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The SLAMM Model (Sea Level Affecting Marshes Model ). Jonathan Clough. 3-18-2014. Warren Pinnacle Consulting, Inc. Founded in 2001 Located in Central VT, Environmental Modeling Experts Jonathan S. Clough, Founder, Environmental Consultant since 1994

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The slamm model sea level affecting marshes model

The SLAMM Model(Sea Level Affecting Marshes Model)

Jonathan Clough


The slamm model sea level affecting marshes model

Warren Pinnacle Consulting, Inc. Founded in 2001

Located in Central VT, Environmental Modeling Experts

Jonathan S. Clough, Founder, Environmental Consultant since 1994

Dr. Amy Polaczyk, SLAMM modeler, with us since 2010

Dr. Marco Propato, Accretion modeling expert, joined in 2011

Slamm sea level affecting marshes model
SLAMMSea Level Affecting Marshes Model

  • Simulates the dominant processes involved in wetland conversions under different scenarios of sea level rise

    • inundation, erosion, accretion, soil saturation and barrier island overwash

  • Uses a complex decision tree incorporating geometric and qualitative relationships to represent transfers among coastal classes

  • Can provide numerical and map-based output with minimal computational time


2100, 1 m SLR


“Uncertainty Cloud” for Selected Region

  • Modest data requirements allowapplication to many sites at a reasonable cost

  • Integrated stochastic uncertainty and parameter sensitivity analyses

    • Provides a range of possible outcomes and their likelihood

  • Users have included US EPA, USGS, The Nature Conservancy, National Wildlife Federation, and the U.S. Fish & Wildlife Service, among others

    • Calibrated to historic SLR in Louisiana

    • The model has been applied to more than 100 National Wildlife Refuges in the US

  • The Range Between 5th and 95th percentiles is graphed along with mean and deterministic results

    Model development overview
    Model Development Overview

    Intermittently under development since 1985, Park & Titus

    Three Year EPA STAR grant (2005-2008) provided funds for significant model development.

    Simulations of entire Georgia and South Carolina Coastline

    Model assumptions closely re-examined by team of scientists

    Survey of recent literature

    Model tested using LIDAR data

    Model results linked to ecosystem services

    National Wildlife Federation Funded Simulations

    Florida, Puget Sound, Chesapeake Bay, Louisiana (Glick et al, 2013)

    USFWS funding of refuge simulations

    Over 100 refuges completed to date in USFWS Regions 4,5,8

    TNC / GOMA funding of Gulf of Mexico Simulations

    Latest version slamm 6 2
    Latest Version SLAMM 6.2

    64-bit (parallel processing in-house)

    Dynamic Accretion

    Open Source

    Elevation Analyses with histograms

    Increased Flexibility in Parameterization.

    Upgrade of Salinity Component (Bathymetry)

    Users Manual & Technical Documentation Update

    Coming soon slamm 6 3 and 6 4
    Coming Soon – SLAMM 6.3 and 6.4

    • SLAMM 6.3 – USGS Sponsored

      • Salinity linkages

      • SAV model

    • SLAMM 6.4 – USFWS Sponsored

      • Roads and Infrastructure module

    Ongoing work on slamm model
    Ongoing Work on SLAMM Model

    • Gulf Coast Prairie LCC

      • “Gap Analysis:” filling in all holes in the Gulf of Mexico

    • NY State – Application to Long Island, NY City, Hudson River

      • Examine the effects of DEM processing and “hydro enforcement”

      • All CT coasts

    • USGS:OR – SLAMM 6.3. Linkages created to EPA salinity models. SAV predictions

      • Habitat switching based on salinity, model testing and documentation

    • Ducks Unlimited – Pacific Northwest

      • Application of uncertainty analysis in WA & OR, evaluating land parcels for restoration

    • TNC TX – Examine effects on infrastructure given development and restoration scenarios

      • Dike model refined to assess likelihood of overtopping

      • Alternative green/grey infrastructure design.

