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Application of Bayesian Decision Networks To Total Maximum Daily Load Analysis

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Pp. 221-231 in Total Maximum Daily Load (TMDL) Environmental Regulations: Proceedings of the March 11-13, 2002 Conference, (Fort Worth, Texas, USA)  701P0102.(doi:10.13031/2013.7562)
Authors:   Bethany T. Neilson, Daniel P. Ames, and David K. Stevens
Keywords:   Total Maximum Daily Load, Bayesian Decision Network, Water Quality, Water Quality Modeling

In this paper, we present a Bayesian Decision Network (BDN) as a framework to support decision-making in the Environmental Protection Agencys (EPA) Total Maximum Daily Load (TMDL) program. Regulatory requirements of the TMDL program include the use of all available sources of water quality data; the inclusion of stakeholders in the decision process; assessment of uncertainty associated with stream characterization; and assessment of economic impacts of TMDL decisions. We present an example BDN for the East Canyon watershed that supports all of these requirements and can serve as a vehicle for helping stakeholders and decision-makers arrive at consensus. This BDN is populated using anecdotal information from experts and stakeholders; water quality, streamflow and socio-economic data; and results of Monte Carlo simulations from a water quality model (QUAL2E-UNCAS). Using this BDN, we were able to determine the probability of meeting water quality standards in East Canyon Creek under different management scenarios. The BDN was also expanded to include information more applicable to stakeholders within the watershed.

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