Green Infrastructure Modeling

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    Green Infrastructure Modeling

    Andrew Parker

    Water Resources Modeling Group Director

    2010 Regional Water Quality and

    Green Infrastructure ConferenceMay 13-14, 2010

    Dallas, Texas

    Presentation Overview

    Modeling basics

    Models and calculators

    applied to green

    infrastructure

    BMP design

    Site developmentWatershed

    management Applications

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    Input Model Output

    Others

    Factor 1

    Rainfall Event

    Pollutant Buildup

    Land use

    System

    Soil

    Stream

    Pt. Source

    Factor 2

    Factor 3

    Response

    What is a model? A theoretical construct,

    together with assignment of numerical

    values to model parameters,

    incorporating some prior observations

    drawn from field and laboratory data,

    and relating external inputs or forcing

    functions to system variable responses

    * Definition from: Thomann and Mueller, 1987

    What constitutes a model?

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    Why use a model or calculator?

    Applications

    Multiple scales of planning site to watershed

    Other TMDLs, permitting, remediation, design

    Purpose

    Determine stormwater runoff quantity (total and

    peak)

    Determine pollutant load reductions and water

    quality benefits

    Monetize costs and benefits Facilitate design

    Model Categories Landscape models

    Runoff of water and materials on and through the

    land surface

    Receiving water models

    Crops

    Pastu

    re

    Urban

    Flow of water through streams and into lakes and

    estuaries

    Transport, deposition, and transformation in receiving

    waters

    Watershed models Combination of landscape and receiving water

    models

    Site-scale models

    Detailed representation of local processes, for

    example Best Management Practices (BMPs)

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    Model Basis Empirical formulations

    mathematical relationship

    based on observed data

    rather than theoretical

    relationships

    Deterministic models mathematical models

    designed to produce system

    responses or outputs to

    temporal and spatial inputs

    (process-based)

    Model Selection

    Utility

    Ability to answer key management questions and convey results

    Relevance

    Representation of key processes

    Assumptions and limitations

    Scale of application

    Credibility

    Peer-reviewed

    Public domain Usability

    Availability of documentation, training, and support

    Availability and accessibility of data to run model

    Model and user interface is reliable and tested

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    Typical Modeling Process

    (simple models may skip or leave out steps)

    Phase I

    Phase II

    Phase III

    Modeling Approach Development

    Data Collection (historic, field monitoring)

    Model Input Preparation and Configuration

    Calibration

    Validation

    Verification

    Follow-up Monitoring OptionalPost-audit

    Analysis of Alternatives/Scenarios

    Simple Models and Calculators Common Calculation

    Methods

    Runoff Volume

    Runoff Curve Number

    Method (TR-55)

    Small Storm

    Hydrology Method

    Infiltration Models

    Peak Runoff Rate

    NRCS Unit

    Hydrograph Method

    Rational Method

    Pollutant Loading

    Simple Method

    Typical DataNeeds Land use

    Soil types

    Rainfall data

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    More Complicated Models

    Uses

    Can evaluate site scale to watershed scale

    impacts of land use decisions

    More accurately estimate stormwater benefits

    of green infrastructure

    Can be used for single-event or continuous

    simulation

    Limitations

    Data intensive

    Require specific expertise to apply

    Models for Green Infrastructure

    BMP design Properly size and configure practices

    Evaluate effectiveness of BMP after design and construction

    Site development Evaluate effectiveness of multiple practices for

    hydrology and water quality Optimize selection and placement of practices

    Watershed management Analyze watershed-wide implementation

    Program evaluation

    CSO reduction

    TMDL compliance

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    BMP Design RECARGA (University of Wisconsin-

    Madison Bioretention/Rain Gardens)

    Green Save Calculator (Green Roofs)

    CityGreen (Tree Canopy and Green

    Space)

