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Severity and extent of alterations to natural streamflow regimes based on hydrologic metrics in the conterminous United States, 1980–2014

December 30, 2019

Alteration of the natural streamflow regime by land and water management, such as land-cover change and dams, is associated with aquatic ecosystem degradation. The severity and geographic extent of streamflow alteration at regional and national scales, however, remain largely unquantified. The primary goal of this study is to characterize the severity and extent of alterations to natural streamflow regimes for 1980–2014 based on hydrologic metrics at 3,355 U.S. Geological Survey streamgages in the conterminous United States. Twelve hydrologic metrics with known relevance to aquatic ecosystem health were used to characterize the streamflow regime. Alterations to the 12 hydrologic metrics were quantified by taking ratios of the metrics calculated from observed daily streamflow records divided by the same metrics predicted for natural conditions by random forest statistical models. Some level of streamflow alteration (diminishment or inflation of hydrologic metrics) compared to natural conditions was indicated at about 80 percent of the assessed streamgages across the conterminous United States. The severity of alteration differed among ecoregions because of differences in dominant land and water management practices. Finally, when compared over the period 1980–2014, climate variability generally played a minor role in the alteration of streamflows across the United States when compared to the effects of land and water management.

Publication Year 2019
Title Severity and extent of alterations to natural streamflow regimes based on hydrologic metrics in the conterminous United States, 1980–2014
DOI 10.3133/sir20195001
Authors Ken Eng, Daren Carlisle, Theodore E. Grantham, David M. Wolock, Rosaly L. Eng
Publication Type Report
Publication Subtype USGS Numbered Series
Series Title Scientific Investigations Report
Series Number 2019-5001
Index ID sir20195001
Record Source USGS Publications Warehouse
USGS Organization WMA - Integrated Modeling and Prediction Division