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June 20, 2012
Separating the Forest from the Trees: Making Intelligent Asset Decisions Using a GIS Decision Tool
Marc A. Lehmann, PE
Agenda
• Project location
• Project description
• Brief history
• Methodology description
• Closure
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Project Location
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Project Description
• Detailed studies to identify the locations and causes of:
– Sewage overflows from manholes
– Sewage system surcharging
– Sewage backup into basements
• Mitigate and/or eliminate for a selected performance target
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Decision Tree History
• 2005: Method developed for the Livingston/James Project
• 2009: Method adopted and used for a major municipality in Minnesota
• 2009: Ported to C# for inclusion in ArcGIS 10 platform
• 2010: Method used on the Northwest Alum Creek Project
• 2011: Method to be used in later phase in Medellin, Colombia
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So what is the Decision Tree?
• GIS-based decision making dashboard incorporating:
– PACP CCTV Data
– Hydraulic and hydrologic data
– Spatial GIS data (topography, surface development, etc.)
• Enabling:
– Flexible and reproducible decision making
– Viewing CCTV footage while overlaying recommendations
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Collapsed View
1. Definitions
2. Decisions
3. Prioritization
5. Data Queries/Review
4. Cost Estimating
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5-Step Methodology
• Step 1: Define problems
• Step 2: Decision making
• Step 3: Prioritization
• Step 4: Cost comparison
• Step 5: Data queries and review
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Step 1: Define the Problem
• Roots
• Infiltration
– Runners and gushers
• Pipe sags
• Pipe cracks and fractures
• Structural Level 5 defects
Paper ID #
• Relies on PACP incident codes as a point of beginning
• How much is too much?
• Which observations are more important to others?
– Roots vs. structural defects
– Grease vs. sags
Paper ID #
Step 2: Decision Making
Paper ID #
The Method
Decision Making Example
Step 3: Prioritization
• Surface development
– Under a major structure?
– Near a hospital?
– Service area?
• Flow regime
– Low velocity?
– Under capacity?
– High I/I?
• Depth
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Step 4: Cost Comparison
• Level of service
– What is desired?
– What is required?
– Does the system meet LOS?
• Available resources
– Does program burden existing funding?
– Does the program need to be adjusted?
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Paper ID #
Step 5: Data Queries
• Where are improvements located?
• How can these improvements be programmed?
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Closure
• Paradigm shift from “Find & Fix”
• Methodology is transparent
– Assumptions are imbedded directly into the tree
– Removes subjectivity
• Methodology is flexible
– Any quantifiable “finding” can be incorporated
– Impact of changes can be seen very quickly
• Basis of improvements is reproducible
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For More Information
• Marc A. Lehmann, PE, CDM Smith
• C. Timothy Fallara, PE, City of Columbus
• Rodney Moeller, PE, CDM Smith
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