Spatial Optimization of Low-Impact Development Facilities Based on a -Median Model and an Ant Colony Optimization
Publication: Journal of Hydrologic Engineering
Volume 24, Issue 12
Abstract
Determining the scales, types, and locations of low-impact development (LID) facilities is the basis for LID practice. Spatially available rainwater on site is first calculated in this study to obtain the scales of LID facilities using the geographic information system technique. Spatially available harvested rainwater in different land-use types is then calculated to determine types of LID facilities according to potential facilities’ performance. Next, a -median model and an ant colony optimization (ACO) algorithm are used to obtain spatially optimal locations for LID facilities. Main runoff pollutants [e.g., suspended solids (SS), total phosphorus (TP), dichromate oxidizability (), and ammonia nitrogen ()] are sampled, interpolated, normalized, and spatially overlaid to identify heavily polluted areas and adjust LID facilities for decontamination. Finally, the performance of the ACO for the -median model is compared with that from the genetic algorithm. Determining the scales, types, and locations of LID practices can effectively guide construction of LID for practitioners and stakeholders.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request (DEM and land use in Yinchuan City, data of potential rainwater availability, -median model, and ACO algorithm).
Acknowledgments
This project (41661026) was supported by the National Natural Science Foundation of China and by the Scientific Research Project of Higher School in Ningxia (Project NGY2017057).
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Published In
Journal of Hydrologic Engineering
Volume 24 • Issue 12 • December 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Feb 13, 2019
Accepted: Jul 10, 2019
Published online: Sep 30, 2019
Published in print: Dec 1, 2019
Discussion open until: Feb 29, 2020
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