ArcGIS REST Services Directory Login | Get Token
JSON

Layer: Road flooding 2055 (ID: 4)

Name: Road flooding 2055

Display Field: TOWN

Type: Feature Layer

Geometry Type: esriGeometryPolyline

Description: A variety of factors affect a tidal marsh’s fate including its elevation relative to the tides, frequency of inundation, salinity of tidal flood waters, amount of vegetation on the marsh surface, land subsidence, marsh substrate, and the settling rate of suspended sediment on the marsh surface. Therefore, a simple comparison of current marsh elevations to future projections of sea level does not adequately predict wetland vulnerability to accelerated rates of sea level rise. SLAMM considers many of these factors and is widely used to predict the response of marshes, and other intertidal resources, such as beaches, to predicted rates of SLR. SLAMM is not a hydrodynamic model, but rather a two-dimensional model in which long term shoreline and habitat class changes are predicted as a function of land elevation, tide range, and sea level rise. A fundamental assumption in SLAMM is that individual wetland types inhabit a range of vertical elevation that is a function of local tide range. The model computes relative sea level rise for each area subject to analysis at different time steps that is offset by both observed and modeled marsh accretion and other factors affecting marsh surface elevation. When the model is applied, each study site is divided into cells of equal area (5x5 meters square for these simulations) that are treated individually. The conversion from one land cover class (e.g., irregularly flooded, or high marsh) to another (e.g.,regularly flooded, or low marsh) is determined by comparing the new tidal water elevation and inundation frequency in a cell resulting from SLR at a given time-step to the existing land cover class in that cell. In general, when a cell is connected to open tidal water and its elevation falls below the minimum elevation for its current land-cover class, then SLAMM converts the cell’s land cover to a new class according to a decision tree and land-coverconversion rules. These data are projections from SLAMM simulations using input from the State of New York's 2014 SLR planning effort. These scenarios were reviewed and determined to be the most current and relevant avaialble, and thus applied to the coast of CT for time-steps of: 2010 (initial conditions), 2025, 2040, 2055, 2070, 2085 and 2100. Each time step provides land-cover change results for the following SLR scenarios: NYC LowNYC Low MediumNYC Medium NYC High MediumNYC HIghFor information on theses SLR estimates, see https://www.nyserda.ny.gov/climaid.Recently SLAMM has been updated to include infrastructure analyses. The new infrastructure code allows for the input of multiple shapefiles representing the locations of critical infrastructure. Road input is required to be a line shapefile which is then segmented by SLAMM to characterize inundation frequnecy on a scales consistent with the resolution used for SLAMM output (here, ~5 m.) Inundation frequency for five elevations above Mean Tide Level (MTL) can be modeled for various SLR scenarios. In the current model application these inundation frequency elevations are the 30-day inundation height, the 60-day inundation height, the 90-day inundation height, the 10-year storm surge height, and the 100-year storm surge height. SLAMM outputs inundation results as GIS attributes associated with each feature.

Copyright Text: Warren Pinnacle Consulting, Inc (WPC); Northeast Regional Ocean Council (NROC); Connecticut Dept of Energy & Environmental Protection (CT DEEP)

Default Visibility: false

MaxRecordCount: 1000

Supported Query Formats: JSON, geoJSON

Min Scale: 100000

Max Scale: 0

Supports Advanced Queries: true

Supports Statistics: true

Has Labels: false

Can Modify Layer: false

Can Scale Symbols: false

Use Standardized Queries: true

Supports Datum Transformation: true

Extent:
Drawing Info: Advanced Query Capabilities:
HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeAsHTMLText

Type ID Field: null

Fields:
Supported Operations:   Query   Query Attachments   Generate Renderer   Return Updates

  Iteminfo   Thumbnail   Metadata