Abstract:

Living shorelines are an environmentally friendly method to reduce shoreline erosion. They increase the ecosystem services of the area, improve the land/sea connectivity, are aesthetically pleasing, and have far fewer maintenance costs than shoreline armoring. Additionally, they can be less costly to install than armoring projects depending upon the exact design parameters. The Living Shoreline Site Suitability Model (LSSSM) is a geospatial model that combines various input parameters to determine which sites are best suited to living shoreline or hybrid stabilization methods and which are not. The Harte Research Institute (HRI) created the LSSSM which provides geospatial information on the suitability of applying living shoreline solutions for erosion control and environmental enhancement along bay shorelines of the Texas coast. This rule-based model uses five factors to consider living shoreline use suitability: bathymetry, exposure to wave energy, type of shoreline, shoreline change rate (erosion rate), and distance to the nearest channel. The model provides four broad categories of living shorelines options to be implemented along the Texas coast. The four categories include Soft Stabilization (marsh grass plantings), Hybrid Stabilization (breakwaters, submerged oyster shell beds, reef balls, articulated blocks or mats, and riprap), Retrofit: Soft Stabilization, and Retrofit: Hybrid Stabilization. This dataset tool can be utilized to determine where a living shoreline may be suitable and to identify the best living shoreline methods to use given the unique conditions at a specific section of the coastline. The data package has two shapefiles – one showing four regions as defined in the Texas Coastal Resiliency Master Plan (TCRMP) and the other showing LSSSM output of shorelines on the Texas coast. The filed name “Output” in the attribute table of the model output shapefile presents the recommended living shoreline type for each shoreline section. If the "Output" field is empty, it means there was not enough data to classify and assign any living shoreline type for that section of shoreline.

Suggested Citation:

Dotson, Marissa, Michelle Culver, and James Gibeaut. 2022. Living Shoreline Site Suitability Model Output for the Texas Coast. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/YQ8MA581

Purpose:

Living shorelines are not one size fits all. In order to build a living shoreline, it needs to be customized to the specific conditions of the shoreline. The Harte Research Institute (HRI) created the Living Shoreline Site Suitability Model (LSSSM) to help determine if any bay shoreline section along the Texas coast is a good candidate for a living shoreline. Therefore, this dataset provides geospatial information on the suitability of applying Living Shoreline (LS) solutions for erosion control and environmental enhancement along the bay shorelines of the Texas coast. In Phase I, HRI compiled geospatial and environmental data to build a rule-based model that classifies bay shorelines as being suitable, unsuitable, or unknown suitability for various types of LS techniques. The specific classes and LS types were determined in collaboration with the Texas General Land Office (GLO) and other partners, including the Galveston Bay Foundation (GBF), which is conducting a similar analysis for Galveston Bay. Phase I focused on developing the process and model using Corpus Christi and Redfish/Aransas Bays as pilot studies. In Phase II, HRI applied the model developed in Phase I to the rest of the Texas coast. Phase II also included creating and implementing an online viewer to help stakeholders determine places where LS techniques are viable (https://gomaportal.tamucc.edu/GLO/LivingShorelines/). HRI has also produced an ArcGIS Story Map to highlight living shoreline examples to accommodate the varying conditions along the coast (https://storymaps.arcgis.com/stories/d6989e741253424584c06ead83078c5d). This dataset allows planners, resource managers, stakeholders, and property owners to find the recommended living shoreline options for any bay shoreline along the coast. It is important to note that this dataset is NOT a substitute for an expert environmental site assessment.

Data Parameters and Units:

Suitability classification [Soft Stabilization, Hybrid Stabilization, Retrofit: Soft Stabilization, and Retrofit: Hybrid Stabilization].

Methods:

