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Identifying and Correcting Rain Gauge Measurement Errors Using a Highly Accurate Hydrologic Model and Radar Reflectivity Data Tim Kuhns, P.E., Orchard Hiltz & McCliment, Inc. Robert Czachorski, P.E., P.H., Orchard, Hiltz & McCliment, Inc. Scott Martin, Scio Township DPS Director
Introduction -Scio Township System- Service Area of 5.3 square miles located in Washtenaw County, Michigan serving approximately 16,000 residents All flows from system outlet to two main pump stations – Jackson Road Pump Station and Liberty Road Pump Station
Background -Scio Township I/I Monitoring/Removal- 2004 I/I Study found peak flows in excess of Jackson Road/Liberty Road Pump Station capacities 2006 I/I removal plan included rehab of 25% of system manholes 2008 Post Rehab monitoring included evaluation of effectiveness of system rehab
Approach of Study -2008 Post-Rehab Monitoring & System Rehab Effectiveness- Calibrate/Validate pre-rehabilitation model using flow, rainfall, and temperature data from 2004 monitoring Compare pre-rehabilitation model to post-rehabilitation data collected in 2008 to evaluate effectiveness A hydrologic model that controls for antecedent moisture effects is needed as the pre- and post- monitoring periods will have varying soil moisture conditions
Hydrologic Model Description -Effects of Antecedent Moisture on Wet Weather Flows- Antecedent Moisture: the relative wetness/dryness of a sewershed preceding a given storm event
Hydrologic Model Description -Effects of Antecedent Moisture on Wet Weather Flows- Scio Township’s system response to rainfall is highly affected by varying antecedent moisture conditions
Hydrologic Model Description -i3DLab Model- Continuous modeling approach as opposed to an event based model for I/I Separate models for inflow and infiltration vary continuously Model at each time step adjusted based on antecedent rainfall and temperature
Hydrologic Model Description -Typical Static Model Results-
Hydrologic Model Description -Typical Antecedent Moisture Model Results-
Detailed comparison of pre-rehab model to post-rehab flows indicates minimal I/I removal (<5%) Largest storm event (9/14/2008) resulted in poor match between pre-rehab model and post-rehab flows. Why? Jackson Road PS Findings -2008 Post-Rehab Monitoring & System Rehab Effectiveness-
Jackson Road PS Findings  -9/14/2008 Pre-Rehab Model and Post-Rehab Flow Discrepancy- Possible Sources of Error: Model Calibration Flow Measurement Rainfall Measurement
Rainfall Measurements -Review of Rainfall & Reflectivity Measurements at Gauge Locations- Two rain gauges installed as part of the study Gauge measurements differed between locations for 9/14/2008 event Reflectivity measurements at gauge locations should differ
Rainfall Measurements -Review of Rainfall & Reflectivity Measurements at Gauge Locations- Reflectivity measurements obtained from National Climatic Data Center Reflectivity measurements at gauge locations almost identical Indicates possible gauge error
Rainfall Measurements -Review of Rainfall & Reflectivity Measurements at Gauge Locations- Pulsing pattern at Jackson Road rain gauge further substantiates gauge failure
Rain Gauge Failure -Clogged Funnel- Pulsing pattern at Jackson Road rain gauge was result of clogged rain gauge
Correcting Rainfall Measurements -For Jackson Road Rain Gauge- Reflectivity readings at both rain gauges suggest similar rainfall patterns and volumes at each gauge site Rainfall measurements from WISD gauge were “spliced” into Jackson Road rainfall measurements Jackson Road pre-rehab model was run with corrected rainfall measurements
Conclusions -A Comprehensive Approach to Modeling- A continuous model that accurately predicts flows can be used to identify anomalies with rainfall and flow measurements. An event based model may not as easily identify these types of errors. A thorough evaluation of all error components (model prediction, rainfall, flow) should be completed for major calibration events to ensure model accuracy and confidence in the model results. Free and readily available radar reflectivity data can be used without pre-processing to assess the accuracy of rainfall measurements.

