From One to Many Evolving the models and products to meet the needs at PSRC 2014 COG/MPO Mini-Conference on Socioeconomic Modeling July 18, 2014

2 Outline In the beginning… Life was simple New Demands from Modeling Growth Management Planning Parcel focus Activity Based Models Expanded Products Modeling emerging policy directions Recasting the Model & Products Swiss Army Knife

Central Puget Sound Region Area: 6,300 mi² 16,300 km² (16% urban) As of 2011: Population 3,715,650 Jobs 1,853,900 Largest City Seattle – 612,000 Smallest City Index Counties 82 Municipalities

4 In the Beginning Top-down, two-model structure Regional Forecasts Zonal allocation “Small Area Forecasts” – mix of Modeled output Reviewer comments Interpretations of policies Assumptions of future plans and projects New Demands from Modeling Growth Management Act in 1990 Focus on land use plans and policies Explicit representation of comp plans and Urban Growth boundaries needed Support AB Modeling

55 PSRC Modeling Suite – circa Travel Forecasts – PSRC Travel Demand Models Benefit-Cost Analysis Tool Transport System - GeoDatabase Air Quality Analysis – EPA MOVES Land Use Model - UrbanSim Land Development Models Household Location Models Employment Location Models Workplace Location Models Regional Economic Forecasts – ECO Model US Forecast (Exogenous Input) Regional Forecast Model

Modeling emerging policy 6 Original concept = compare Forecast to emerging policy, a “Gap Analysis”

Forecast Products Package Two new future land use datasets: 1.Land Use Forecast  New land use forecast developed using PSRC’s UrbanSim model 2.Local Targets Representation  Companion future land use dataset based on local growth targets developed to align with VISION 2040’s Regional Growth Strategy Additional resources: 3.VISION 2040 Gap Analysis  Comparison of Land Use Forecast and V2040 Regional Growth Strategy 4.Planning Guidance & Technical Assistance 7

8 Three Months Later – Renaming….

9 … there’s still a void Product for travel modeling, other planning uses Consistent with VISION 2040 (Regional Growth Strategy) Updated to reflect the 2012 Regional Economic Forecast Years: Horizon of 2040 with interim years available Consistency with locally adopted Growth Targets

10 A Third Product Land Use BaselineLand Use TargetsLand Use Vision What It Represents: The region’s predicted development pattern based on current pre-VISION 2040 local comprehensive plans and development regulations (circa 2012) A future land use and development scenario based on county/local growth targets developed to align with the VISION 2040 Regional Growth Strategy Future land use scenario consistent with the VISION 2040 Regional Growth Strategy, updated by the 2012 Regional Economic Forecast, and informed by local targets Model:UrbanSimAllocation Method Regional Forecast Assumption: 2012 Regional Economic Forecast 2005 Puget Sound Economic Forecast/ 2006 Small Area Forecast 2012 Regional Economic Forecast Data Variables: - Total population - Group quarter population (by institutional/non-institutional) - Household population - Households (by income quartile) - Employment (by major sectors) Geography:FAZ, CT, city/uninc’d urban/rural Base Year: Interim Years: Decadal through 2040None5-year intervals Horizon Years: , 2030, 2031 &

Forward: Recasting the Platform UrbanSim as the Swiss Army Knife (DRAFT) Simulation Mode Allocation Mode Baseline Projections Scenario Analysis Sub-Regional Control Totals Output Refinements

12 Redefining the Products Product concept (DRAFT – still to be vetted) Simulation Mode Allocation Mode Baseline Projections Scenario Analysis Sub-Regional Control Totals Output Refinements Control run – aka “do nothing” alternative No post-processing, “it is what it is” Inform thru comparisons to Control run Output achieved thru policy & plan levers Post-process to predefined totals Synthesize for travel model Generate policy-based distributions Replace decision-rule allocation models

13 Stress Test Concept: Goal:Be in position this fall to demonstrate UrbanSim’s ability to support scenario analysis work Reasoning:Land Use Baseline was the result of one set of assumptions (basically, the status quo) It did not leverage the strengths of building a complex model with many “levers” that could be used to test policy outcomes. We would like to test those levers to see how the model behaves – to build confidence in and support for the tool.

14 Stress Test Approach: Borrowing from ABAG’s approach in the Bay Area: Define & design Policy Levers Groupings of levers ultimately used to define tests Multi-round testing: Initial Levers on extreme settings Analysis of what worked, what needs work Inform parallel model improvement work

15 Learned Lessons and Future Direction Staffing Economic expertise Inner-agency consortium (policy, modeling, outreach) Establish credibility prior to scenario analysis Outreach, internal & external Stress testing and model improvement Expectations Review process Re-assess = inputs instead of outputs? Break w tradition Time & labor intensive – learning curve, Q&A, implementation of changes Alternative inputs consensus Straightforward to create scenario inputs, but are parcel-level assumptions about future land use plans acceptable?

16 The review process – Draft Release March 2012 Workshop & documentation to explain basic UrbanSim workings & how to comment Focus on input correction & model improvements o Web mapping tool for reviewers

17 The review process – Revised Draft December 2012 Focus on both inputs & outputs Begin implementing output Refinements - two ‘types’ Year 2010 Refinement – attempt to correct for validation error Forecast Refinement – adjust output in response to comments Both processes – Zone adjustments, maintained regional forecast totals. Use of Confidence Intervals for adjustment guidance

Forecast Products Package / Land Use Modeling Staff Billy Charlton Carol Naito Rebeccah Maskin Mark Simonson Hana Sevcikova Peter Caballero Michael Jensen