• A new LID spatial allocation o...

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

Title:
A new LID spatial allocation optimization system at neighborhood scale: Integrated SWMM with PICEA-g using MATLAB as the platform.
Authors:
Yu Y; Dept of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada., Zhou Y; The Institute of Municipal Engineering, Zhejiang University, Hangzhou 310058, China., Guo Z; College of New Energy and Environment, Jilin University, Changchun, 130012, China., van Duin B; Dept of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada; Water Resources, City of Calgary, Calgary, AB T2G 4K8, Canada., Zhang W; Dept of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada. Electronic address: wenming@ualberta.ca.
Source:
The Science of the total environment [Sci Total Environ] 2022 Jul 20; Vol. 831, pp. 154843. Date of Electronic Publication: 2022 Mar 26.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0330500 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1026 (Electronic) Linking ISSN: 00489697 NLM ISO Abbreviation: Sci Total Environ Subsets: MEDLINE
Imprint Name(s):
Original Publication: Amsterdam, Elsevier.
MeSH Terms:
Picea* , Water Movements*, Hydrology ; Models, Theoretical ; Rain ; Water Quality
Contributed Indexing:
Keywords: Cost-benefit; LID; MATLAB; PICEA-g; SWMM; Spatial allocation optimization (SAO)
Entry Date(s):
Date Created: 20220330 Date Completed: 20220603 Latest Revision: 20220603
Update Code:
20250114
DOI:
10.1016/j.scitotenv.2022.154843
PMID:
35351503
Database:
MEDLINE

Weitere Informationen

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).
(Copyright © 2022 Elsevier B.V. All rights reserved.)

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.