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.

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

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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 mi²16,300 km²

(16% urban)

As of 2011: Population 3,715,650

Jobs 1,853,900

Largest City Seattle – 612,000

Smallest City Index - 180

4 Counties

82 Municipalities

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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

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PSRC Modeling Suite – circa 2010-2013

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

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Previous GMA Cycle Current GMA Cycle

CurrentComp Plans

CPPs Targets 2022/2025

OFM Projections

VISION 2040

Updated CPPs

Comp Plansdue 2015/16

Targets 2030-2035

OFM Projections

Land Use Forecast

Local Targets Representation

VISION 2020

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 2030-2035

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

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Three Months Later – Renaming….

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… 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

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A Third Product Land Use Baseline Land Use Targets Land 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: UrbanSim Allocation Method Allocation MethodRegional 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: 2000 2010 2010Interim Years: Decadal through 2040 None 5-year intervals

Horizon Years: 2040 2025, 2030, 2031 & 2035 2040

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2014 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

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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” alternativeNo post-processing, “it is what it is”

Inform thru comparisons to Control runOutput achieved thru policy & plan levers

Post-process to predefined totalsSynthesize for travel model

Generate policy-based distributionsReplace decision-rule allocation models

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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.

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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

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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?

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The review process – Draft Release• March 2012

• Workshop & documentation to explain basic UrbanSim workings & how to comment

• Focus on input correction & model improvementso Web mapping tool for reviewers

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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 CharltonCarol NaitoRebeccah MaskinMark SimonsonHana SevcikovaPeter CaballeroMichael Jensen