Inter-model comparison of simulated Gulf of Mexico hypoxia in response to reduced nutrient loads: effects of phytoplankton and organic matter parameterization.

Complex simulation models are a valuable tool to inform nutrient management decisions aimed at reducing hypoxia in the northern Gulf of Mexico, yet simulated hypoxia response to reduced nutrients varies greatly between models. We compared two biogeochemical models driven by the same hydrodynamics, the Coastal Generalized Ecosystem Model (CGEM) and Gulf of Mexico Dissolved Oxygen Model (GoMDOM), to investigate how they differ in simulating hypoxia and their response to reduced nutrients. Different phytoplankton nutrient kinetics produced 2-3 times more hypoxic area and volume on the western shelf in CGEM compared to GoMDOM. Reductions in hypoxic area were greatest in the western shelf, comprising 72% (~4,200 km2) of the total shelfwide hypoxia response. The range of hypoxia responses from multiple models suggests a 60% load reduction may result in a 33% reduction in hypoxic area, leaving an annual hypoxic area of ~9,000 km2 based on the latest 5-yr average (13,928 km2).

A modeling study to determine the contribution of interbasin versus intrabasin phosphorus loads on the southwestern nearshore of Lake Ontario.

Elevated phosphorus and nuisance algae such as Cladophora have been persistent environmental concerns in the coastal areas of Lake Ontario. Phosphorus is regarded as one of the drivers of nearshore Cladophora and the most likely mitigation that can be used to control levels of this nuisance algae in the lakes. The Niagara River, carrying the Lake Erie interbasin load, is the major contributor of the overall phosphorus load to Lake Ontario. Due to circulation patterns in the lake, this contribution is especially significant in the southwestern nearshore areas. Here we apply a mathematical model to provide insight into the relative contribution of the Niagara River versus loadings from local rivers (intrabasin loads) on the nearshore phosphorus concentrations in this region. We performed numerical experiments to determine to what extent the Niagara, Genesee and smaller local rivers impact the nearshore (< 20 m depth) phosphorus concentrations. Our model results show that the Niagara River dominates the nearshore region between its discharge location and the Genesee River's mouth, but the Genesee River strongly impacts the nearby Ontario Beach region in the very nearshore (< 5 m depth). Smaller rivers have some impact close to their discharge locations. However, uncertainty with the Niagara River phosphorus load is the limiting factor in making any credible nearshore phosphorus predictions. Model accuracy is also impacted by insufficient short time scale phosphorus loads for all of the rivers, the dynamic nature of the lake circulation in shallow nearshore areas, and the simplified assumptions of the model.

The impact of alternative nutrient kinetics and computational grid size on model predicted primary production and hypoxic area in the northern Gulf of Mexico.

Model structure uncertainty is seldom calculated because of the difficulty and time required to perform such analyses. Here we explore how a coastal model using the Monod versus Droop formulations and a 6 km × 6 km versus 2 km 2 × km computational grid size predict primary production and hypoxic area in the Gulf of Mexico. Results from these models were compared to each other and to observations, and sensitivity analyses were performed. The different models fit the observations almost equally well. The 6k-model calculated higher rates of production and settling, and especially a larger hypoxic area, in comparison to the 2k-model. The Monod-based model calculated higher production, especially close to the river delta regions, but smaller summer hypoxic area, than the model using the Droop formulation. The Monod-based model was almost twice as sensitive to changes in nutrient loads in comparison to the Droop model, which can have management implications.

Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: successes and challenges.

Decision-support tools (DSTs) are often produced from collaborations between technical experts and stakeholders to address environmental problems and inform decision making. Studies in the past two decades have provided key insights on the use of DSTs and the importance of bidirectional information flows among technical experts and stakeholders - a process that is variously referred to as co-production, participatory modeling, structured decision making, or simply stakeholder participation. Many of these studies have elicited foundational insights for the broad field of water resources management; however, questions remain on approaches for balancing co-production with uncertainty specifically for watershed modeling decision support tools. In this paper, we outline a simple conceptual model that focuses on the DST development process. Then, using watershed modeling case studies found in the literature, we discuss successful outcomes and challenges associated with embedding various forms of co-production into each stage of the conceptual model. We also emphasize the "3 Cs" (i.e., characterization, calculation, communication) of uncertainty and provide evidence-based suggestions for their incorporation in the watershed modeling DST development process. We conclude by presenting a list of best practices derived from current literature for achieving effective and robust watershed modeling decision-support tools.

Modeling the Relative Importance of Nutrient and Carbon Loads, Boundary Fluxes, and Sediment Fluxes on Gulf of Mexico Hypoxia.

The Louisiana continental shelf in the northern Gulf of Mexico experiences bottom water hypoxia in the summer. In this study, we applied a biogeochemical model that simulates dissolved oxygen concentrations on the shelf in response to varying riverine nutrient and organic carbon loads, boundary fluxes, and sediment fluxes. Five-year model simulations demonstrated that midsummer hypoxic areas were most sensitive to riverine nutrient loads and sediment oxygen demand from settled organic carbon. Hypoxic area predictions were also sensitive to nutrient and organic carbon fluxes from lateral boundaries. The predicted hypoxic area decreased with decreases in nutrient loads, but the extent of change was influenced by the method used to estimate model boundary concentrations. We demonstrated that modeling efforts to predict changes in hypoxic area on the continental shelf in relationship to changes in nutrients should include representative boundary nutrient and organic carbon concentrations and functions for estimating sediment oxygen demand that are linked to settled organic carbon derived from water-column primary production. On the basis of our model analyses using the most representative boundary concentrations, nutrient loads would need to be reduced by 69% to achieve the Gulf of Mexico Nutrient Task Force Action Plan target hypoxic area of 5000 km(2).

The Lake Michigan eutrophication model, LM3-Eutro: model development and calibration.

A eutrophication model developed to generate primary-production estimates in Lake Michigan can simulate 17 state variables, including three plankton classes and several nutrients. The model, known as the Lake Michigan Eutrophication model (LM3-Eutro), has a high-resolution computational grid that enables good spatial description of spring temperature and phytoplankton concentrations, which have significant gradients in the lakes. The grid also allows the model to predict concentrations in nearshore areas and other regions of interest. The model provided more accurate estimates of algal light limitation based on three-hour intervals compared to daily averages that are used in most eutrophication models, especially during sunny summer days when algal photo-inhibition often occurs. Model output was compared to field data using statistical parameters such as squares of the correlation coefficients to determine the best model fit. The calibrated model output fit the field data reasonably well for nutrients and phytoplankton, which provided confidence in the framework, governing equations, and coefficients used.