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This research examined the relationship between sediment sample data taken at Potential Release Sites (PRSs) and storm water samples taken at selected sites in and around Los Alamos National Laboratory (LANL). The PRSs had been evaluated for erosion potential and a matrix scoring system implemented. It was assumed that there would be a stronger relationship between the high erosion PRSs and the storm water samples. To establish the relationship, the research was broken into two areas. The first area was raster-based modeling, and the second area was data analysis utilizing the raster based modeling results and the sediment and storm water sample results.
Two geodatabases were created utilizing raster modeling functions and the Arc Hydro program. The geodatabase created using only Arc Hydro functions contains very fine catchment drainage areas in association with the geometric network and can be used for future contaminant tracking. The second geodatabase contains sub-watersheds for all storm water stations used in the study along with a geometric network.
The second area of the study focused on data analysis. The analytical sediment data table was joined to the PRSs spatial data in ArcMap. All PRSs and PRSs with high erosion potential were joined separately to create two datasets for each of 14 analytes. Only the PRSs above the background value were retained. The storm water station spatial data were joined to the table of analyte values that were either greater than the National Pollutant Discharge Elimination System (NPDES) Multi-Sector General Permit (MSGP) benchmark value, or the Department of Energy (DOE) Drinking Water Defined Contribution Guideline (DWDCG). Only the storm water stations were retained that had sample values greater than the NPDES MSGP benchmark value or the DOE DWDCG. Separate maps were created for each analyte showing the sub-watersheds, the PRSs over background, and the storm water stations greater than the NPDES MSGP benchmark value or the DOE DWDCG. Tables were then created for each analyte that listed the PRSs average value by storm water station allowing a tabular view of the mapped data. The final table that was created listed the number of high erosion PRSs and regular PRSs over background values that were contained in each watershed.
An overall relationship between the high erosion PRSs or the regular PRSs and the storm water stations was not identified through the methods used in this research. However, the Arc Hydro data models created for this analysis were used to track possible sources of contamination found through sampling at the storm water gaging stations. This geometric network tracing was used to identify possible relationships between the storm water stations and the PRSs. The methods outlined for the geometric network tracing could be used to find other relationships between the sites. A cursory statistical analysis was performed which could be expanded and applied to the data sets generated during this research to establish a broader relationship between the PRSs and storm water stations.