Abstract
Wetland restoration can improve water quality by reducing concentrations of sediment, total phosphorus, and nitrate in runoff. Managers need a simple method to choose among many possible restoration sites, particularly in large agricultural basins covering thousands of square kilometers. The purpose of this paper is to outline a method for prioritizing and monitoring wetland restoration sites in light of the factors that affect water-quality improvement by wetlands. These factors are categorized as loading factors, path factors, and process factors. The method for prioritizing wetland restoration sites depends primarily on assessing the potential effectiveness of the wetland for improving water quality. Three types of effectiveness are considered: problem effectiveness (is the site in an area with known water-quality problems?), function effectiveness (is the site likely to improve water quality more or less than other sites?), and information effectiveness (does the site fit within an overall research plan to gain information on how wetlands improve water quality?). The variables of hydraulic residence time, hydraulic flux, and wetland area, volume, and average depth are combined into a single variable termed ε and used as a proxy for estimating the relative function effectiveness of potential restoration sites. Monitoring restoration sites is targeted at establishing a minimum data set that can be collected consistently at different sites over time, and that can be used for inter-site comparison with simple statistical techniques. The Minnesota River Basin is used as an example throughout to demonstrate the types of data that are available to plan wetland restoration. While this paper focuses on the water-quality benefits, wetland restoration should be a multi-disciplinary effort to integrate other benefits of restoration, such as improvement of wildlife habitat and flood abatement.
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Almendinger, J. A method to prioritize and monitor wetland restoration for water-quality improvement. Wetlands Ecology and Management 6, 241–252 (1998). https://doi.org/10.1023/A:1008439031165
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DOI: https://doi.org/10.1023/A:1008439031165