LAKECAT – DATASET OF LAKE BASIN CHARACTERISTICS
FACTSHEET FOR LAKECAT. ABSTRACT OF ORIGINAL ARTICLE: Natural and human-related landscape features influence the ecology and water quality within lakes. It is critical to summarize these features in a hydrologically-meaningful way to understand and manage lake ecosystems. Such summaries are often done through the delineation of watershed boundaries of individual lakes. However, there are many technical challenges associated with delineating hundreds or thousands of lake watersheds at broad spatial extents that can limit the application of analyses to new, unsampled locations. We present the development of the Lake-Catchment (LakeCat) Dataset (https://www.epa.gov/national-aquatic-resource-surveys/lakecat); a dataset of watershed features for 378,088 lakes within the conterminous US. We describe the methods we used to (1) delineate lake catchments, (2) hydrologically connect nested lake catchments, and (3) generate several hundred watershed-level metrics that summarize both natural (e.g., soils, geology, climate, and land cover) and anthropogenic (e.g., urbanization, agriculture, and mines) features. To illustrate how this dataset can be used, we developed a random forest model to predict the probability of lake eutrophication by combining LakeCat with data from US EPA’s National Lakes Assessment (NLA). This model correctly predicted the trophic state of 72% of NLA lakes and we applied the model to predict the probability of eutrophication at 297,071 unsampled lakes across the conterminous US. The large suite of LakeCat metrics could be used to improve analyses of lakes at broad spatial extents, improve the applicability of analyses to new, unsampled lakes, and ultimately improve the management of these important ecosystems.