A Bayesian Decision Network Engine for Internet-Based Stakeholder Decision-Making

In this paper, we present an Internet-based, Bayesian Decision Network engine to aid watershed stakeholders in collaborative decision-making. Recent years have seen an increased emphasis on including all affected parties in the process of making water resources and water quality management decisions (as in the TMDL program). Given the complexity of the models and data analysis tools that are typically employed by engineers and scientists in watershed studies, meaningful communication with stakeholders can be a daunting task. In our experience, stakeholders are often skeptical of model and data analysis results because of the inherent uncertainty associated with these methods. Because of this, a stakeholder may be more likely to accept results presented in the form of a probability distribution of potential outcomes, than a single predicted result. Additionally, if model predictions are mapped into the likelihood of realizing tangible and intangible benefits, stakeholders have a means whereby to evaluate the anticipated results. Bayesian Decision Network (BDNs) are presented here as a useful tool for diagramming the decision process; for holding relationships between variables; and for analyzing the anticipated effects of management decisions while explicitly accounting for the associated uncertainties. An Internet-based application for employing BDNs in watershed decision-making is described with a demonstration application from the East Canyon watershed in Utah.