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Uncertainty in streamflow measurements significantly impacts estimates of downstream nitrate export

Bibliographic Data

ID15550714
AuthorsShannon L Speir (0000-0002-3624-0327, University of Arkansas at Fayetteville, corresponding author), C Nathan Jones (0000-0002-5804-0510, University of Alabama System), Arial J Shogren (0000-0002-1284-3836, University of Alabama), Carla L Atkinson (0000-0002-6430-7613, University of Alabama)
Year2023
Volume18
Issue12
Pages124045-124045
Publication date2023-11-08
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/ad0ad2
OpenAlexW4388483858
LanguageEN
References cited47

Across watershed science, two key variables emerge–streamflow and solute concentration–which serve as the basis for efforts ranging from basic watershed biogeochemistry research to policy decisions surrounding watershed management. However, we rarely account for how error in discharge (Q) impacts estimates of downstream nutrient loading. Here, we examined the impact of uncertainty in streamflow measurements on estimates of downstream nitrate export using publicly available data from the U.S. Geological Survey (USGS). We characterized how uncertainty in stage-discharge relationships impacts annual flux estimates across 70 USGS gages. Our results indicate the interquartile range of relative error in Q was 33% across these USGS sites. We documented a wide range in mean error in annual nitrate loads; some sites were underestimated (−105%), while predicted loads at other sites vastly overestimated (500%). Overall, any error in estimating Q leads to significant unpredictability of annual nutrient loads, which are often used as critical success benchmarks for governmental nutrient reduction strategies. Moreover, error in annual nitrate loads (as mass, kg) increases with mean Q; thus, as high flows become more unpredictable and intense under future climate change, error in estimates of downstream nutrient loading may also increase. Together, this indicates that error in Q may drastically influence our measures of water quality success and decrease our ability to accurately quantify progress towards algal bloom and ‘dead zone’ reduction

Biogeochemistry · Downstream (manufacturing · Geography · Hydrology (agriculture · Nitrate · Nutrient · Range (aeronautics · Streamflow · Water quality · Watershed · Computer Science · Environmental Science · Groundwater and Isotope Geochemistry · Hydrology and Watershed Management Studies · Soil and Water Nutrient Dynamics · Ecology · Geology · Oceanography

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