Journal
WATER RESOURCES RESEARCH
Volume 48, Issue -, Pages -Publisher
AMER GEOPHYSICAL UNION
DOI: 10.1029/2011WR011016
Keywords
-
Categories
Funding
- German Research Foundation (DFG) within the Cluster of Excellence in Simulation Technology at the University of Stuttgart [EXC 310/1]
- Spanish Ministry of Science
- U.S. Department of Energy (DOE) Office of Biological and Environmental Research through DOE-ERSP [DE-FG02-06ER06-16]
Ask authors/readers for more resources
Most field campaigns aim at helping in specified scientific or practical tasks, such as modeling, prediction, optimization, or management. Often these tasks involve binary decisions or seek answers to yes/no questions under uncertainty, e. g., Is a model adequate? Will contamination exceed a critical level? In this context, the information needs of hydro(geo) logical modeling should be satisfied with efficient and rational field campaigns, e. g., because budgets are limited. We propose a new framework to optimize field campaigns that defines the quest for defensible decisions as the ultimate goal. The key steps are to formulate yes/no questions under uncertainty as Bayesian hypothesis tests, and then use the expected failure probability of hypothesis testing as objective function. Our formalism is unique in that it optimizes field campaigns for maximum confidence in decisions on model choice, binary engineering or management decisions, or questions concerning compliance with environmental performance metrics. It is goal oriented, recognizing that different models, questions, or metrics deserve different treatment. We use a formal Bayesian scheme called PreDIA, which is free of linearization, and can handle arbitrary data types, scientific tasks, and sources of uncertainty (e. g., conceptual, physical, (geo) statistical, measurement errors). This reduces the bias due to possibly subjective assumptions prior to data collection and improves the chances of successful field campaigns even under conditions of model uncertainty. We illustrate our approach on two instructive examples from stochastic hydrogeology with increasing complexity.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available