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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).

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A eutrophication model developed to generate primaryproduction 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. Water Environ. Res., 80, 853 (2008).

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 *