EARTH SCIENCE INNOVATIONS SPAWNED BY THE YUCCA MOUNTAIN PROJECT

Beginning in 1955 (and many times thereafter) expert panels have been convened to provide recommendations on the disposition of high-level radioactive waste. Nationally and internationally these panels have recommended geologic disposal. In 1980, a large group of scientists and engineers from 15 different government and industry organizations concluded that a site could be found and licensed within 10 years using available technology. However, when regulations were promulgated, predicted performance had to show safety for 10,000 years, about double the time span of recorded history (later extended to approximately a million yrs). In large part, the long-term predictions required data with greater detail and accuracy than was needed for reactor-siting studies and some new approaches were needed as well.

Results of scientific investigations had to be able to stand legal scrutiny without needing the testimony of the scientists who originally did the work; thus a quality-assurance program was born. Lessons learned from this effort should benefit others who anticipate that their work may end up in court. The Project had to learn how and when water moved through the unsaturated zone and how fast. How much of the infiltrating water continues down to the saturated zone? How have these variables changed in the past in response to changes in past climates? These questions required new micro-dating techniques and new numeric models for flow and transport.

The size of the data base needed can be appreciated from the facts that data were gathered from more than 100 boreholes, 91 faults were identified and assessed, over 60 fault-trenches were dug and mapped in detail, and underground mapping recorded all fractures longer than 1 m. One natural exposure of a fault provided a nearly continuous record of movement for the last 750,000 yrs. The physical scale and time-spans considered for features and processes required in predicted performance led to the generation of a large data base of natural analogues, which could be used to test predictions qualitatively and to communicate complex science to non-scientists. This approach may prove useful in other areas of complex science that also are of great interest to the general public.