Multiobjective Optimization of Sensor Placement for Precipitation Station Monitoring Network Design
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Volume 25, Issue 9
Abstract
An optimal sensor placement of a precipitation station network should fulfill different regulations and requirements, such as coverage maximization, easy access, and uniform distribution. However, few studies have focused on an integrated way to optimize the precipitation network design from the perspective of monitoring efficiency in space. In this paper, given the complex requirements and diversified goals for precipitation monitoring, a new multiobjective location model is established for optimizing the network’s monitoring efficiency with a comprehensive weighting scheme. Based on the precipitation station siting regulations, the spatial coverage, accessibility, and dispersion of stations are considered in the model. The Elitist Nondominated Sorting Genetic Algorithm (NSGA-II) is used to obtain a set of Pareto-efficient solutions. The Jinsha River Basin is selected as the study region to test the proposed method. The results show that the proposed method satisfies the complex precipitation monitoring requirements and achieves higher coverage than the real-world deployment. The decision making for siting schemes, comparison of other dispersion models, and the extensibility of the proposed method are also discussed.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by grants from the National Nature Science Foundation of China (NSFC) Program (No. 41701453), the Open Research Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (Wuhan University) (No. 17I02), the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (No. CUG190616), the Science and Technology Research Project of Hubei Provincial Department of Education (No. B2018053), the Social Science Foundation of Wuhan Institute of Technology (No. R201805), the Science Research Project of Wuhan Institute of Technology (No. K201730), and the Application Fundamental and the Special Fund for Foundation and Frontier of Applications of Wuhan (No. 2018010401011293).
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Journal of Hydrologic Engineering
Volume 25 • Issue 9 • September 2020
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©2020 American Society of Civil Engineers.
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Received: Nov 6, 2019
Accepted: Feb 19, 2020
Published online: Jun 19, 2020
Published in print: Sep 1, 2020
Discussion open until: Nov 19, 2020
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