Dataset

Tidal Marsh Elevation Models

Commons Hosting
Climate Commons Hosting Status: 
Available
Other Online Access: 

This dataset may be visualized and downloaded at Future San Francisco Bay Tidal Marshes, A Climate Smart Planning Tool

Discussion Forum
Basic Information

Marsh accretion was modeled by ESA PWA using the Marsh-98 model, described here. The model assumes that rates of marsh plain elevation change depend on the availability of suspended sediment and organic material, water depth, and duration of inundation periods. If enough suspended sediment is available, then tidal marsh elevations can keep pace with increased inundation. Model outputs were linearly interpolated in 10-cm increments for starting elevations ranging from -3.7 to 1.7 m (relative to mean higher high water, or MHHW), and applied to a composite 5-m elevation grid (see below) for SF Bay. Results for each possible combination of projected sea level rise, sediment and organic material availability, and target year were combined to produce the scenario layers.

Understanding San Francisco Bay's vulnerabilities to sea level rise is important for both biodiversity conservation and for management of public infrastructure. Coastal marshes provide essential ecosystem services such as water filtration and flood abatement while also providing important habitat for species of conservation concern. Improving our understanding of how tidal marsh habitats will be affected by sea level rise is important so that we maximize ecosystem services that coastal marshes provide and ensure that endemic populations of plants and animals persist into the future. For this project, marsh accretion was modeled by ESA PWA (http://www.pwa-ltd.com/index.html) using the Marsh-98 model, described here: http://escholarship.org/uc/item/8hj3d20t . The model assumes that rates of marsh plain elevation change depend on the availability of suspended sediment and organic material, water depth, and duration of inundation periods. If enough suspended sediment is available, then tidal marsh elevations can keep pace with increased inundation. Model outputs were linearly interpolated in 10-cm increments for starting elevations ranging from -3.7 to 1.7 m (relative to mean higher high water, or MHHW), and applied to a composite 5-m elevation grid (see below) for SF Bay. Results for each possible combination of projected sea level rise, sediment and organic material availability, and target year were combined to produce the scenario layers. See http://data.prbo.org/apps/sfbslr/ for interactive maps and additional details.

This dataset was produced by PRBO Conservation Science's project to assess the effects of sea-level rise (SLR) and salinity changes on San Francisco Bay tidal marsh ecosystems. Tidal marshes are naturally resilient to SLR, in that they can build up elevation through the capture of suspended sediment and deposition of organic material (vegetation). Thus, a "bathtub" model approach is not appropriate for assessing impacts to this dynamic habitat. Rather, dynamic accretion potential can be modeled annually based on tidal inundation, sediment availability, and the rate of organic accumulation (related to salinity). Working with researchers at Philip Williams and Associates (http://www.pwa-ltd.com) University of San Francisco, University of California Berkeley, and San Francisco State University, we have developed a set of geographically based climate change scenarios based on a dynamic marsh accretion model. We have developed preliminary projections for potential changes in tidal marsh elevation and extent over five time frames (20, 40, 60, 80 and 100 years from now) and under eight scenarios representing different assumptions about sea-level rise, salinity, and sediment supply. Our goal is to provide an overview of potential future tidal marsh extent and location in San Francisco Bay, as well as information on priorities for restoration and conservation efforts. Due to the additional complexity of open-bay hydrodynamics, our analysis does not include bay-edge mudflats.

See the following website for additional information http://data.prbo.org/apps/sfbslr/

Supplemental Info
Initial elevation data were developed using the best available data sources. Most of our study area was covered by Light Detection and Ranging (LiDAR) remote sensing data (contributed by USGS). Elevations at locations within the North Bay were field sampled with GPS data to investigate systematic bias in the data. In some areas, errors due to impenetrable mats of vegetation caused erroneously high elevations. Where possible, vegetation data was used to develop correction factors for these errors then applied tothe elevation layer. All datasets were converted to the NAVD88 vertical datum and resampled to a 5 meter resolution. The NAVD88 vertical datum of the elevation data was converted to MHHW reference levels using NOAA tidal gauge and benchmark data. Our models are designed to easily incorporate more accurate elevation data as it becomes available. Rates of sea level rise were based on two non-linear scenarios provided by the US Army Corps of Engineers (2009) from curves provided by the National Research Council to project moderate and high sea level rise over the next century (0.52m and 1.65m). Different input parameter values for sediment supply and organic accumulation were given to 15 geographic sub-regions within the bay to account for the regional variability in these values. Each subregion was assigned a high and low value for sediment supply and organic accumulation based on a combination of USGS monitoring reports, observed accretion rates from restored sites, and expert opinion. For future scenarios, six different suspended sediment concentrations were modeled: 25, 50, 100, 150, 200, 250 and 300 mg/L. Three rates of organic matter accumulation were modeled: 1, 2 and 3 mm/yr, encompassing the presumed range of variability within San Francisco Bay proper (i.e., not the Delta). Projections for the Delta region do not incorporate the much higher rates of organic accumulation there, and should be considered underestimates of marsh sustainability potential. See the following website for additional information http://data.prbo.org/apps/sfbslr/

Creator: 
Point Blue Conservation Science
Subjects:
Spatial Resolution: 
5m
Temporal Coverage: 
2010 - 2110
Date Issued: 
2012
Parameters / Choices
A dataset often contains many geodata layers representing the same kind of measurement, but for different values of some parameters - time periods, models or scenarios, different species, etc. A value must be chosen for each such parameter in order to select a specific layer or raster which associated a single value with each geographic location (cell). The parameters or choices relevant to selecting layers from this dataset are described here.
Time Units: 
20-year time periods
Multi-year Ranges: 
Present (2010), 2030, 2050, 2070, 2090, 2110
File Attachments

Data Variables in this Dataset