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From an evolutionary perspective, glacial lakes at the Bering Glacier System are highly immature and are classified as extremely oligotrophic, resulting from their relatively recent formation and the surrounding harsh, northern climate. Unlike temperate or tropical lakes, northern glacial lakes do not contain significant amounts of biological material. Instead, these lakes are dominated by rock flour, suspended sediment originating from glacial rock weathering. This lack of biological influence makes satellite turbidity mapping and prediction more straightforward and potentially more accurate than similar efforts in temperate or tropical environments, where biology typically drives these systems and strongly affects the remotely sensed, electro-optical signal.

In-situ turbidity data, collected using an autonomous robot buoy, were used to develop a model-based turbidity algorithm. Multiple linear regression analyses were conducted using different Landsat 7 ETM+ bands to determine the best predictor(s) of turbidity in glacial lakes. The final algorithm utilized Landsat 7 ETM+ band 3 (red portion of the electromagnetic spectrum) and band 4 (near-infrared portion of the electromagnetic spectrum) data to predict turbidity concentrations.

Turbidity maps created using the algorithm can be used to help determine inter- and intra-annual sediment dynamics of Vitus Lake. This information could be used to help researchers predict significant glacial events such as outburst floods or surge events. The turbidity maps could also provide insight into the hydrologic routing of the Bering Glacier System by showing where the Glacier is discharging sediment-laden fresh water into Vitus Lake through subsurface conduits. The turbidity algorithm also has broader applicability to other glacial lakes in south-central Alaska and potentially to glacial lakes worldwide.

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