Department

Department of Ecosystem Sciences

First Advisor

Scott Miller

Description

Previous work at the University of Wyoming has identified landscapes in Wyoming that do not follow traditional observations and contradict principal scientific understanding of watershed behavior. High resolution data was collected in oil and gas development areas in the Pinedale region to map channel dimensions. Predictable relationships of watershed and terrain characteristics could not be found during hydrologic analysis (Vithanage and Miller, 2014). The Moneta Divide, another active oil and gas development field in the central Wyoming area, bears similar characteristics in terms of climate and soils to the Pinedale region. It is of scientific interest to compare the findings of data analysis in the Moneta Divide to previously determined patterns of channel behavior in the state or region. In this research we have processed high resolution Light Detection and Ranging (LiDAR) data of stream channels in the Moneta Divide, to determine whether these morphological characteristics can be described by statistical relationships from other watershed data. This information will likely be useful to support future hydrologic modeling and field-based monitoring efforts in areas affected by oil and gas development.

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NASA Space Grant Consortium

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Analysis of Stream Bed Morphology in Oil and Gas Development Areas Using LIDar Data

Previous work at the University of Wyoming has identified landscapes in Wyoming that do not follow traditional observations and contradict principal scientific understanding of watershed behavior. High resolution data was collected in oil and gas development areas in the Pinedale region to map channel dimensions. Predictable relationships of watershed and terrain characteristics could not be found during hydrologic analysis (Vithanage and Miller, 2014). The Moneta Divide, another active oil and gas development field in the central Wyoming area, bears similar characteristics in terms of climate and soils to the Pinedale region. It is of scientific interest to compare the findings of data analysis in the Moneta Divide to previously determined patterns of channel behavior in the state or region. In this research we have processed high resolution Light Detection and Ranging (LiDAR) data of stream channels in the Moneta Divide, to determine whether these morphological characteristics can be described by statistical relationships from other watershed data. This information will likely be useful to support future hydrologic modeling and field-based monitoring efforts in areas affected by oil and gas development.