Assessing biophysical controls on Gulf of Mexico hypoxia through probabilistic modeling

Abstract

A mechanistic model was developed to predict midsummer bottom-water dissolved oxygen (BWDO) concentration and hypoxic area on the Louisiana shelf of the northern Gulf of Mexico, USA (1985-2011). Because of its parsimonious formulation, the model possesses many of the benefits of simpler, more empirical models, in that it is computationally efficient and can rigorously account for uncertainty through Bayesian inference. At the same time, the model incorporates important biophysical processes such that its parameterization can be informed by field-measured biological and physical rates. The model is used to explore how freshwater flow, nutrient load, benthic oxygen demand, and wind velocity affect hypoxia on the western and eastern sections of the shelf, delineated by the Atchafalaya River outfall. The model explains over 70% of the variability in BWDO on both shelf sections, and outperforms linear regression models developed from the same input variables. Model results suggest that physical factors (i.e., wind and flow) control a larger portion of the year-to-year variability in hypoxia than previously thought, especially on the western shelf, though seasonal nutrient loads remain an important driver of hypoxia, as well. Unlike several previous Gulf hypoxia modeling studies, results do not indicate a temporal shift in the system's propensity for hypoxia formation (i.e., no regime change). Results do indicate that benthic oxygen demand is a substantial BWDO sink, and a better understanding of the long-term dynamics of this sink is required to better predict how the size of the hypoxic zone will respond to proposed reductions in nutrient loading.

Ensemble modeling informs hypoxia management in the northern Gulf of Mexico

“…We estimate that the probability that hypoxia would be <5,000 km 2 under an 80% load reduction is 87%. The 59% reduction is larger than the 45% reduction called for in the most recent Action Plan (17), but within the range of previous individual models (5,30,31,(33)(34)(35)(36). This percentage is also higher than recommendations made for other eutrophic systems.…”

“…Previous studies suggested no apparent correlation between hypoxic area (or predictive errors) in 1 y and either N load or hypoxic extent in the previous year. Thus, including predictors representing carryover effects from the previous year did not substantially improve model fit (31,35,69). The loads used by each model show similar interannual patterns (Fig.…”

“…The NCSU model, calibrated for 1985-2011, explains ∼75% of the variability in BWDO and 70% of the variability in hypoxic area. The cross-validation performed similarly to the full calibration (R 2 = 72% for BWDO) (31). This model was first used for hypoxia forecasts in 2015 (Fig.…”

“…This Bayesian biophysical model predicts BWDO concentrations in western and eastern segments of the Louisiana-Texas shelf that are separated by the Atchafalaya River outfall (31). BWDO predictions are converted to hypoxic area by using empirical relationships between mean BWDO and hypoxic area, both of which are determined from a geostatistical model (70).…”

“…BWDO predictions are converted to hypoxic area by using empirical relationships between mean BWDO and hypoxic area, both of which are determined from a geostatistical model (70). The model is a steady-state solution to mechanistic, massbalance equations (31), and is calibrated within a Bayesian framework that accounts for prior information on model parameters. It systematically characterizes parameter and prediction uncertainty (78).…”