    RECARGAUniversity of Wisconsin-Madison

    MATLAB application Design tool for

    evaluating

    performance of

    bioretention facilities

    and infiltration

    basins

    Model can simulate

    continuous rainfall, a

    single-event, or user

    specified volume

    User inputs

    Rainfall and evaporation file

    Drainage area characteristics

    Layer characteristics

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    GreenSave CalculatorGreen Roofs for Healthy Cities

    Web-enabled tool (registrationrequired)

    Life-cycle costing tool used to

    compare cost of green roof

    with conventional roof

    Option to publish data to Case

    Study database

    Modules with minimum and

    optional detailed data inputs

    Roof durability

    Energy use

    Stormwater

    Heat island

    Development fees

    Sale-ability/rent-ability

    Tenant health and productivity

    CityGreenAmerican Forests

    ArcGIS extension (not free)

    Analyzes ecological and economic

    benefits of tree canopy and other green

    space

    Stormwater Runoff

    Runoff volume for 2-year, 24-

    hour storm

    Based on Runoff Curve

    Number (TR-55)

    Air Pollution Removal

    Pollutant removal capacity of

    tree canopy and financial

    benefit

    Based on US Forest Service air

    pollution model

    Carbon Storage andSequestration

    Amount of carbon stored in

    trees and annual carbon

    removal

    Based on US Forest Service

    model

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    Site Development Green Values Stormwater Management Calculator

    (Center for Neighborhood Technology)

    IncreasedComplexity

    LID Quicksheet (Milwaukee, WI MSD)

    LTHIA (Local Government Environmental Assistance

    Networks Long-Term Hydrologic Impact Assessment

    Model)

    BMP-DSS (Prince Georges County, MDs Best

    Management Practice Decision Support System)

    SUSTAIN (EPAs System for Urban Stormwater

    Treatment and Analysis Integration)

    Green Values StormwaterManagement CalculatorCenter for Neighborhood Technology

    Web-enabled application

    Planning tool with lot and

    neighborhood level

    calculations

    Hydrologic

    Financial

    Evaluates range of green

    infrastructure practices

    Pre-defined or custominputs

    Landscape details

    Cost elements

    Integrated pop-up help

    screens

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    LID QuicksheetMilwaukee Metropolitan Sewerage District

    Excel spreadsheet

    Evaluates various green

    infrastructure features on a

    development site to reduce

    detention requirements

    Can evaluate 2-year and

    100-year, 24 hour storm

    events

    Practices include:

    Rain gardens

    Rain barrels

    Green roofs

    Cisterns

    Permeable pavement

    Long-Term Hydrologic Impact Assessment ModelLocal Government Environmental Assistance Network

    Web-enabled tool

    Quantifies impact of land use change

    on water quantity and quality

    Runoff Curve Number approach

    30 years of precipitation data topredict yearly runoff

    Event Mean Concentrations forpollutant loading estimation

    Provides graphical and tabular runoff

    volumes and associated pollutant

    loads Five versions:

    Basic L-THIA

    Impervious L-THIA

    GIS L-THIA

    Detailed Input L-THIA

    Advanced Input L-THIA

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    BMP-DSSPrince Georges County, MD

    Developed for detailedsite-scale planning andBMP modeling

    Considers hydrology andwater quality

    Models individual BMPsor groups of BMPs (e.g.,at watershed scale)

    Includes post-processingcapabilities

    Watershed Management

    STEPL (EPAs Spreadsheet Tool for

    Estimating Pollutant Load)IncreasedC

    omplexity

    BMP-DSS

    SWMM (EPAs Storm Water Management

    Model)

    SUSTAIN

    Multiple models used collectively

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    STEPL Spreadsheet Model Spreadsheet Tool forEstimating Pollutant Load (STEPL)

    Used at the watershed level for nutrients (nitrogen andphosphorus), sediments, and organic compounds (e.g. biochemical oxygen demand)

    U.S. EPA Office of Wetlands, Oceans, and Watersheds - Nonpoint

    Source Control Branch, Washington, DC

    Automatically customized Microsoft Excel application

    Easy-to-follow graphical interfaces

    Online STEPL input data server

    BMP calculator

    Assisting federal, state, and local organizations in reportingestimated pollutant reductions of 319 projects to the Grants