Step 1: Input Preparation (Type of Shoreline, Bathymetry, Proximity to Channel): ESI shoreline type is clipped to the study area and classified based on shoreline type (Shoreline = 1 where beach or marsh present; Scarp = 1 where scarp present; Hard = 1 where shoreline is hardened) Bathymetry points from ADCIRC Mesh are clipped to study area, a tin is created (using the shoreline as a hard line and the bay polygon as a soft clip), and then contours are derived Shoreline where the 1m contour is at least 10 m away are deemed shallow (Bathy = 1) Land/water raster for the fetch model is generated (landwater_c) (will use later in USGS Fetch Model) Shoreline segments are classified based on proximity to channels (chan_bord = 1 where channel <=30 m; chan_near = 1 where channel <= 50m) NOTE: channels are not categorized into type Channel type: small channels (< 50m in width) = 1, large channels (> 50m in width) = 2 For small channels – chan_bord = 1 where channel <= 15m away & chan_near = 1 where channel <= 30m For large channels – chan_bord = 1 where channel <= 15m away & chan_near = 1 where channel <= 50m Data used in Step 1: Environmental Sensitivity Index (ESI) shoreline type from HRI; Bathymetry from ADCIRC Mesh developed by USACE; Channel Polygon from HRI; Land-water raster from HRI Step 2: Simplify shoreline features while maintaining attributes. Shoreline features divided into 50 m segments. Data used in Step 2: Environmental Sensitivity Index shoreline type from HRI Step 3: Derive wave exposure index using the USGS Fetch Model: (User guide: https://umesc.usgs.gov/management/dss/wind_fetch_wave/wind_fetch_wave_2012update/wind_wave_2012_update_070814.pdf) Create a text file based on the wind rose data for the study area. Obtain wind speed data from corresponding NOAA buoy for 2007-2017 – calculate the average for each direction (every 22.5 degrees) in knots. Land/water raster is derived in the above model (landwater_c). Use Raster Calculator to generate wave exposure index - Wind energy = % time of wind in that sector * average wind speed (knots) squared in that sector. Wave exposure index is equal to the sum of fetch in each direction * wind energy in each direction. Symbolize the raster into 3 categories using quartiles - 1st category will be Low (0-25), 2nd will be Moderate (25-75), 3rd will be High (75-100). Reclassify the raster (first category = 1, etc.). Convert the raster into a polygon. Use spatial join to add the wave exposure index to the shoreline shapefile. Add Field called “Wave_log” & define three types code as 1 for Low, 2 for Moderate and 3 for High. Add Field called “Fetch_soft” & assign a value 1 if "Wave_log" is "Low". Add Field called “Fetch_hybr” & assign a value 1 if "Wave_log" is either "Moderate" or "High". Data used in Step 3: NOAA Wind Rose data; USGS Wind Fetch Model Step 4: Calculate shoreline change rates: Merge shoreline type shapefile to historic shoreline shapefile for modern shoreline data (date: 02/01/2012). Historic shoreline obtained from the BEG at UT Austin: http://www.beg.utexas.edu/coastal/zip_shoreline/zone14_up10.htm Used the date “07/01/year” when the exact date for a given year wasn’t given. Create a baseline and follow AMBUR user guide to format shapefile and calculate shoreline change rates: http://ambur.r-forge.r-project.org/user/ambur%20basic%20user%20guide%201_0a.pdf. Use Spatial Join to join envelope_transects_analysis to shoreline shapefile – join field LRR. Add field called “Erosion” & define the erosion type as "High" if LRR <= -6.5, "Moderate" if -3.2 >= LRR > -6.5, "Low" if 0 >= LRR > -3.2, and "Accretion" if LRR > 0. Select by attributes, Join_count = 0 & use Field Calculator on selection to change Erosion = Unknown. Add Field called “Erode_soft” & assign a value 1 if "Erosion" is "Low" or "Accretion". Add Field called “Erode_hybr” & assign a value 1 if "Erosion" is "Moderate" or "High". Add Field called “Unknown” & assign a value 1 if "Erosion" is "Unknown". Step 5: Perform final feature selections and assign value for most suitable living shoreline technique as follows: Soft Stabilization - Shoreline = 1 AND Bathy = 1 AND fetch_soft = 1 AND Scarp = 0 AND Erode_soft = 1 AND chan_bord = 0 AND chan_near = 0 AND Hard = 0 Hybrid Stabilization - (Shoreline = 1 AND Bathy = 1 AND chan_bord = 0 AND Erode_soft = 1 AND Fetch_hybr = 1) OR (Shoreline = 1 AND Bathy = 1 AND chan_bord = 0 AND Erode_soft = 1 AND Fetch_soft = 1 AND chan_near =1) OR ( Shoreline = 1 AND Bathy = 1 AND chan_bord = 0 AND Unknown =1) OR (Bathy = 1 AND chan_bord = 0 AND Scarp =1) Retrofit: Soft Stabilization - Bathy = 1 AND fetch_soft = 1 AND Erode_Soft =1 AND Scarp = 0 AND chan_bord = 0 AND chan_near = 0 AND Hard = 1 Retrofit: Hybrid Stabilization - (Hard = 1 AND Bathy = 1 AND chan_bord = 0 AND Erode_soft = 1 AND Fetch_hybr = 1) OR (Hard = 1 AND Bathy = 1 AND chan_bord = 0 AND Erode_soft = 1 AND Fetch_soft = 1 AND chan_near =1) OR ( Hard = 1 AND Bathy =1 AND chan_bord = 0 AND Fetch_hybr =1) Not Suitable - Bathy = 0 OR chan_bord = 1 OR (Shoreline = 0 AND Scarp = 0 AND Hard = 0)

Error Analysis:

Attribute accuracy was verified by manual comparison of model outputs to existing living shoreline projects. Checked for data consistency by visual examination and expert elicitation- compared model output to current living shoreline projects and expert understanding of the Texas coast.

Individual Files: