Reservoir Morphology Data Series
Many descriptors (measures) of surface-water reservoir basin features including physical, chemical, morphological, physiographic, hydrologic, and landscape characteristics are available that are likely to be related to reservoir eutrophication and impairment, reservoir fish habitat degradation, and invasive aquatic plant habitat infestation. The U.S. Geological Survey, in cooperation with the Reservoir Fisheries Habitat Partnership, combined multiple national databases to create one comprehensive national reservoir database and to calculate new morphological metrics for 3,828 reservoirs.
The database describes shape and form of individual reservoirs, within its watershed, as well as hydrologic measures. Information in the database can be used to estimate, for example, littoral zone size (shallow-water habitat) related to reservoir volume (index of reservoir permanence), shoreline development (measured reservoir shoreline distance relative to the circumference of a circle of the same surface area) and other metrics that can influence sediment and nutrient retention (eutrophication), fisheries habitat, invasive aquatic plant habitat infestation, and other functions and impairments. With the inclusion of watershed attributes from the various USGS major river basin SPARROW models, another 50 or more measures or characteristics related to each reservoir were included, like annualized nutrient loads and yields, sources and origins.
One comprehensive database will assist water-resource managers in their understanding of local reservoir morphology and water chemistry characteristics throughout the continental United States. The RMD has been delivered to NFHP’s Science and Data Committee and discussions on inclusion of this information (along with the aforementioned reservoir habitat impairment information) in the national assessment are ongoing. The RMD has been published as a U.S. Geological Survey Technical Series entitled “A reservoir morphology database for the conterminous United States”; Data Series 1062. The report was authored by Kirk D. Rodgers.
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