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How Hydrologic Modeling and Radar Rainfall Analysis Can Overcome Rain Gauge Errors in I/I Studies

  • 1. Identifying and Correcting Rain Gauge Measurement Errors Using a Highly Accurate Hydrologic Model and Radar Reflectivity Data Tim Kuhns, P.E., Orchard Hiltz & McCliment, Inc. Robert Czachorski, P.E., P.H., Orchard, Hiltz & McCliment, Inc. Scott Martin, Scio Township DPS Director
  • 2. Introduction -Scio Township System- Service Area of 5.3 square miles located in Washtenaw County, Michigan serving approximately 16,000 residents All flows from system outlet to two main pump stations – Jackson Road Pump Station and Liberty Road Pump Station
  • 3. Background -Scio Township I/I Monitoring/Removal- 2004 I/I Study found peak flows in excess of Jackson Road/Liberty Road Pump Station capacities 2006 I/I removal plan included rehab of 25% of system manholes 2008 Post Rehab monitoring included evaluation of effectiveness of system rehab
  • 4. Approach of Study -2008 Post-Rehab Monitoring & System Rehab Effectiveness- Calibrate/Validate pre-rehabilitation model using flow, rainfall, and temperature data from 2004 monitoring Compare pre-rehabilitation model to post-rehabilitation data collected in 2008 to evaluate effectiveness A hydrologic model that controls for antecedent moisture effects is needed as the pre- and post- monitoring periods will have varying soil moisture conditions
  • 5. Hydrologic Model Description -Effects of Antecedent Moisture on Wet Weather Flows- Antecedent Moisture: the relative wetness/dryness of a sewershed preceding a given storm event
  • 6. Hydrologic Model Description -Effects of Antecedent Moisture on Wet Weather Flows- Scio Township’s system response to rainfall is highly affected by varying antecedent moisture conditions
  • 7. Hydrologic Model Description -i3DLab Model- Continuous modeling approach as opposed to an event based model for I/I Separate models for inflow and infiltration vary continuously Model at each time step adjusted based on antecedent rainfall and temperature
  • 8. Hydrologic Model Description -Typical Static Model Results-
  • 9. Hydrologic Model Description -Typical Antecedent Moisture Model Results-
  • 10. Detailed comparison of pre-rehab model to post-rehab flows indicates minimal I/I removal (<5%) Largest storm event (9/14/2008) resulted in poor match between pre-rehab model and post-rehab flows. Why? Jackson Road PS Findings -2008 Post-Rehab Monitoring & System Rehab Effectiveness-
  • 11. Jackson Road PS Findings -9/14/2008 Pre-Rehab Model and Post-Rehab Flow Discrepancy- Possible Sources of Error: Model Calibration Flow Measurement Rainfall Measurement
  • 12. Rainfall Measurements -Review of Rainfall & Reflectivity Measurements at Gauge Locations- Two rain gauges installed as part of the study Gauge measurements differed between locations for 9/14/2008 event Reflectivity measurements at gauge locations should differ
  • 13. Rainfall Measurements -Review of Rainfall & Reflectivity Measurements at Gauge Locations- Reflectivity measurements obtained from National Climatic Data Center Reflectivity measurements at gauge locations almost identical Indicates possible gauge error
  • 14. Rainfall Measurements -Review of Rainfall & Reflectivity Measurements at Gauge Locations- Pulsing pattern at Jackson Road rain gauge further substantiates gauge failure
  • 15. Rain Gauge Failure -Clogged Funnel- Pulsing pattern at Jackson Road rain gauge was result of clogged rain gauge
  • 16. Correcting Rainfall Measurements -For Jackson Road Rain Gauge- Reflectivity readings at both rain gauges suggest similar rainfall patterns and volumes at each gauge site Rainfall measurements from WISD gauge were “spliced” into Jackson Road rainfall measurements Jackson Road pre-rehab model was run with corrected rainfall measurements
  • 17. Conclusions -A Comprehensive Approach to Modeling- A continuous model that accurately predicts flows can be used to identify anomalies with rainfall and flow measurements. An event based model may not as easily identify these types of errors. A thorough evaluation of all error components (model prediction, rainfall, flow) should be completed for major calibration events to ensure model accuracy and confidence in the model results. Free and readily available radar reflectivity data can be used without pre-processing to assess the accuracy of rainfall measurements.