Info What? Using InfoMaster to Develop a Rehabilitation and Replacement Plan



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Info What? Using InfoMaster to Develop a Rehabilitation and Replacement Plan Amanda Lei - City of San Jose Alex Palmatier - HDR 2014 HDR, Inc., all rights reserved.

Background Forecasting and Budget Data Management Lessons Learned Prioritizing CCTV Work Repair, Rehabilitation or Replacement?

Background Sewer System, Assessment Approaches and InfoMaster

City of San Jose Service Area Approximately 180 square miles Approximately 2,200 miles of sewer Approximately 985,000 residents 16 Lift Stations 90% clay pipe 85% 10-inch or smaller 45,000 Manholes Average system age approximately 45 years Median age is 52

Historical CCTV Program On-Call/As-Needed (project design/corrective maintenance) Inspections Completed by Contractors and City Crews 2010 Started SSCA Pilot program Currently Completed System Sample Set - 371 miles (usable data) Remainder Focused on High SSO Areas

3 rd Party Consent Decree For sewer mains with diameter smaller than 18-inches: o Inspecting mains within 200 feet of Water Bodies within two (2) years of CD Effective Date o Repair or replace mains that receive a PACP rating of 5 within one (1) year of determination o Repair or replace mains that receive a PACP rating of 4 within five (5) years of determination o Assess 70% of City s collection system within ten (10) years of CD Effective Date o Reporting of SSOs that discharge to a critical habitat area as defined by the Endangered Species Act

Historical Approach to Renewal Planning Risk-Based Renewal Planning Backward Looking Budget Based on Last Year Little knowledge of system risks Forward Looking Based on asset risk scores throughout system and long term forecasts of risk and cost Reactive Projects determined as problems arise during the year Proactive High risk assets slotted for renewal before failure occurs Budget Constrained Do as many projects as you can afford each year Risk or Budget Constrained Budget could be determined based on agreed risk targets for system Ignores asset and system risks Money is spent but overall risk may not have been reduced much Focused on risk management High risk assets addressed first Budget may rise or fall to meet risk targets San Jose Goal Risk Based Planning Represents a New Focus for Most Utilities

InfoMaster What? Analytical and Optimization Software Package by Innovyze Built On and Runs Inside ArcGIS Infrastructure Out-of-the-Box Improves Data Collection and Validation Smarter Decision Making

Likelihood of Failure Hydraulic Model Pressure Changes Roughness Multiple Calculation Options Consequence of Failure Pipe/Valve Criticality Flow Delivered Hydraulic Model Infrastructure Data Age Material Hospitals, Schools, etc Power, Industry, etc. Critical Facilities GIS Data CMMS & Work Orders Soil Type Railroads/Fault Lines Break History Repairs/Lining Calculation of Risk Population Density Street Paving GIS Data Traffic Analysis Community Relations Other Rehabilitation Costs Rehabilitation Engine Budget Scenarios What Does it Do? Workflow Diagram Prioritized Capital Plan

InfoMaster Why? GIS Data Management CCTV Viewer Risk Profile Capital Planning

Data Management

Challenges Data o Where is it coming from? Cond Assessment CCTV CIP Project CCTV O&M CCTV o Where does it go? Storage Access o How do we maintain it? Formats Quality Control

Solutions Use GIS as Database of Record o Data stored in SDE or GDB o Hyperlink to videos for viewing Combine Multiple Data Sources o CCTV PACP based Can accept anything tabular o Single Inspection Instance or Multiple o Can Use Any GIS Data

Data Collection Review of the Standards o Update to require PACP database as a deliverable o Develop a frequency interval for data submission o Develop and implement a QA criteria and QC protocol o Develop requirements for the use of specific codes Sag issues

Creating the InfoMaster Workspace Database Setup o Project o System Mapping Asset Attribute o Based on ESRI Data Model Connects to SDE or GDB Importing CCTV Data o Imports PACP Database

