Simulating 10,000 Years of Erosion to Assess Nuclear Waste Repository Performance

Long-term environmental performance assessments of natural processes, including erosion, are critically important for waste repository site evaluation. However, assessing a site’s ability to continuously function is challenging due to parameter uncertainty and compounding nonlinear processes. In lie...

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Veröffentlicht in:Geosciences (Basel) 2019-03, Vol.9 (3), p.120
Hauptverfasser: Atchley, Adam L., Birdsell, Kay H., Crowell, Kelly, Middleton, Richard S., Stauffer, Philip H.
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Sprache:eng
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Zusammenfassung:Long-term environmental performance assessments of natural processes, including erosion, are critically important for waste repository site evaluation. However, assessing a site’s ability to continuously function is challenging due to parameter uncertainty and compounding nonlinear processes. In lieu of unavailable site data for model calibration, we present a workflow to include multiple sources of surrogate data and reduced-order models to validate parameters for a long-term erosion assessment of a low-level radioactive nuclear waste repository. We apply this new workflow to a low-level waste repository on mesas in Los Alamos National Laboratory in New Mexico. To account for parameter uncertainty, we simulate high-, moderate-, and low-erosion cases. The assessment extends to 10,000 years, which results in large erosion uncertainties, but is necessary given the nature of the interred waste. Our long-term erosion analysis shows that high-erosion scenarios produce rounded mesa tops and partially filled canyons, diverging from the moderate-erosion case that results in gullies and sharp mesa rims. Our novel model parameterization workflow and modeling exercise demonstrates the utility of long-term assessments, identifies sources of erosion forecast uncertainty, and demonstrates the utility of landscape evolution model development. We conclude with a discussion on methods to reduce assessment uncertainty and increase model confidence.
ISSN:2076-3263
2076-3263
DOI:10.3390/geosciences9030120