    Model process overview
    Model Process Overview

    Addresses Six Primary Processes (Inundation, Erosion, Saturation, Overwash, Accretion, Salinity)

    Titus and Wang 2008

    Model process overview1
    Model Process Overview

    • Inundation:Calculated based on the minimum elevation and slope of the cell.

    • Erosion:Triggered given a maximum fetch threshold and proximity of the marsh to estuarine water or open ocean.

    • Accretion:Vertical rise of marsh due to buildup of organic and inorganic matter on the marsh surface. Rate differs by marsh-type.

    • Salinity: Optional model or linkage to existing model. Salinity affects habitat switching in areas with significant freshwater flows

    • Overwash:Barrier islands undergo overwash at a fixed storm interval. Beach migration and transport of sediments are calculated.

    • Saturation:Migration of coastal swamps and fresh marshes onto adjacent uplands-- response of the water table to rising sea level.

    Conceptual model
    Conceptual Model

    • Square “raster” cells with elevation, slope, aspect, estimated salinity, wetland type

      • Cells may contain multiple land-types

      • Cell size flexible given size of study area

    Dry Land

    Various Wetlands

    Open Water

    2D Representation 3D Representation

    Slamm inundation model
    SLAMM Inundation Model

    Equilibrium Approach


    Land Elevation

    Salt Elev.

    (30 day inundation)

    Salt Boundary




    Regularly- Flooded Marsh (Often Salt Marsh)

    Inland Fresh and Dry Land

    Tidal Flat

    Transitional or Irregularly- Flooded Marsh

    Distance Inland

    Slamm inundation model migration of wetlands boundaries due to sea level rise
    SLAMM Inundation Model(Migration of Wetlands Boundaries due to Sea Level Rise)


    Old Land Elevation

    New Land Elevation

    Salt Elev.

    (30 day inundation)

    Salt Boundary




    Tidal Flat

    Regularly- Flooded Marsh (Often Salt Marsh)

    Inland Fresh and Dry Land

    Irregularly- Flooded Marsh


    Distance Inland

    The slamm model sea level affecting marshes model

    Feedbacks to Accretion

    • SLAMM 6 Allows for Elevation Feedbacks to Accretion as shown by Morris et al. (2002)

    • Linkage to Morris MEM model

    “Unstable Zone”

    High-elevation marsh subject to less flooding

    The slamm model sea level affecting marshes model

    Linkage to Marsh Equilibrium Model

    • Explicitly accounts for physical and biological processes affecting marsh accretion

    Detailed slamm land categories
    Detailed SLAMM Land Categories

    • 26Categories, often derived from NWI (National Wetlands Inventory)

    • May be specified as “protected by dikes or seawalls”

    Dry Land:Developed and Undeveloped

    Swamp:General, Cypress, & Tidal

    Transitional Marsh:Occasionally Inundated, Scrub Shrub

    Marsh:Salt, Brackish, Tidal Fresh, Inland Fresh, Tall Spartina

    Mangrove:Tropical Settings Only

    Beach:Estuarine, Marine, Rocky Intertidal

    Flats:Tidal Flats & Ocean Flats

    Open Water:Ocean, Inland, Riverine, Estuarine, Tidal Creek

    Sea level rise scenarios
    Sea Level Rise Scenarios

    • Model incorporates IPCC Projections as well as fixed rates of SLR

    • Global (Eustatic)Rates of SLR are correctedfor local effects using long-term tide gauge trendsor spatial subsidence

    Grinsted, 2009Clim. Dyn.

    Vermeer and Rahmstorf, 2009, Proceedings of the National Academy of Sciences

    The slamm model sea level affecting marshes model

    Powerful SLAMM Interface – Main Interface

    (Illustrates 3-D Graphing Capabilities)

    Connectivity component
    Connectivity Component

    • Method of Poulter & Halpin 2007

    • Assesses whether land barriers or roads prevent saline inundation

    • Can be used for levee overtop model with fine-scale DEM

    Built in sensitivity analyses
    Built-in Sensitivity Analyses

    • Marshes most sensitive to accretion rates

    • Beaches and Tidal flats most sensitive to parameters that affect SLR rates, tide ranges, and initial condition elevations

    • Dry land most sensitive to SLR rates.

