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Knowledge,transparency, and refutability in groundwater models,an example from the Death Valley regional groundwater flow system
Institution:1. UNSW Water Research Centre, School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, Australia;2. Department of Environmental Sciences, University of California Riverside, Riverside, CA 92521, USA;1. Institute of Applied Physics, University of Hamburg, 20355 Hamburg, Germany;2. National Center for Materials Study and Testing, Technical University of Moldova, 2004 Chisinau, Republic of Moldova;3. Institute of Solid State Physics, University of Bremen, 28334 Bremen, Germany
Abstract:This work demonstrates how available knowledge can be used to build more transparent and refutable computer models of groundwater systems. The Death Valley regional groundwater flow system, which surrounds a proposed site for a high level nuclear waste repository of the United States of America, and the Nevada National Security Site (NNSS), where nuclear weapons were tested, is used to explore model adequacy, identify parameters important to (and informed by) observations, and identify existing old and potential new observations important to predictions. Model development is pursued using a set of fundamental questions addressed with carefully designed metrics. Critical methods include using a hydrogeologic model, managing model nonlinearity by designing models that are robust while maintaining realism, using error-based weighting to combine disparate types of data, and identifying important and unimportant parameters and observations and optimizing parameter values with computationally frugal schemes. The frugal schemes employed in this study require relatively few (10–1000 s), parallelizable model runs. This is beneficial because models able to approximate the complex site geology defensibly tend to have high computational cost. The issue of model defensibility is particularly important given the contentious political issues involved.
Keywords:Sensitivity analysis  Uncertainty  Worth of data  Value of information  Hydrogeology  Groundwater
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