RESUMEN
Aerial gamma ray surveys are an important tool for national security, scientific, and industrial interests in determining locations of both anthropogenic and natural sources of radioactivity. There is a relationship between radioactivity and geology and in the past this relationship has been used to predict geology from an aerial survey. The purpose of this project is to develop a method to predict the radiologic exposure rate of the geologic materials by creating a high resolution background model. The intention is for this method to be used in an emergency response scenario where the background radiation environment is unknown. Two study areas in Southern Nevada have been modeled using geologic data, images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), geochemical data, and pre-existing low resolution aerial surveys from the National Uranium Resource Evaluation (NURE) Survey. Using these data, geospatial areas that are homogenous in terms of K, U, and Th, referred to as background radiation units, are defined and the gamma ray exposure rate is predicted. The prediction is compared to data collected via detailed aerial survey by the Department of Energy's Remote Sensing Lab - Nellis, allowing for the refinement of the technique. By using geologic units to define radiation background units of exposed bedrock and ASTER visualizations to subdivide and define radiation background units within alluvium, successful models have been produced for Government Wash, north of Lake Mead, and for the western shore of Lake Mohave, east of Searchlight, NV.
Asunto(s)
Radiación de Fondo , Modelos Químicos , Monitoreo de Radiación , NevadaRESUMEN
This study compares high resolution forward models of natural gamma-ray background with that measured by high resolution aerial gamma-ray surveys. The ability to predict variations in natural background radiation levels should prove useful for those engaged in measuring anthropogenic contributions to background radiation for the purpose of emergency response and homeland security operations. The forward models are based on geologic maps and remote sensing multi-spectral imagery combined with two different sources of data: 1) bedrock geochemical data (uranium, potassium and thorium concentrations) collected from national databases, the scientific literature and private companies, and 2) the low spatial resolution NURE (National Uranium Resource Evaluation) aerial gamma-ray survey. The study area near Cameron, Arizona, is located in an arid region with minimal vegetation and, due to the presence of abandoned uranium mines, was the subject of a previous high resolution gamma-ray survey. We found that, in general, geologic map units form a good basis for predicting the geographic distribution of the gamma-ray background. Predictions of background gamma-radiation levels based on bedrock geochemical analyses were not as successful as those based on the NURE aerial survey data sorted by geologic unit. The less successful result of the bedrock geochemical model is most likely due to a number of factors including the need to take into account the evolution of soil geochemistry during chemical weathering and the influence of aeolian addition. Refinements to the forward models were made using ASTER visualizations to create subunits of similar exposure rate within the Chinle Formation, which contains multiple lithologies and by grouping alluvial units by drainage basin rather than age.