    The slamm model sea level affecting marshes model

    Uncertainty Module Addresses Two Primary Criticisms

    • Accretion Model

      • Doesn’t account for feedbacks (not true in SLAMM 6)

      • Manner in which feedbacks are accounted for is uncertain

    • Lack of uncertainty evaluation

      • How confident are you of the results?

      • Interpretation of deterministic results difficult

      • What to do if available input parameters are not very good?

      • Decision making difficult since likelihood and outcome variability are unknown

    Model output distributions

    Parametric Model Input Distributions

    Model Output Distributions

    “Uncertainty Cloud” for Selected Region

    • Examining SLAMM results as distributions can improve the decision making process

      • Results account for parametric uncertainties

      • Range of possible outcomes and their likelihood

      • Robustness of deterministic results may be evaluated

    Dike considerations
    Dike Considerations

    • Traditional SLAMM has “on-off” dike layer

      • Option to model dike elevations is included

    • New: Dike elevations may be input at fine scale

      • Connectivity can be used to calculate dike overtop

    • Dike Removal

      • Dynamic accretion processes following dike removal are not represented

    Hindcasting capability
    Hindcasting” Capability

    • Run the model with historical data for validation and calibration

    • Results will be imperfect

      • Historical elevation data with high vertical resolution unavailable

      • Historical land-cover data are spotty and changes in NWI classification have occurred

      • Model will not predict land-use changes, beach nourishment or shoreline armoring

    • For many sites, hindcasting is not possible due to insignificant RSLR “signal”

    • In GOM, land subsidence amplifies SLR signal enough to make hindcasting possible

    Slamm infrastructure module
    SLAMM Infrastructure Module

    • Grant funded by US Fish and Wildlife Service

    • Integrates predicted SLR and tide-ranges with roads and infrastructure databases

    • Predicts effects on infrastructure

    • Better captures infrastructure effects on surrounding wetlands

    2075 under 1m by 2100
    2075 under 1M by 2100

    Slamm erosion model
    SLAMM Erosion Model

    • Erosion assumed a function of wave action

    • Maximum Fetch calculated at each cell based on previous land-changes.

    • When threshold of 9km is exceeded horizontal erosion rates are implemented.

      • 9 km threshold based on visual inspection of maps

      • Value verified within literature (Knutson et al., 1981)

    • Tidal Flats have different assumptions

    Overwash assumptions
    Overwash Assumptions

    • Barrier islands of under 500 meter width are identified and assumed to be affected

    • Frequency of “large storms” is user input

    • Assumed effects are professional judgment based on observations of existing overwash areas (Leatherman and Zaremba, 1986).

    • Effects editable in SLAMM 6

    Soil saturation
    Soil Saturation

    • SLAMM estimates (fresh) water table from the elevation nearby swamps or fresh-water wetlands

    • As sea levels rise, this applies pressure to fresh water table (within 4km of open salt water)

    • Model results could include “streaking” as a result of soil saturation predictions.

    Water Table Rise Near Shore, Based on Carter et al., 1973

    Slamm salinity model
    SLAMM Salinity Model

    • Required as marsh-type is more highly correlated to salinity than elevation when fresh-water flow is significant (Higinbotham et. al, 2004)

    • Simple steady-state salinity model; not hydrodynamic

    • Adds complexity to model development

    • Requires additional model specifications

      • Estuary Geometry

      • Freshwater flow and projections

    • Linkages to external salinity models are already built in to SLAMM 6.3

    Slamm 5 salinity component
    SLAMM 5 Salinity Component

    (For cells defined as “in-estuary”)

    Salinity calculated as a function of estuary width,

    tide range, fresh-water flows, and bathymetry


    FWH, fn of River Discharge

    Fresh Water

    Tide Range + SLR

    Salt Water


    Tidal Fresh

    Tidal Swamp


    Estuary Area, Moving Inland

    salinity decreasing, but not linearly

    Salinity calibration
    Salinity Calibration

    • Successfully calibrated to 5 GA estuaries

    • Good match of salinity to river mile vs LMER data

    • Publication pending

    • Spatially calibrated to salinity data in Port Susan Bay, WA

    Next steps in model development
    Next Steps in Model Development

    • Make “flow-chart” of habitat switching and land-categories modeled completely flexible (international applications)

