Decision Making Under Uncertainty in Systems Hydrology
| dc.contributor.author | Davis, Donald Ross | |
| dc.date.accessioned | 2016-07-27T23:59:20Z | |
| dc.date.available | 2016-07-27T23:59:20Z | |
| dc.date.issued | 1971-05 | |
| dc.identifier.uri | http://hdl.handle.net/10150/617654 | |
| dc.description.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. | |
| dc.description.sponsorship | 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. | en |
| dc.language.iso | en_US | en |
| dc.publisher | Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ) | en |
| dc.relation.ispartofseries | Technical Reports on Hydrology and Water Resources, No. 2 | en |
| dc.rights | Copyright © Arizona Board of Regents | en |
| dc.source | Provided by the Department of Hydrology and Water Resources. | en |
| dc.subject | Hydrology -- Mathematical models. | en |
| dc.subject | Hydrological forecasting. | en |
| dc.subject | decision making | en |
| dc.subject | Systems Engineering | en |
| dc.subject | Bridges -- Design and construction. | en |
| dc.subject | Levees | en |
| dc.subject | Rillito River (Ariz.) | en |
| dc.title | Decision Making Under Uncertainty in Systems Hydrology | en_US |
| dc.type | text | en |
| dc.type | Technical Report | en |
| dc.contributor.department | Department of Hydrology & Water Resources, The University of Arizona | en |
| dc.description.collectioninformation | 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. | en |
| refterms.dateFOA | 2018-06-29T01:39:15Z | |
| html.description.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. |
