This research aims to develop statistical relationships between pollutant loadings and climate and traffic data. More importantly, the research will develop a methodology by which we can estimate pollutant loadings on a highway segment or watershed basis. The methodology will be GIS based to superimpose the various effects of the roadway to establish the loadings on a segment or basin basis. The methodology will help identify Best Management Practices on a case-by-case basis as required in the NPDES requirements.
UNC Charlotte researchers were contracted by NCDOT to monitor and characterize pollutants in highway runoff from several roadway sites across North Carolina as part of our NPDES (National Pollution Elimination Discharge System) permit requirements. This data will be used to develop a statistical relationship between runoff water quality and climate, traffic and physiographic road conditions (traffic and roadway maintenance activities) in order to predict pollutant loadings for the roadways across the State. The predictive relationships will then be applied to a GIS platform that could be used to predict NPS road source pollutant loadings for the various physiographic regions.
The goal is to provide an automatic, scientifically based model (GIS NPS platform or model) that can be used: to calculate basin wide pollutant loadings from roadway corridors; to prioritize outfall sensitive water quality sites to determine the installation of Best Management Practices (BMP's) to treat highway runoff; and to compare the estimated GIS NPS data with existing estimates of NPS pollutant loadings."