    • Linkage to hydrodynamic, sediment transport models

    • More salinity testing

    • Wider testing of SAV module

    • Model evaluation and refinement – erosion, overwash, soil saturation

    • Seeking collaborative partners

    Galveston bay
    Galveston Bay

    • Hindcast and Initial Forecast Results

    • Meeting with Stakeholders in TX

    • Incorporation of & Response to Stakeholder Comments

    • Final results available at GOMA and SLAMMView website


    Complicating factor subsidence
    Complicating Factor: Subsidence

    • Spatial maps used in hindcasting

    • Used to convert eustatic to local SLR

    • Held constant over simulation

    Gabrysch and Coplin 1990

    The slamm model sea level affecting marshes model



    The slamm model sea level affecting marshes model





    2100 scenario a1b mean
    2100, Scenario A1B Mean

    Slamm strengths
    SLAMM Strengths

    • Open source

    • Relatively simple model

    • Ease and cost of application

    • Relatively quick to run (enables uncertainty analysis)

    • Contains all major processes pertinent to wetland fate

    • Provides information needed by policymakers

    Strengths cont
    Strengths (cont.)

    • Detail oriented flow chart

    • Relatively minimal data requirements

    • Designed in poor data environment -- has assumptions to work through those conditions.

    • Internal uncertainty & sensitivity analyses

    Slamm model limitations
    SLAMM Model Limitations

    • Not a Hydrodynamic Model

      • Conceptual model captures these sites initial conditions well; future changes in hydrodynamics may not be properly represented.

    • Spatially Simple Erosion Model

      • Could be modified or replaced with more sophisticated model

      • Beach erosion is ephemeral and difficult to quantify anyway

    Model limitations
    Model Limitations

    • No Mass Balance of Solids

      • i.e. accretion rates not affected by bank sloughing

      • Storms do not mobilize sediment

    • Overwash component is subject to considerable uncertainty

      • Timing and size of storms is unknown

      • Based on observations of barrier islands after large storms

    Mcleod poulter et al 2010
    Mcleod, Poulter, et al., 2010

    • Ocean & Coastal Management “SLR impact models and environmental conservation, a review of models and their applications”

    • SLAMM 5 Advantages

      • Can be applied at wide range of scales

      • Provides detailed information about coastal habitats and shift in response to SLR

      • Can be used to identify potential future land-use conflicts

      • Integrates numerous driving variables

      • “Provides useful, high-resolution, insights regarding how SLR may impact coastal habitats.”

    Mcleod poulter et al 20101
    Mcleod, Poulter, et al., 2010

    • SLAMM 5 Disadvantages

      • Lacks feedback mechanisms between hydrodynamic and ecological systems

      • Changes in wave regime from erosion not modeled

        • Note wave setup is recalculated on basis of land loss

      • Lacks feedback between salinity and accretion rates in fresh marshes

        • SLAMM 6 does include feedbacks between frequency of inundation and accretion rates and links to mechanistic modeling.

      • Does not include a socioeconomic component to estimate costs; not useful for adaptation policies

    Considerations and costs of implementation
    Considerations and Costs of Implementation

    • GIS expertise required to produce raster inputs

    • Tidally-coordinated LiDAR elevation data highly beneficial

    • NWI data often out-of-date

      • Alternative data sources have often been used

      • Crosswalk process time consuming

    • Salinity model requires additional support

    • Model QA tests can be time-consuming

    To stay in touch with future model developments
    To Stay In Touch with Future Model Developments

    • SLAMM webpage

      • Includes brief model overview, bibliography

      • Updated with latest projects and results

      • Technical documentation with full model specs

      • Model executable available at this site

      • Model code is “open source” available for review or modification

    • Email me --