I'm modeling an area in which some "recoding" of the LiDAR data was done prior to its distribution and am wondering what effects this could potentially have on my results. Specifically, all inland water bodies were recoded to a blanket elevation of -0.03 meters. (The mean sea level in the region is about -0.21 meters). Thus, in certain instances we have wetland habitats that are at a lower elevation than adjacent water bodies.
The model seemed to run without any trouble and I don't see anything jumping out as odd because of this issue.
On a somewhat related note, the LiDAR data have also been purged of any codes of the estuaries and open ocean (ie., those areas are all "no data"). It seemed critical to have at least a few cells of water adjacent to land coded as such, and I've assigned them all as the MSL elevation.
More generally, my question is, what role does the elevation of water play, if any, in habitat conversions or other model functions within SLAMM? Would you suggest other strategies for getting around the issues described above?
Unless you are running the salinity module, SLAMM pretty much ignores the elevations of inland waterbodies. Sometimes the model may classify inland open water as estuarine open water if it falls at a low enough elevation but this really has no effects on model results for land categories and we pretty much ignore conversions of one open-water type to another open-water type.
Therefore, I'm glad that the model ran without trouble despite that recoding. That's what I would epect.
It is important for SLAMM to have estuaries and open ocean categorized as such in terms of land cover as it helps for calculating maximum fetch for erosion rates. If the model is moving over water to calculate wave fetch and comes to a blank cell it assumes that the fetch is infinite from that point. However, elevations for estuarine water and open ocean are not important.
Elevation of water is unimportant. If you are running the salinity module, then you need bathymetry data, however.