Importing GIS

Importing CCTV Data Validation Defect Mapping Defect Scoring Rehab Plan

Validation Errors Missing MH Missing Pipe Pipe Length Errors

Visualizing the Data Profile View

Visualizing the Data Map View

Prioritizing CCTV Work Cost Effective, Risk Based Assessment

Challenges Which Segments to CCTV Next? Bidding Out the CCTV Work (spec language, data formats, point repairs)

Solutions Develop Risk Profile o Determine Likelihood of Failure (LoF) Criteria o Determine Consequence of Failure (CoF) Criteria o Use CCTV History o Reliability Analysis Life Expectancy Failure Condition

Likelihood of Failure Based on Pipe Attributes Environmental Conditions o Soil type o Land use History o Tasks o Incidents

LoF Evaluation Determine a Correlation Between Categories and Failure o Identifies if they should be used and how to score Pipe Attribute SSO Risk = (Pipe Attribute Spill Count / System Spill Count) (Pipe Attribute Count / System Count)

Attribute SSO/Stoppage Risk Attribute SSO/Stoppage Risk 1.4 ABS ACP BRI CI CIP CP CPL DIP HDPE PE PVC PVL RCP VCP 1.2 LoF Attributes Evaluated Cleaning Frequency Age Diameter Material Asset Type Slope Groundwater Table Location (with respect to pipe) Pipe Depth Easement Type Restaurant Proximity 1 0.8 0.6 0.4 0.2 0 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 0"-5" 6" 7"-10" 12"-21" 23"-45" >45" Pipe Attribute SSO Risk Pipe Attribute Stoppage Risk Pipe Attribute Stoppage&SSO Risk Average Risk Diameter Pipe Attribute SSO Risk Pipe Attribute Stoppage Risk Pipe Attribute Stoppage&SSO Risk Average Risk Pipe Material

Consequence of Failure Physical Attributes o Diameter o Flow Critical Facilities Health Impacts Regulatory Political

Creeks (200 ft) CoF Evaluation CoF Criteria Identified by: o Staff o Available Data o CD Requirements Several Different Combinations Evaluated for Risk Profile Schools (200 ft) Hospitals Railroad (intersect) Right-of-Way Storm Drain (200 ft) Parks (200 ft) Diameter Length Capacity Land Use Major Roads

Risk Profile Use LoF and CoF Criteria to Generate Risk Profile

Risk Profile Comparison Combine Different Parameters, Risk Distributions and Risk Weights

Risk Profile Comparisons Created 4 Different Combinations of LoF and CoF Focused on SSO Likelihood Consequence Looked at Combinations of Health and CD Components

Future CCTV (Mi) Complete/Planned CCTV (Mi) LOF Install Date COF Creeks (200') 450 400 350 70 60 Diameter Schools (200') 300 50 Material Hospitals 250 40 Slope Railroad (Intersect) 200 30 Depth Right of Way 150 100 20 Storm Drain (200') 50 10 Parks (200') 0 0 Roadways Diameter/Length/Capacity Normalized Risk FUTURE CCTV CCTV COMPLETE PLANNED

150-200 200-250 250-300 300-350 350-400 400-450 450-500 500-550 550-600 600-650 650-700 700-750 750-800 800-850 850-900 900-950 950-1000 Future CCTV (Mi) Complete/Planned CCTV (Mi) Future CCTV (Mi) Complete/Planned CCTV (Mi) 450 80 600 70 400 70 500 60 350 60 50 300 400 50 250 40 40 300 200 30 30 150 200 100 20 20 50 10 100 10 0 0 0 0 Normalized Risk FUTURE CCTV CCTV COMPLETE PLANNED Normalized Risk FUTURE CCTV CCTV COMPLETE PLANNED

50-100 100-150 150-200 200-250 250-300 300-350 350-400 400-450 450-500 500-550 550-600 600-650 650-700 700-750 750-800 800-850 850-900 900-950 950-1000 Future CCTV (Mi) Complete/Planned CCTV (Mi) 900 90 LoF CoF 800 80 Diameter Creek (200') 700 600 70 60 Age Storm Drain (200') 500 400 50 40 Material Population Density 300 200 30 20 100 10 Asset Type 0 0 Cleaning Frequency Normalized Risk FUTURE CCTV CCTV COMPLETE PLANNED

Repair, Rehabilitation or Replacement? Making Consistent, Defensible Decisions

Challenges o No Overall Condition Based Rehab Plan o No Methodical Decision Tool Used Expert Method o Creating the Decision Trees Repair Methods Used Decision Points Defect Lengths Determination Is Our Decision Model Reflective of Reality?

