Persistent Link:
http://hdl.handle.net/10150/617654
Title:
Decision Making Under Uncertainty in Systems Hydrology
Author:
Davis, Donald Ross
Affiliation:
Department of Hydrology & Water Resources, The University of Arizona
Publisher:
Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ)
Issue Date:
1971-05
Rights:
Copyright © Arizona Board of Regents
Collection Information:
This title from the Hydrology & Water Resources Technical Reports collection is made available by the Department of Hydrology & Atmospheric Sciences and the University Libraries, University of Arizona. If you have questions about titles in this collection, please contact repository@u.library.arizona.edu.
Abstract:
Design of engineering projects involve a certain amount of uncertainty. How should design decisions be taken in face of the uncertainty? What is the most efficient way of handling the data? Decision theory can provide useful answers to these questions. The literature review shows that decision theory is a fairly well developed decision method, with almost no application in hydrology. The steps of decision theoretic analysis are given. They are augmented by the concept of expected expected opportunity loss, which is developed as a means of measuring the expected value of additional data before they are received. The method is applied to the design of bridge piers and flood levees for Rillito Creek, Pima County, Arizona. Uncertainty in both the mean and the variance of the logarithms of the peak flows of Rillito Creek is taken into account. Also shown are decision theoretic methods for: 1) handling secondary data, such as obtained from a regression relation, 2) evaluating the effect of the use of non - sufficient statistics, 3) considering alternate models and 4) regionalizing data.It is concluded that decision theory provides a rational structure for making design decisions and for the associated data collection and handling problems.
Keywords:
Hydrology -- Mathematical models.; Hydrological forecasting.; decision making; Systems Engineering; Bridges -- Design and construction.; Levees; Rillito River (Ariz.)
Series/Report no.:
Technical Reports on Hydrology and Water Resources, No. 2
Sponsors:
This research was supported in part by research grant B- 007 -ARIZONA on the "Efficiency of Data Collection Systems in Hydrology and Water Resources for Prediction and Control" from the office of Water Resources Research, United States Department of the Interior.

Full metadata record

DC FieldValue Language
dc.contributor.authorDavis, Donald Rossen
dc.date.accessioned2016-07-27T23:59:20Z-
dc.date.available2016-07-27T23:59:20Z-
dc.date.issued1971-05-
dc.identifier.urihttp://hdl.handle.net/10150/617654-
dc.description.abstractDesign of engineering projects involve a certain amount of uncertainty. How should design decisions be taken in face of the uncertainty? What is the most efficient way of handling the data? Decision theory can provide useful answers to these questions. The literature review shows that decision theory is a fairly well developed decision method, with almost no application in hydrology. The steps of decision theoretic analysis are given. They are augmented by the concept of expected expected opportunity loss, which is developed as a means of measuring the expected value of additional data before they are received. The method is applied to the design of bridge piers and flood levees for Rillito Creek, Pima County, Arizona. Uncertainty in both the mean and the variance of the logarithms of the peak flows of Rillito Creek is taken into account. Also shown are decision theoretic methods for: 1) handling secondary data, such as obtained from a regression relation, 2) evaluating the effect of the use of non - sufficient statistics, 3) considering alternate models and 4) regionalizing data.It is concluded that decision theory provides a rational structure for making design decisions and for the associated data collection and handling problems.en
dc.description.sponsorshipThis research was supported in part by research grant B- 007 -ARIZONA on the "Efficiency of Data Collection Systems in Hydrology and Water Resources for Prediction and Control" from the office of Water Resources Research, United States Department of the Interior.en
dc.language.isoen_USen
dc.publisherDepartment of Hydrology and Water Resources, University of Arizona (Tucson, AZ)en
dc.relation.ispartofseriesTechnical Reports on Hydrology and Water Resources, No. 2en
dc.rightsCopyright © Arizona Board of Regentsen
dc.sourceProvided by the Department of Hydrology and Water Resources.en
dc.subjectHydrology -- Mathematical models.en
dc.subjectHydrological forecasting.en
dc.subjectdecision makingen
dc.subjectSystems Engineeringen
dc.subjectBridges -- Design and construction.en
dc.subjectLeveesen
dc.subjectRillito River (Ariz.)en
dc.titleDecision Making Under Uncertainty in Systems Hydrologyen_US
dc.typetexten
dc.typeTechnical Reporten
dc.contributor.departmentDepartment of Hydrology & Water Resources, The University of Arizonaen
dc.description.collectioninformationThis title from the Hydrology & Water Resources Technical Reports collection is made available by the Department of Hydrology & Atmospheric Sciences and the University Libraries, University of Arizona. If you have questions about titles in this collection, please contact repository@u.library.arizona.edu.en
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