Associated dataset: The competing impacts of climate change and nutrient reductions on dissolved oxygen in Chesapeake Bay

This research uses an estuarine-watershed hydrodynamic–biogeochemical modeling system along with projected mid-21st-century changes in temperature, freshwater flow, and sea level rise to explore the impact climate change may have on future Chesapeake Bay dissolved-oxygen (DO) concentrations and the potential success of nutrient reductions in attaining mandated estuarine water quality improvements

Evaluating Confidence in the Impact of Regulatory Nutrient Reduction on Chesapeake Bay Water Quality

Excess nutrients derived from anthropogenic activity have resulted in the degradation of coastal water quality and an increase in low-oxygen and hypoxic events worldwide. In an effort to curb these impacts and restore water quality in the Chesapeake Bay, a maximum load of nutrients has been established based on a framework of regulatory standards and models. This research aims to evaluate the projected changes in water quality resulting from the implementation of these nutrient reductions by applying the regulatory methodology to two different models that have been previously shown to have similar model skill. Results demonstrate that although the two models differ structurally and produce a different degree of absolute change, they project a similar relative improvement in water quality along the main stem of the Chesapeake Bay and the lower reaches of the tributaries. Furthermore, the models largely agree on the attainment of regulatory water quality standards as a result of nutrient reduction, while also establishing that meeting water quality standards is relatively independent of hydrologic (wet/dry) conditions. By developing a Similarity Index that compares model results across habitat, time, and methodology, this research identifies the locations and causes of greatest uncertainty in modeled projections of water quality. Although there are specific locations and times where the models disagree, overall this research lends support and increased confidence to the appropriateness of the nutrient reduction levels and in the general impact of nutrient reduction on Chesapeake Bay water quality under current environmental conditions

A 3D unstructured-grid model for Chesapeake Bay: importance of bathymetry

We extend the 3D unstructured-grid model previously developed for the Upper Chesapeake Bay to cover the entire Bay and its adjacent shelf, and assess its skill in simulating saltwater intrusion and the coastal plume. Recently developed techniques, including a flexible vertical grid system and a 2nd-order, monotone and implicit transport solver are critical in successfully capturing the baroclinic responses. Most importantly, good accuracy is achieved through an accurate representation of the underlying bathymetry, without any smoothing. The model in general exhibits a good skill for all hydrodynamic variables: the averaged root-mean-square errors (RMSE‟s) in the Bay are 9 cm for sub-tidal frequency elevation, 17 cm/s for 3D velocity time series, 1.5 PSU and 1.9 PSU for surface and bottom salinity respectively, 1.1 °C and 1.6 °C for surface and bottom temperature respectively. On the shelf, the average RMSE for the surface temperature is 1.4 °C. We highlight, through results from sensitivity tests, the central role played by bathymetry in this estuarine system and the detrimental effects, from a common class of bathymetry smoothers, on volumetric and tracer fluxes as well as key processes such as the channel-shoal contrast in the estuary and plume propagation in the coast. Associated Data is available: https://doi.org/10.21220/V5HK5

Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison

As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and biogeochemical complexity. To this end, 2-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratification, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen parameterizations, in contrast to the more complex full biogeochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesapeake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density gradient