10.1021/es504029c.s001
Brian A. Pellerin
Brian A.
Pellerin
Brian
A. Bergamaschi
Brian
A.
Bergamaschi
Robert
J. Gilliom
Robert
J.
Gilliom
Charles G. Crawford
Charles G.
Crawford
JohnFranco Saraceno
JohnFranco
Saraceno
C. Paul Frederick
C. Paul
Frederick
Bryan D. Downing
Bryan D.
Downing
Jennifer C. Murphy
Jennifer C.
Murphy
Mississippi
River Nitrate Loads from High Frequency
Sensor Measurements and Regression-Based Load Estimation
American Chemical Society
2015
time steps
Gulf hypoxia formation
WRTDS
Mississippi River
load estimation techniques
LOADEST
Mississippi River Nitrate Loads
High Frequency Sensor Measurements
2015-12-17 05:31:32
Journal contribution
https://acs.figshare.com/articles/journal_contribution/Mississippi_River_Nitrate_Loads_from_High_Frequency_Sensor_Measurements_and_Regression_Based_Load_Estimation/2042952
Accurately quantifying nitrate (NO<sub>3</sub><sup>–</sup>) loading from the Mississippi River is
important for predicting
summer hypoxia in the Gulf of Mexico and targeting nutrient reduction
within the basin. Loads have historically been modeled with regression-based
techniques, but recent advances with high frequency NO<sub>3</sub><sup>–</sup> sensors allowed us to evaluate model performance
relative to measured loads in the lower Mississippi River. Patterns
in NO<sub>3</sub><sup>–</sup> concentrations and loads were
observed at daily to annual time steps, with considerable variability
in concentration-discharge relationships over the two year study.
Differences were particularly accentuated during the 2012 drought
and 2013 flood, which resulted in anomalously high NO<sub>3</sub><sup>–</sup> concentrations consistent with a large flush of stored
NO<sub>3</sub><sup>–</sup> from soil. The comparison between
measured loads and modeled loads (LOADEST, Composite Method, WRTDS)
showed underestimates of only 3.5% across the entire study period,
but much larger differences at shorter time steps. Absolute differences
in loads were typically greatest in the spring and early summer critical
to Gulf hypoxia formation, with the largest differences (underestimates)
for all models during the flood period of 2013. In additional to improving
the accuracy and precision of monthly loads, high frequency NO<sub>3</sub><sup>–</sup> measurements offer additional benefits
not available with regression-based or other load estimation techniques.