Use of a Bayesian network as a decision support tool for watershed management: a case study in a highly managed river-dominated estuary

Abstract

Decision making in water resource management has many dimensions including water supply, flood protection, and meeting ecological needs, therefore, is complex, full of uncertainties, and often contentious due to competing needs and distrust among stakeholders. It benefits from robust tools for supporting the decision-making process and for communicating with stakeholders. This paper presents a Bayesian network (BN) modeling framework for analyzing various management interventions regulating freshwater discharges to an estuary. This BN was constructed using empirical data from 98months of monitoring the Caloosahatchee River Estuary in south Florida during the period 2008-2021 as a case study to illustrate the potential advantages of the BN approach. Results from three different management scenarios and their implications on down-estuary conditions as they affected eastern oysters (Crassostrea virginica) and seagrass (Halodule wrightii) are presented and discussed. Finally, the directions for future applications of the BN modeling framework to support management in similar systems are offered.