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Hydrogeological Decision Analysis: 4. The Concept of Data Worth and Its Use in the Development of Site Investigation Strategies
Author(s) -
Freeze R. Allan,
James Bruce,
Massmann Joel,
Sperling Tony,
Smith Leslie
Publication year - 1992
Publication title -
groundwater
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 94
eISSN - 1745-6584
pISSN - 0017-467X
DOI - 10.1111/j.1745-6584.1992.tb01534.x
Subject(s) - hydrogeology , computer science , regret , site selection , risk analysis (engineering) , uncertainty reduction theory , reduction (mathematics) , operations research , data collection , decision analysis , data mining , engineering , mathematics , business , statistics , machine learning , geometry , geotechnical engineering , communication , sociology , political science , law
In the design of new waste‐management facilities, or in the remedial design for contaminated facilities, there are economic tradeoffs possible between the resources assigned to site investigation, facility design, and site monitoring. Hydrogeological decision analysis provides a framework that allows a sequential, iterative approach to design, in which data acquisition through site investigation alternates with economic analysis of alternative design options. In this framework, the purpose of collecting hydrogeological data is to aid in the making of decisions between the alternative design options. Such decisions are made on the basis of a risk‐cost‐benefit objective function. Additional measurements have worth only if the risk reduction they provide exceeds the cost of obtaining them. The location of measurement points in a site‐investigation network should minimize economic regret with respect to design decisions. This paper provides an introduction to the concepts of data‐worth analysis for two cases: (1) the reduction of uncertainty in aquitard continuity, and (2) the reduction of uncertainty in hydraulic‐conductivity distribution in an aquifer. It is shown how the use of search theory and Bayesian updating can be applied in comparing prior and preposterior analyses to provide a stopping rule for the collection of additional data in site investigation programs at a hypothetical landfill site.