    Reporting and Tracking System (GRTS)

    SWMM

    Often used toestimate existingloads

    Different BMPscenarios modeled todetermine loadreductions

    Considerations

    Street sweeping Flow detention and

    pollutant removal

    Varying hydrologic

    and pollutant loading

    assumptions

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    Fairfax County, VA

    SWMM Application

    Creating countywide SWMM

    watershed models

    Representing hydrology

    Simulating stormwater BMPs

    Creating prioritization strategy to

    maximize stormwater and

    environmental benefits

    Also linking SWMM to HEC-RASmodels for flood analysis

    Prince Georges County, MD BMP-DSS Application

    Applied to Anacostia Sewershed (Washington, D.C.) to

    support CSO alternative analyses

    Identified potential LID configuration scenarios

    Tested BMP selection

    and placement

    optimization

    Summarized the effectof potential LID

    configurations on runoff

    volume and CSO inflow

    reduction

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    Los Angeles County, CA

    Multiple Models Developing comprehensive

    watershed management decision

    support system Dynamic HSPF/LSPC models for watershed

    hydrology and transport of multiple pollutants Evaluation of storm size and return frequencies

    for identification of management targets Dynamic simulation of BMP processes, including

    both distributed LID and centralized facilities Optimization of the most cost-effective

    combination and designs of BMPs to meetmanagement objectives

    Load reduction quantification to support TMDLimplementation efforts

    Cost estimates for County-wide water qualityimprovement planning

    System forUrban StormwaterTreatment andAnalysis INtegrationSUSTAIN

    U.S. EPA ORD - Edison

    A GIS-based framework designed to support decision-

    making

    Evaluate and select BMPs to achieve loading targets set by a

    TMDL

    Identify protective management practices and evaluate pollutant

    loadings forSource Water Protection

    Develop cost-effective management options for a municipal MS4

    program

    Determine a cost-effective mix of green infrastructure measures to

    help meet optimal flow reduction goals in a CSO control study

    Released in November 09

    http://www.epa.gov/ednnrmrl/models/sustain/index.html

    http://www.epa.gov/ednnrmrl/models/sustain/index.htmlhttp://www.epa.gov/ednnrmrl/models/sustain/index.html
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    BMP criteria GIS data Suitable area for BMP placement

    SUSTAIN Advantages Multi-scale application

    Detailed BMP simulation

    Cost consideration

    Optimization

    Siting Tool

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    Background InfiltrationMedia F iltrationSettlingOrifice OutflowBypass Flow

    Small Medium

    Untreated

    Bypass

    Attenuated

    Orifice Outflow

    Media Filtration

    (Underdrain

    Outflow)

    Large

    100%

    (% Treated)

    50%

    (% Treated)

    10%

    (% Treated)

    Continuous BMP Simulation

    Optimization What is

    optimum?

    Minimize cost

    Maximize pollutant flow and/or load reduction

    Subject to BMP size, selection, and placement constraints

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    55%24%0%21%

    $4.5DRYPOND

    RAINBARREL

    Selected Simulation

    55%24%

    0%

    21%

    BIORETENTION

    POROUSPAVEMENT

    CostDistribution($Million)

    $4.0

    $3.5

    $3.0

    $2.5

    $2.0

    $1.5

    $1.0

    $0.5

    $0.0

    9.9

    %

    14.1

    %

    16.6

    %

    18.4

    %

    20.3

    %

    22.1

    %

    23.4

    %

    24.2

    %

    24.8

    %

    25.7

    %

    26.6

    %

    27.3

    %

    27.9

    %

    28.5

    %

    29.6

    %

    30.2

    %

    30.6

    %

    30.8

    %

    31.1

    %

    31.6

    %

    31.8

    %

    32.1

    %

    32.4

    %

    32.9

    %

    Effectiveness (% Reduction)

    Thank you!

    Contact Information:

    Andrew Parker

    [email protected]

    (703)385-6000

    Optimization