Hi Scott:

First of all, please note that there is a difference in datum used for the two parameters (which is probably not an ideal design.)   GT is expressed as meters between MLLW and MHHW.  The salt elevation is expressed as height above MTL (the mid point between MLLW and MHHW), so is a lower value than the GT generally.

As you have likely seen in some of our reports, this is based on "frequency of elevation" analysis from observed-data analysis so that it takes into account wind tides as well as astronomical tide cycle data.  I can point you at one of these analyses at some point if you'd like.   If you calculate a daily high water level using NOAA data for several years and then calculate the 0.967 percentile of those data that pretty much will get you there.

Best!  -- Jonathan

Sorry -- the forum stopped notifying me of new posts apparently and I completely missed this until today.

The accretion and historical SLR and uplift subsidence equations and considerations haven't changed since the previous version.

Elevation data can be output as MTL or NAVD88.

Greetings.

You are using a different development platform than the model was created on.  Things have changed, see:

https://stackoverflow.com/questions/44227692/casting-with-tulargeinteger-in-delphi-10-2-tokyo-differ-from-previous-version

Looks like it should be a quick code fix if you'd like to make it.  Otherwise you should be able to download [Embarcadero Delphi XE3] as a licensed user of the more recent version.   [edit- fixed version required at this time]

Best regards-- Jonathan

This category is usually changed as a function of the "salt elevation" parameter which has units of meters above MTL.  Make sure that parameter is properly set within the "Site Parameters" screen.  It is often approximately 133% to 140% of MHHW (relative to MTL). 

To examine the distribution of dry-land cell elevations you can go through "elevation analysis" (you must go through the "set map attributes" button first to load all cells and elevations for analysis.)  Select run elevation analysis and you can view statistics and histograms about each land-classes elevation.  There's more information about this screen in the users manual (context sensitive help).

I hope this gives you a hint as to how to proceed, otherwise please post again!

A users guide and sample files are included in the installer:

http://warrenpinnacle.com/prof/SLAMM/SLAMM_Versions.pdf

https://github.com/WarrenPinnacle/SLAMM6.7/tree/master/DOCS

Sorry I let this thread go cold.  I have not seen this type of response.  Wonder if you figured it out.  You may want to check the "marsh collapse" parameter that could cause this problem if mis-set.

Tidal ranges affect SLAMM in many ways.  Certainly the model predicts significantly enhanced resilience to SLR for larger tidal range sites.

For one thing, a fixed change in tide levels (due to SLR) is a much higher percentage of the tide range in a microtidal site than a macrotidal.  This means that a marsh (that exists within the "tidal frame") can have much more elevation capital in a macrotidal site.

But with regard to the question at hand.  The SLAMM model does not directly model sediment inputs but those inputs come into account in the relationship between marsh accretion rate and marsh elevation.   See for example Figure 4 in this document.  https://www.sciencedirect.com/science/article/pii/S1364815216302705  This figure was derived based on the calibration of a model that does explicitly model sediment inputs (MAM3) 

We recognized that a model such as MAM3 generally predicts a single parabolic accretion-rate response to SLR (if you hold sediment inputs and tide range constant over time).  (The parabola has accretion rates on the y axis and marsh elevation relative to MTL on the x axis)  Therefore we allow for an input of this type of parabola to SLAMM.  A site with a larger tide range has more elevation capital to work with and will generally accumulate more sediment over a period of SLR.  MAM3 also predicts increased sedimentation rates in sites with larger tide ranges.

To generate the required parabola a site-specific empirical data analysis or application of a site-specific mechanistic model should be utilized. 

Hope this is useful and sorry about the long delay in response

The input files look good but there was one key issue.  The CRS units for SLAMM projects must be meters.  I am sorry if that has not been made clear enough through the GUI and/or users guide.  I will specify that on the file-input GUI for the next version .

Best regards -- Jonathan

If you are using a dike layer I would turn that off as a test.

