A numerical tool to predict ice growth in lakes

Oil and gas exploration activities on the North of Slope of Alaska rely on ice roads to provide access to the exploration sites, with negligible effects on the tundra. The construction of ice roads requires a large volume of water which, in turn, poses challenges to water resource managers. A tool capable of predicting ice thickness in a given lake could certainly benefit the oil industry. This study focuses on the development and use of such a predictive tool. Using a simplified Stefan equation, the tool is based on a combination of three weather scenarios (warm, average and cold winters), current winter condition and ice thickness measurements. It was applied to four lakes located on the Arctic Coastal Plain and one lake in the foothill area. The study results indicate the model predictions are relatively accurate (7% average percentage error) for monthly time spans. The study results also reveal a temporal variation in a coefficient used in the calculations, although previous literature utilized a constant coefficient to estimate the ice thickness.