Solutions Create Standards o Data Collection and Defect Coding o Defect Repair Methods o Acceptable Number of Defects/Pipe o At what point do we replace?

Defect Repair Methods Which discrete defects are fixed and how?

Rehabilitation Methods How are pipeline repairs determined?

Cost Tables

Typical Decisions Hydraulic capacity OK? Pipe smaller than current standards? Length of continuous defects? Number of defects per 100 feet? Part of an existing project? Maintenance costs versus capital costs? Defects that increase risk of SSO?

Development Approach Started with 3 Existing Decisions o Reviewed agency characteristics and goals System age and size R&R goals Processed Existing 322 Miles of San Jose CCTV

Review of Results Yields of Miles of Construction from 322 CCTV Miles Yields and Costs Used for Forecasting Agency Yield Cost (millions) A 31% $85 B 10% $35 C 38% $70

Developing San Jose s Model What is Currently Being Used? Are There Any Decisions from Previous Models that are Applicable to San Jose? What Should Our Yield Be? o What codes are driving decisions?

Major Issues to Address Data MWLS Codes o Are they truly sags? What to Do with 6 Pipe

Results Yield from initial 322 miles of San Jose CCTV: Approximately 32% construction yield 42.4 Miles of Rehab» Allows 6 pipe to be lined 56.5 Miles of Repair 0.6 Miles of Replacement 3.6 Miles of Evaluate Sags Emphasis away from replacement Approximately $40 Million in Backlogged Projects

Forecasting and Budget Short Term and Long Term CIP

Challenges Now That We Have Information What s Next? Has some already been built? o How do we reconcile? How Do We Forecast Future CIP o Is 32% a realistic yield? From Budgeting to Project Delivery, How Will InfoMaster be Used? o Impacts to budget o Planning window 5 or 10 years CD impacts

Estimated Cost Model 2 Cost Forecast at 5% Yield Decrease Per Year $45,000,000 $40,000,000 $38,400,737 $35,000,000 $30,000,000 $25,000,000 $20,000,000 Initial Cost Forecast Cost $15,000,000 $10,000,000 $5,000,000 $- 0 1 2 3 4 5 6 7 8 9 10 Year Forecasting Estimating Future Yield and Cost

Statistical Sample Set Sanitary Sewer Condition Assessment (SSCA) Pilot o Randomly selected ~50 miles of pipe to CCTV o Identified to determine approximate condition of entire system o Based on statistical sample of: Material Diameter Age Results of San Jose Model o 10% Construction Yield

Lessons Learned Issues, The Future, and Questions

Lessons Learned - Software Data Compatibility o SDE vs GDB Numeric vs Text Defect Length and Count of Defects o PACP vs Count o Continuous Defects CapPlan Limitations Asset Based vs Project Approach

Project Status Where are we in implementation? Completed Model Validated Decision Process o Compared to previous projects Begin Rollout o Setup on City servers o Data mapping o Staff training

Questions?

Cost CIP 10 Year Cost Forecast $50,000,000 $45,000,000 $40,000,000 $35,000,000 $30,000,000 $25,000,000 $20,000,000 $15,000,000 $10,000,000 $5,000,000 $- 0 1 2 3 4 5 6 7 8 9 10 Initial Cost $47,308,210 Forecast Cost $14,563,747 $9,970,632 $6,811,930 $4,653,571 $3,165,471 $2,171,385 $1,480,737 $1,018,555 $675,107 $447,983 Statistical Sample Set Forecast with SSCA Yield Percentage

$50,000,000 $45,000,000 $40,000,000 $35,000,000 $30,000,000 $25,000,000 $20,000,000 $15,000,000 $10,000,000 $5,000,000 $- 0 1 2 3 4 5 6 7 8 9 10 Straight-line Yield