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