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

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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 98 months 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.

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Availability of data and materials

All data used in the study are available from the sources identified in the paper: https://www.sfwmd.gov/science-data/dbhydro; https://waterdata.usgs.gov/nwis; http://leegis.leegov.com/surfwater/

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Acknowledgements

The author would like to acknowledge all the hard work of the field and laboratory staff of SFWMD, Lee County Environmental Lab and USGS for the collection and analysis of water samples and flow measurements over the years; their efforts in generating and maintaining long-term data sets that are crucial for decision making are often underappreciated. I would also like to thank Dhruvkumar Bhatt for his assistance in making the map and especially the Honors Students in my Fall 2021 Oceanography class who assisted in reviewing data downloads and double-checking data processing necessary for this study.

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  1. Department of Marine and Earth Sciences, The Water School, Florida Gulf Coast University, Fort Myers, FL, USA

    Darren G. Rumbold

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The author downloaded the data from the sources identified in the paper, carried out all data processing and authored the manuscript.

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Correspondence to Darren G. Rumbold.

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Rumbold, D.G. Use of a Bayesian network as a decision support tool for watershed management: a case study in a highly managed river-dominated estuary. Environ Monit Assess 195, 741 (2023). https://doi.org/10.1007/s10661-023-11273-y

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