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Estimation bias in water-quality constituent concentrations and fluxes: A synthesis for Chesapeake Bay rivers and streams

April 24, 2019

Flux quantification for riverine water-quality constituents has been an active area of research. Statistical approaches are often employed to make estimation for days without observations. One such approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS) method. While WRTDS has been used in many investigations, there is a general lack of effort to identify factors that influence its estimation bias. This work was aimed to (1) synthesize and compare WRTDS estimation bias for constituent concentrations and fluxes for rivers and streams in the Chesapeake Bay watershed (including headwater sites) and (2) identify controlling factors from five broad categories (watershed size, sampling practice, concentration and discharge conditions, land use, and geology). Five major constituents were considered, namely, suspended sediment (SS), total phosphorus (TP), total nitrogen (TN), orthophosphate (PO4), and nitrate-plus-nitrite (NOx). For both concentration and flux, estimation bias follows the general order of SS > TP > PO4 > TN ≈ NOx. Median TN and NOx bias statistics were near zero, with an equal distribution of small positive and negative bias. TP, PO4, and SS each showed a median positive bias across sites of

Publication Year 2019
Title Estimation bias in water-quality constituent concentrations and fluxes: A synthesis for Chesapeake Bay rivers and streams
DOI 10.3389/fevo.2019.00109
Authors Qian Zhang, Joel D. Blomquist, Douglas L. Moyer, Jeffrey G. Chanat
Publication Type Article
Publication Subtype Journal Article
Series Title Frontiers in Ecology and Evolution
Index ID 70216034
Record Source USGS Publications Warehouse
USGS Organization Maryland-Delaware-District of Columbia Water Science Center
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