Managers at Marine Corps Base Camp Lejeune must evaluate the environmental impacts of their proposed development plans. The effect of land cover changes on water quality is an important consideration for these evaluations. An interactive geospatial tool was developed in 2009. The tool allows managers to interactively select their proposed development site and input what the proposed land cover will be for the site. The tool returns the changes in average ammonium concentration in the tributary creeks. The tool incorporates water quality data collected by the DCERP project from 2008-2009 to drive the prediction model. The purpose of this project was to (1) improve usability of the tool to make it a spatial decision support system, (2) update the water quality data used to drive the statistics of the water quality prediction models, and (3) determine if using the National Land Cover Dataset (NLCD) from 2006 instead of the 2001 NLCD changes the relationship between land cover predictors and water quality response variables. Tool usability was enhanced by adding in-tool and external help menus, creating a user guide, and adding the ability to name and save outputs. The updated tool allows the user to run multiple land development scenarios for comparison without overwriting the previous results. Adding additional water quality data from 2007-2010 resulted in fewer significant water quality prediction models. The most predictive of these models was for organic nitrogen. The model, predicted by barren (rock/sand/clay), shrub/scrub, and grassland/herbaceous land covers, was incorporated into the decision support tool. Using land cover data from 2001 and 2006 allowed the same two water quality parameters to be predicted: NOx and ON. Managers at Marine Corps Base Camp Lejeune can use this data driven Spatial Decision Support System to evaluate how different development scenarios will affect the concentration of organic nitrogen in the tributary creeks on base.





Baker, Brittney (2011). A DECISION SUPPORT TOOL FOR PREDICTING WATER QUALITY BASED ON LAND COVER. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/3652.

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