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Application of Statistical Decision Theory to Water Use Analysis in Sevier County, Utah
Author(s) -
Andersen Jay C.,
Hiskey Harold H.,
Lackawathana Suwaphot
Publication year - 1971
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr007i003p00443
Subject(s) - flexibility (engineering) , variety (cybernetics) , profitability index , bayesian probability , computer science , water resource management , environmental resource management , operations research , environmental science , business , engineering , statistics , mathematics , finance , artificial intelligence
Statistical or Bayesian decision theory was applied to a farm management situation in Sevier County, Utah, which is characterized by risk and uncertainty with respect to the supply of late season water. Information on reservoir carry‐over and mountain snowpack becomes available just before resources must be committed. These data are incorporated into the model as predictors of the late season water supply. Use of this predictive information is compared to the ‘no data’ situation, in which the predictive information is not used, and also to the ‘perfect knowledge’ situation, in which the availability of full information at the time of resource commitment is assumed. A limited growing season and other physical constraints along with lack of markets restrict the flexibility of the management decisions so that the profitability of adapting the technique is not great in the present application. However, the technique is shown to be usable and potentially profitable in a variety of management situations.