Mississippi River nitrate loads from high frequency sensor measurements and regression-based load estimation

Abstract

Accurately quantifying nitrate (NO 3 – ) 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 3 – sensors allowed us to evaluate model performance relative to measured loads in the lower Mississippi River. Patterns in NO 3 – 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 3 – concentrations consistent with a large flush of stored NO 3 – 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 3 – measurements offer additional benefits not available with regression-based or other load estimation techniques.