You are here:
Towards national mapping of aquatic condition (I): The Stream-Catchment (StreamCat) Dataset
Citation:
Weber, M., R. Hill, S. Leibowitz, AND Tony Olsen. Towards national mapping of aquatic condition (I): The Stream-Catchment (StreamCat) Dataset. 9th International Association of Landscape Ecology World Congress, Portland, OR, July 05 - 10, 2015.
Impact/Purpose:
Stream environments reflect, in part, the hydrologic integration of upstream landscapes. Characterizing upstream features is critical for effectively understanding, managing, and conserving riverine ecosystems but represents a major challenge. We developed and will present a database of >100 landscape metrics for ~2.7 million watersheds within the conterminous USA: The Stream-Catchment (StreamCat) Dataset. This dataset can be linked to an existing geospatial framework to provide rapid extraction of upstream characteristics for stream-based studies. This presentation will be paired with an example application of the StreamCat Dataset to predict the probable biological condition of streams across the conterminous USA. These paired presentations will introduce the StreamCat Dataset and our model of USA-wide biological condition to a wide range of scientists and practitioners.
Description:
Stream environments reflect, in part, the hydrologic integration of upstream landscapes. Characterizing upstream features is critical for effectively understanding, managing, and conserving riverine ecosystems. However, watershed delineation is a major challenge if hundreds to thousands of watersheds must be delineated or if a study spans a large geographic extent. Further, site-specific watershed delineations do not provide a framework for easily and quickly applying analytical results to new, un-sampled locations. We developed a database of >100 landscape metrics for ~2.7 million watersheds within the conterminous USA: The Stream-Catchment (StreamCat) Dataset. These landscape metrics include both natural (e.g., climate, soils, geology) and anthropogenic (e.g., dams, agriculture, urbanization) factors, and were derived within and link to the National Hydrography Dataset Plus v.2 (NHDPlusV2), allowing for rapid extraction of upstream characteristics for stream-based studies. The framework uses topological flow information contained within the NHDPlusV2 to summarize upstream characteristics for each NHDPlusV2 stream segment. Locations of field samples can be integrated with the framework of upstream landscape metrics to derive site-based watershed metrics. Variation in landscape features or model results can be presented visually and provide a unique tool for assessing analyses. We provide an example of how the framework can be used to visualize variation in key landscape indicators of water quality such as urbanization and provide an input to national stream biological condition modeling. In addition to streams, we show how the process can be applied to derive a similar framework for lakes.