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Apr 26, 2012

Using Eutrophication Modeling to Predict the Effectiveness of River Restoration Efforts

Publication: Engineering Approaches to Ecosystem Restoration

Abstract

Massive summer fish kills in 1995 drew public attention to the deteriorating water quality in North Carolina's Neuse River Estuary. Nitrogen loading to the estuary has increased dramatically due to increases in population, agricultural activity, and livestock production. Widespread anoxia and fish kills have occurred occasionally in the Neuse River Estuary in the past, but occurred in both 1995 and 1996. In addition, problems associated with algal blooms and macrophytes are at all time highs. In response, the State has drafted regulations aimed at reducing nitrogen loading to the estuary by 30 percent. At the same time, the State has funded a research project to predict the water quality improvement that will result from reduced nutrient loading, and to plan for future management of the river basin. This three-phase project, referred to as MODMON (MODeling and MONitoring), will include collection of tightly coupled water quality, fisheries, hydrodynamic, and sediment data; application of a eutrophication model to predict the results of reduced nitrogen loading; and development of recommendations for longer-term development of a watershed-river-estuary water quality model focusing on management outcomes. Results from initial water quality monitoring showed the estuary to be intermittently anoxic even during "good" years such as 1997. The special characteristics of the predictive eutrophication modeling effort now underway are also discussed. These characteristics include a large database of water quality and ecosystem rate measurements, the existence of a multi-disciplinary monitoring effort, parallel short-term and long-term model development efforts, and incorporation of an uncertainty analysis into the process-based eutrophication model.

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Go to Engineering Approaches to Ecosystem Restoration
Engineering Approaches to Ecosystem Restoration
Pages: 687 - 692

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Published online: Apr 26, 2012

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James D. Bowen
A.M.ASCE
Assistant Professor, Department of Engineering Technology, University of North Carolina at Charlotte, Charlotte NC 28223

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