Using Bayesian networks to model watershed management decisions: an East Canyon Creek case study | Zendy

Daniel P. Ames | Zendy; Bethany T. Neilson | Zendy; David K. Stevens | Zendy; Upmanu Lall | Zendy

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Using Bayesian networks to model watershed management decisions: an East Canyon Creek case study

Author(s) -

Daniel P. Ames,

Bethany T. Neilson,

David K. Stevens,

Upmanu Lall

Publication year - 2005

Publication title -

journal of hydroinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.654

H-Index - 50

eISSN - 1465-1734

pISSN - 1464-7141

DOI - 10.2166/hydro.2005.0023

Subject(s) - canyon , watershed , bayesian network , hydrology (agriculture) , recreation , environmental science , bayesian probability , watershed management , bayesian inference , computer science , water resource management , environmental resource management , geography , engineering , cartography , artificial intelligence , ecology , geotechnical engineering , machine learning , biology

An approach to developing and using Bayesian networks to model watershed management decisions is presented with a case study application to phosphorus management in the East Canyon watershed in Northern Utah, USA. The Bayesian network analysis includes a graphical model of the key variables in the system and conditional and marginal probability distributions derived from a variety of data and information sources. The resulting model is used to 1) estimate the probability of meeting legal water quality requirements for phosphorus in East Canyon Creek under several management scenarios and 2) estimate the probability of increased recreational use of East Canyon Reservoir and subsequent revenue under these scenarios.

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