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

Yang Yu; Yongchao Zhou; Zhiyong Guo; Bert van Duin; Wenming Zhang

doi:10.1016/j.scitotenv.2022.154843

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

Sci Total Environ. 2022 Jul 20:831:154843. doi: 10.1016/j.scitotenv.2022.154843. Epub 2022 Mar 26.

Authors

Yang Yu¹, Yongchao Zhou², Zhiyong Guo³, Bert van Duin⁴, Wenming Zhang⁵

Affiliations

¹ Dept of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.
² The Institute of Municipal Engineering, Zhejiang University, Hangzhou 310058, China.
³ College of New Energy and Environment, Jilin University, Changchun, 130012, China.
⁴ Dept of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada; Water Resources, City of Calgary, Calgary, AB T2G 4K8, Canada.
⁵ Dept of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada. Electronic address: wenming@ualberta.ca.

PMID: 35351503
DOI: 10.1016/j.scitotenv.2022.154843

Abstract

Despite the growing interest, limited studies have been conducted on LID spatial allocation optimization (SAO) at neighborhood scale, and no study has applied modifications to the optimization algorithm to improve its performance. In this study, such a new LID SAO system was proposed, which integrated a hydrological computing engine (SWMM) with an optimization algorithm (PICEA-g) using a programming language (MATLAB) as the platform. The specific modifications to the PICEA-g algorithm include: new methodologies for initializing candidate solutions, defining goal vector boundaries and enhanced genetic operators. The new LID SAO system was tested in a typical urban residential neighborhood in western Canada, and optimal solutions for LID implementation (bioretention, rain garden, permeable pavement and green roof) were obtained. The results showed that promising hydrologic benefits of reducing peak flow rate and total volume of stormwater runoff from the catchment, can be achieved with a relatively low cost. The LID SAO system provides users with flexibility and feasibility for a variety of drainage locations, scales and objectives (e.g., water quality).

Keywords: Cost-benefit; LID; MATLAB; PICEA-g; SWMM; Spatial allocation optimization (SAO).

MeSH terms

Hydrology
Models, Theoretical
Picea*
Rain
Water Movements*
Water Quality