Next thing to do is look at the elevation analysis -- Set Map Attributes, Elevation Analysis button towards middle of Analysis Tools tab.  Then "Run Elevation Analysis (This Site)  Double click on the category names to sort, sorting by n cells can be useful.  The 5th percentile for wetland classes should be around the minimum elevation. 

See the help file text for more information on interpreting the matrix on that page.  Also you can see this reference:

https://docs.google.com/spreadsheets/d/13AhT1PwsUsmOSA3LdGTtbWZIBIk1DoZ7D7KCheGlXtk/edit

If you want to email me the SLAMM6 and spatial files I will take a look at it, or you can just email the elevation-analysis matrix after exporting to Excel for now.

Good luck!  -- Jonathan

I ran multiple tests and, for my study files, when there is no dike input raster map, the maps produced have been identical whether "use dikes" is checked or not.  Are you willing to share your input files so that I can look into this further?   Regards -- Jonathan

If you do not have a dike file specified, the results should be identical.  Please let me know which version you are using and I'll run a test and ensure there is not a software bug causing this problem.

As you know, NRow and NCol and "lower left corner attributes" must match precisely.

In the QGIS world we use GDAL WARP to ensure that this is the case.

It is best to set the attributes precisely when converting from NWI polygons into a raster because re-projecting or moving raster files can result in data loss.

I cannot speak to the ESRI world -- anyone else?

Best regards -- Jonathan

I think the problem is that the ASCII DEM is treating 1.17e-38 as its NODATA value.  The GIS software is then not recognizing this NODATA value.  Try specifying a NODATA value of -9999 prior to conversion and this may solve the problem. 

Also, look at the header in the first lines of the ASCII DEM to see if that helps understand the problem (the NODATA value is defined there.)  The best way to do this is convert the file type to a TXT file and look at it in the Windows Explorer Preview pane (not Internet Explorer, just the Windows Explorer file manager).

Hope this is useful.

On November 3rd, at 10:30 AM EST, Warren Pinnacle Consulting Inc. will present the results of a multi-year sea-level rise modeling project supported by the New York State Energy Research and Development Authority (NYSERDA). This project has produced a new decision-support tool designed to help decisionmakers understand the benefits of different adaptation strategies for wetland management under uncertain future conditions. The presentation will focus on background of the project and results from three New York county case studies, as well as presenting a tutorial for users interested in learning how to use the tool.

SLAMM Marsh-Management Tool
Friday, November 3, 2017

10:30 am  |  Eastern Daylight Time (New York, GMT-04:00)  |  1 hr 30 mins
Register
After your request has been approved, you'll receive instructions for joining the meeting.

Need help? Go to http://help.webex.com.

Prioritization of marsh-management strategies can be a difficult undertaking. Ideally, a manager could evaluate the relative benefits of adaptation strategies and maximize wetland benefits while considering uncertainty both in future sea-level rise and dynamic marsh response. Warren Pinnacle has developed a modeling framework to evaluate the costs and benefits of management strategies while accounting for these uncertainties using the SLAMM marsh migration model. Model results are combined with ecosystem-valuation assessments from stakeholders that define a set of relative "wetland benefits" (e.g., habitat preservation, flood protection), and each site's wetland benefits can then be projected into the future and compared to the estimated costs for each adaptation strategy. By calculating the "wetland benefits per estimated cost" ratio, one can identify the most effective marsh management strategies.

To understand these curves and parameters, please see the spreadsheet:

SLAMM6_Accretion_Release_6.5.xlsx

Which is installed along with SLAMM. 


You will see that the equations describe a third order polynomial which then can be scaled to the min and max accretion values.  That allows you to play games keeping the shape of the feedback curve intact but increasing or decreasing the minimum and maximum accretion values as part of a sensitivity or uncertainty analysis.

Let me know if you can't find the spreadsheet or have additional questions.