Lifespan of marsh units in Connecticut salt marshes

This process step was performed by Kate Ackerman, using ArcGIS Pro (ver. 3.2.2). In this and all process steps, for simple operations the name of the geoprocessing tool used is given in capital letters; for complex operations, the name of the geoprocessing tool used is given in capital letters and any critical parameters used are given in parentheses, separated by a semicolon, immediately after the tool name. The input and output file names are provided in [square brackets] when necessary. Units for length and area calculations are meters (m) and square meters (m^2) unless otherwise stated.
Merge input datasets.
a) Download elevation (mu_elev_CT.shp) and unvegetated to vegetated marsh ratio (UVVR) (mu_UVVR_CT.shp) layers from the publications that cover the salt marshes of Connecticut.
b) JOIN the elevation and UVVR datasets to create one shapefile with both datasets in it.
c) Convert the coordinate system from Web Mercator to the North American Datum of 1983 (NAD 1983) geographic coordinate system and add the coordinates for polygon centroids (X_POINT, Y_POINT) in decimal degrees to the data table using CALCULATE_GEOMETRY_ATTRIBUTES tool.
d) Export the following variables to a comma separated values file [CT_mu.csv]: X_POINT, Y_POINT, FID_CMU, UVVR, ATOT_M2, AVEG_M2, mu_ELEV, vg_ELEV, FLG.

This processing steps was performed by Zafer Defne using VDatum online (VDatum ver. 4.6.1) and Matlab (ver. 2021b).
Convert datums and calculate lifespan.
a) Convert marsh unit elevations from the North American Vertical Datum of 1988 (NAVD88) to Mean Tide Level (MTL) referenced elevations.
Input the ASCII file of latitude and longitude coordinates and elevation from CT dataset (CT_mu.csv) to VDatum software, and transform vertical datum from the NAVD88 to MTL. Do this for the marsh unit elevation (MU_ELEV) and elevation of the vegetated part of the marsh unit (VG_ELEV) to calculate MU_ELEV_MTL and VG_ELEV_MTL, respectively. Use value from the nearest Vdatum point for any point where VDatum has no data.
b) Calculate sediment budget from UVVR based on Ganju and others (2020) with SB=-0.416*log(UVVR)-1.0749, where SB is sediment budget in kilograms per square meter per year, and log() indicates natural logarithm function.
c) Calculate total sediment flux under background relative SLR (BGRND) with SF=SB*ATOT_M2, where SF is sediment flux in kilograms per year and ATOT_M2 is total surface area of marsh unit in square meters.
d) Calculate total sediment flux under global mean sea level (GMSL) scenarios (for example, GMSL03 scenario means GMSL rise of 0.3 meters). SLR reduces vegetated marsh area, therefore, causes reduction in sediment flux. The sediment flux under SLR is calculated with SF_SLR=(SB-SLR_RATE*RHO_F)*ATOT_M2, where SF_SLR is sediment flux under SLR, RHO_F is dry bulk density of future deposited sediment. RHO_F was assigned 159 kilograms per cubic meters from Morris and others (2016). SLR_RATE is the SLR rate, calculated as SLR_RATE=(RSL2100+RSL_OFFSET)/100-RSL_VLM, where RSL2100 is the relative sea level by 2100 under a global mean sea level rise scenario, RSL_OFFSET is the offset to initiate the projection at year 2000, and RSL_VLM is the relative sea level contribution from vertical land motion.
For sea level rise projections, Sweet and others (2022) SLR data within the region were used. A total of 27 points including 15 stations and 12 grid points were within the bounding box with lower left corner of (-74.1463N, 40.6391W) and upper right corner of (-69.0000N, 42.0000W).
Interpolate the SLR_RATE from 27 points over a regular grid using GRIDDATA function with natural neighbor interpolation (grid size 51 longitudinal by 14 latitudinal points). Assign to each marsh unit the interpolated SLR_RATE value from the nearest grid point. Do this for the three scenarios considered: GMSL rise of 0.3 meters, 0.5 meters and 1.0 meters by year 2100 and calculate sediment flux for each of them.
e) Total sediment mass in the vegetated plain above MTL is calculated with TS=vg_ELEV_MTL*AVEG_M2*RHO_E, where TS is total sediment mass, AVEG_M2 is the surface area of the vegetated part of the marsh unit and RHO_E is the dry bulk density of existing marsh substrate sediment. RHO_E was assigned 373 kilograms per cubic meters from Morris and others (2016).
f) Calculate lifespan (in years) for the background relative SLR with the equation BGRND= -TS/SF. Calculate lifespan (in years) for global mean sea level rise by 0.3 meters, 0.5 meters and 1.0 meters by year 2100 scenarios with the equation GMSL= -TS/SF_SLR for each scenario (GMSL03, GMSL05, GMSL10, respectively).
g) Output Matlab data as a comma separated text file [CT_lifespan.csv].

This processing step was performed by Zafer Defne using ArcGIS Pro (ver. 3.2.2).
Finalize the feature dataset and change projection.
a) JOIN lifespan calculation results file [CT_lifespan.csv] with the marsh unit features using ADD_JOIN and join field as FID_CMU.
b) For marshes that are more stable, lifespan calculation sometimes results in large numbers that are far beyond the lifespan horizon of interest. Also, positive sediment budget implies unlimited lifespan. For these units, set the maximum lifespan value to 10,000 years.
c) Set lifespan values to -9999 for units with no vegetated area or with missing elevation values (FLG values that contain any of -1 or -200 values in them) so that they can be labeled as not available or excluded while plotting the data.
d) Set legend label for lifespan values less than 0 as imminent.
e) Rearrange field names and change the projection for better performance of web services with online base maps. PROJECT(Input coordinate system= NAD 1983 Geographic coordinate system; Output coordinate system=WGS 1984 Web Mercator Auxiliary Sphere; Geographic transformation= WGS 1984 (ITRF00) to NAD 1983) the feature dataset to obtain the lifespan values [mu_lifespan_CT.shp].