Bayesian Optimization Framework for Cost-Effective Control and Research of Non-Point-Source Sediment
Publication: Journal of Water Resources Planning and Management
Volume 139, Issue 5
Abstract
Rural nonpoint sources of water pollution are particularly difficult to control, with relatively little progress having been made compared to point sources. Management choices are difficult because of large uncertainties in both the monitoring of nonpoint pollution and the effectiveness of various actions to reduce that pollution. This study includes a proposed framework for selecting the optimal combination of research, monitoring, and management actions. The approach combines Bayesian inference and multiobjective linear programming to explicitly represent uncertainty in the effectiveness and cost of controls and to quantify the value of reducing uncertainty through research and monitoring. The authors illustrate the framework using the problem of reducing turbidity from rural sediment sources in the Minnesota River basin. The results show that a combination of research methods in different subbasins usually yields the most valuable information and is predicted to result in benefits via reduced cost and increased effectiveness of sediment reduction.
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Acknowledgments
This work was supported by the Science and Technology Centers Program of the U.S. National Science Foundation via the National Center for Earth-Surface Dynamics under agreement EAR-0120914 and the David H. Smith Conservation Research Fellowship Program. P. Zheng, J. Bassman-Ruch, and C. Zuerndorfer collected and analyzed data, and S. Becker and J. Brach provided helpful insights into management practices in Minnesota. K. Gran, the stream restoration team at NCED, S. J. Cho, and M. Kenney gave useful suggestions. P. Belmont and R. Moore provided essential expert opinions and data. Publication no. DHS2012-01 of the David H. Smith Conservation Research Fellowship Program.
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Published In
Journal of Water Resources Planning and Management
Volume 139 • Issue 5 • September 2013
Pages: 534 - 543
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Aug 30, 2011
Accepted: May 16, 2012
Published online: Aug 15, 2013
Published in print: Sep 1, 2013
Discussion open until: Jan 15, 2014
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