1. SANITARY SEWER EXFILTRATION & INFILTRATION RISK ASSESSMENT Meredith S. Moore Penn State MGIS Program Advisor: Dr. Barry Evans GEOG 596A, Fall 2014

2. PRESENTATION OVERVIEW  Background – explanation of the problem  Previous Study Methodology  Objectives  Approach – identification and incorporation of relevant datasets  Proposed Methodology  Goals & Deliverables  Timeline  References

3. BACKGROUND Water Quality Perspective: Localized study from 2000 implicated sewage as a pollution threat to groundwater. http://www.krwa.org/water-wastewater/ Broken sewer pipes allow for exfiltration of sewage into the surrounding soil.

4. Sewer Utility Perspective: Infiltration of ground- water causes infrastructure capacity problems. Groundwater infiltration into sewer line documented during CCTV investigation

5. Comparison of sewer line and groundwater elevations can be straightforward with survey-grade stream cross section elevation data. Elevation Comparisons: Example

6. Determining Groundwater Elevation PREVIOUS STUDY METHODOLOGY

7. Scoring Exfiltration Risk

8. OBJECTIVES  Perform a Risk Assessment for both exfiltration of sewage and infiltration of groundwater  Provide meaningful data to incorporate into a prioritization strategy for sewer line rehabilitation and repair  Provide data to Water Quality to support targeted water quality monitoring

9. APPROACH  Groundwater elevation (water table) surface  Infrastructure information (i.e. pipe elevation, rehab status, material, flow volume) Two datasets must be developed to facilitate the risk assessment:

10. Determining Groundwater Elevation Existing regional water table maps for the NC Piedmont are not considered useful due to variable local conditions.  Available Datasets:  Flood study: surveyed stream cross section elevations  Bare Earth LiDAR-derived DEMs for streambed and ground surface elevations  Well depth and static water level data  Depth to Water raster developed by USGS in 2001  Soil Surveys  National Wetlands Inventory  CCTV infiltration study data

11. Survey-grade grade elevation points were collected along cross sections on FEMA- regulated streams for a Mecklenburg County flood study.

12. DEMs were developed from bare earth LiDAR data that was flown in 2012. Not all parts of the county have been processed. The FEMA stream centerline layers were “burned in” using this surface.

13. Despite good coverage of wells with static water level data; it is unknown if the water level reflects the level of the surficial aquifer, or the pressure of groundwater within bedrock fractures. Relevant wells can possibly be extracted using bedrock depth data from soil surveys.

14. Static Water Levels  The static water level of wells drilled into water-bearing fractures in bedrock is related to the pressure within the aquifer, not the elevation of the surficial aquifer. http://www.maine.gov/dacf/mgs/explore/water/facts/aq-01.gif

15. An existing groundwater elevation surface developed by USGS in 2001 is not intended for site-specific analysis. It is a modeled surface and uses low resolution elevation and slope data. Redeveloping this surface with recent, high-resolution LiDAR is a potential approach.

16. The 1980 Mecklenburg County NRCS soil survey includes areas with shallow bedrock and a shallow water table.

17. The National Wetlands Inventory map service provides a reference for locations that can be assumed to have a water table near the ground surface.

18. Charlotte-Mecklenburg Utilities has noted the locations of groundwater infiltration during CCTV investigations. These locations can be used to “test” different groundwater elevation surfaces for accurate predictions.

19. Incorporating Sewer Infrastructure Information: Scoring This table shows the failure potential scores assigned to different pipe materials during a previous study. Higher scores indicate a higher likelihood of pipe failure. If a sewer line had been recently rehabbed, a score of 1 was automatically assigned. This table shows the scores assigned to different flow volume ranges during a previous study. Higher scores represent more potential damage that can result from infiltration of groundwater or exfiltration of sewage.

20.  Develop interpolated groundwater elevation raster and raster using USGS methods with higher-quality data. Test these two rasters and the existing USGS raster for accuracy with CCTV infiltration data.  Assign scores to pipes for material type, flow volume, and rehab status. Consider utilizing other available datasets.  Select pipes at risk for infiltration due to position below the water table. Develop infiltration risk ranking using pipe material and rehab status scores.  Score pipes above the water table for exfiltration risk based on their distance above the water table (closer = higher risk score). Develop exfiltration risk ranking using these scores; as well the pipe material, flow volume, and rehab status scores. PROPOSED METHODOLOGY

21. GOALS & DELIVERABLES  Deliver a prioritized dataset to the engineers that plan pipe rehabilitation and repair scheduling. CMUD will be concerned with both exfiltration and infiltration risk assessment.  Provide an exfiltration risk dataset to Water Quality to support targeted water quality monitoring.

22. TIMELINE  Continue with analysis through winter and early spring  Late Spring/Early Summer Conference such as Esri’s Southeast User Conference

23. REFERENCES  Bannister, Roger A. (2013). Incorporating Professional Judgment into Groundwater Contouring Tools within GIS. Provided by Roger Bannister.  Department of Agriculture, Conservation and Forestry. (2005). Sand and Gravel Aquifers. Retrieved from http://www.maine.gov/dacf/mgs/explore/water/facts/aquifer.htm [Accessed 09/18/2014]. http://www.maine.gov/dacf/mgs/explore/water/facts/aquifer.htm  Fels, John E., & Matson, Kris C. (1996). Approaches to Automated Water Table Mapping. Retrieved from http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/sf_papers/matson_kris/santa-fe.2.html [Accessed 09/03/2014]. http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/sf_papers/matson_kris/santa-fe.2.html  Mecklenburg County Geospatial Services (2014). Mecklenburg County Well & Flood Study layers [Data files]. Provided by Jamie Metz of Mecklenburg County Geospatial Services.  USDA, NRCC. (2013). Soil Survey Geographic (SSURGO) database for Mecklenburg County, North Carolina [Data file]. Available from http://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx [Accessed 09/03/2014].http://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx  USFWS. Map Service for National Wetlands Inventory. Available from http://107.20.228.18/arcgis/rest/services/Wetlands/MapServer http://107.20.228.18/arcgis/rest/services/Wetlands/MapServer  USGS. (2001). Estimated Depth to Water, North Carolina [Data file]. Provided by Silvia Terziotti of USGS.  USGS. (2012). Groundwater Frequently Asked Questions. Retrieved from http://nc.water.usgs.gov/about/faq_ground.html [Accessed 08/22/2014]. http://nc.water.usgs.gov/about/faq_ground.html