SAWPA OWOW 2.0 Project Ranking Process
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Transcript of SAWPA OWOW 2.0 Project Ranking Process
SAWPA OWOW 2.0 PROJECT RANKING PROCESS
December 6, 2012
Multi-Step Project Ranking Process
1. OWOW Steering Committee developed five criteria and weights and eight performance measures Criteria equally weighted at 20% each (each criteria can
contribute a maximum of 20% of the overall project score)
2. Project applicants submitted data to SAWPA
3. Project data initially reviewed for data entry errors by SAWPA
4. Scales developed and data normalized for each criteria
5. Data entered into Criterium Decision Plus (CDP) software and scored for each project
6. Results sorted into three tiers
Criterium Decision Plus Software
CDP software developed by InfoHarvest utilized to develop initial project tiers
CDP uses a multi-attribute rating techniqueo Methodology involves
1) Defining the evaluation criteria for comparison between alternatives
2) Developing performance measures indicating when a criterion is achieved
3) Determining the relative weight of importance that each criterion has in terms of influencing the decision
Criteria 1 – Improve Water Reliability and Reduce Reliance on Imported Water
1. AFY yields summed for each project: Water use efficiency Stormwater capture and storage Recycled water reuse Groundwater desalination Other
2. Multiplied maximum AFY by 110% - maximum bookendExample: Maximum summed AFY = 100
Maximum scale = 110 (100 x 110%)
3. Minimum scale set to 0
4. Projects with higher values receive higher scores for Criteria 1
5. Resultant values entered into CDP
Criteria 2 – Improve Water Quality and Salt Balance in the Watershed
1. Three categories of data contribute to criteria score: Non-point source reduction (mgd) Reduction of TMDLs and other pollutants (kg/year) Salt removal (tons/year)
2. Data normalized on scale of 1 to 5 for each category 1 = worst 5 = best Data for each category with a value greater than 0 was divided
into quartiles to facilitate developing ranges for the scale
3. Normalized data summed together by project across the three categories
Criteria 2 – Continued
4. Summed data adjusted by subtracting 2 to ensure projects with values of 1 in each category receive an overall value of 1, resultant values entered into CDP
5. Summed values greater than 5 capped at 5Example:
Normalized Values
Criteria ScoreSalt Removal
Nonpoint Source TMDL & Other Sum
Project 1 1 1 1 3 1
Project 2 1 3 2 6 4
Project 3 5 5 5 15 5
Criteria 3 – Manage Flood Waters Through Preservation and Restoration of Natural Hydrology
1. Three performance measures with varying weights: 3a - Acres of habitat created (acres), weight 60% 3b - Natural hydrology restoration and connectivity, weight 20% 3c - LID or resource efficient land use practices, weight 20%
2. 3a assigned weight of 60% as provides greatest benefit to criteria
3. When a criteria has multiple performance measures resultant data for each performance measure is entered into CDP
Criteria 3 – Performance Measure 3a
1. Acres of habitat performance measure – developed using same methodology as Criteria 1
2. Maximum bookend = 110% of maximum data value
3. Minimum bookend = 0
Criteria 3 – Performance Measures 3b and 3c
1. Data for performance measures 3b and 3c consists of yes/no answers to whether the project provides the applicable benefit and a description of the benefit 1 = answer provided was no and no explanation 2 = answer provided was yes and no explanation or explanation
not applicable 5 = answer provided was yes and logical explanation provided
2. Scale of 1 to 5 used 1 = worst 5 = best
Criteria 4 – Reduce Greenhouse Gas Emissions from Water Management Activities
1. Data normalized on scale of 1 to 5 for greenhouse emissions (co2e metric tons) 1 = worst 5 = best Data > 10,000 co2e metric tons assigned a score of 5 Data with a value greater than 0 and less than 10,000 co2e metric
tons was divided into quartiles to facilitate developing ranges for the scale
2. Normalized data entered into CDP
Criteria 5 – Cost Effectiveness
1. Criteria is composed of five components evaluating the cost effectiveness on a per unit basis per year for each benefit claimed: 5a - Cost per AFY of water 5b - Cost per acre of habitat 5c - Cost per tons of salt removed 5d - Cost per mgd of water treated 5e – Cost per kg of TMDL or other pollutants removed
2. Data normalized on scale of 1 to 5 for each component 1 = worst 5 = best Data for each component with a value greater than 0 was
divided into quartiles to facilitate developing ranges for the scale
Data for a component with a value of 0 received a score of 1
Criteria 5 – Continued
3. Normalized values for each component summed together and divided by 5 to arrive at cost effectiveness score
4. Data entered into CDP
Normalized Values
Criteria Score
Cost per AFY of Water
Cost per Acre of habitat
Cost per Ton of Salt Removed
Cost per MGD of Water
Treated
Cost per kg of TMDL or
Other Pollutant Removal Sum
Project 1 1 1 1 1 1 5 1
Project 2 4 3 3 5 4 19 4.75
Project 3 5 5 5 5 5 25 5
Results
Tiers developed using natural breaks in resultant project scores from CDPo Tier 1 - Projects closely matching the OWOW project criteria
100% match to 22% match of the OWOW project criteria 33 projects
o Tier 2 - Projects that match OWOW project criteria in some respects, but have deficiencies in areas
21% match to a 5% match of the OWOW project criteria 54 projects
o Tier 3 – Projects that provide lesser benefits than projects in Tier 1 or Tier 2 or projects earlier in development phase
or benefits cannot be determined at this time 4% to 0% match of the OWOW project criteria 49 projects
Results - Continued
Example on following slide illustrates overall contribution of each criteria for three hypothetical projects and provides a total score for each project based on output from CDPo Maximum score is 1 (100%) overall and 20% for each criteria
Results – Continued