engagement and a focus on equity, climate change impacts, and the return on investment and performance of LID practices to address gaps in knowledge.

A Multiobjective Spatial Optimization Model of LID Based on Catchment Landuse Type

Aiming to solve the problem of the low efficiency and single objective of low impact development (LID) layout, the objectives of stormwater control, water quality purification, and economic cost are selected to present the performance of LID practices. A novel method of evaluating urban runoff and pollutant concentration is put forward based on the land-use type of each catchment. Shenzhen City is selected as the study area, and three LID scenarios are designed and contrasted for an ideal solution according to their land-use type. The results show that the multiobjective optimization model based on runoff evaluation, pollutant simulation, and investment calculation can be more efficient and can be applied in other areas.