2022 Early Hearing Detection & Intervention Virtual Conference

March 13 - 15, 2022

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6/06/2017 | 9:30 AM - 9:45 AM | THE LAKE-CATCHMENT (LAKECAT) DATASET FOR CHARACTERIZING HYDROLOGICALLY-RELEVANT LANDSCAPE FEATURES FOR LAKES ACROSS THE CONTERMINOUS US | 302B

THE LAKE-CATCHMENT (LAKECAT) DATASET FOR CHARACTERIZING HYDROLOGICALLY-RELEVANT LANDSCAPE FEATURES FOR LAKES ACROSS THE CONTERMINOUS US

Lake conditions, including their biota, respond to both natural and human-related landscape features. Characterizing these features within the contributing areas (i.e., delineated watersheds) of lakes could improve the analysis and the sustainable use and management of these important aquatic resources. However, the specialized geospatial techniques required to define and characterize lake watersheds has limited their widespread use in both scientific and management efforts. We developed the LakeCat Dataset to improve the accessibility of such information for lakes within the conterminous US (CONUS). LakeCat parallels another recent USEPA dataset developed for streams (i.e., StreamCat). LakeCat contains watershed-level characterizations of several hundred natural (e.g., soils, geology, climate, and land cover) and anthropogenic (e.g., urbanization, agriculture, mining, and forest management) landscape features for ca. 376,000 lakes across the CONUS. LakeCat can be quickly paired with lake samples to provide independent variables for modeling and other analyses. We will present the LakeCat framework, main features of the dataset, and examples of linking field data to LakeCat to model and predict the condition of all lakes nationally rather than only those that have been sampled.

C07 Lentic Ecology
C28 Land-Water Interfaces
S29 Macrosystem Ecology of Aquatic Systems

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Presenters/Authors

Ryan Hill (), US EPA, Pacific Ecological Systems Division, Corvallis, OR, hill.ryan@epa.gov;