I have a SLR shapefile provided by Party A (random name for anonymity) for the island i’m wanting to perform the coastal vulnerability for. The shapefile shows the extent of SLR under the IPCC AR6 4.5 (middle-road, warming of 2.1-3.5 degrees Celsius) and 8.5 (worst-case scenario, 3.3-5.7 degrees Celsius).
Do i need to create points on the shore of the island and then associate the SLR data with those points. Also do the points need to be equally spaced apart (i.e. every 100 meters) or can they be random (i.e. starting point 20m, 49m, 12m, 120m, etc…)? I’m inserting an example below of what the attribute table of the points might look like, to my understanding:
This image shows a small segment of the SLR shapefile i received. It is contour lines based on the islands topography instead of one complete ‘straight’ line. Is there a way to use this instead of make points? i feel like it might be more accurate as it shows the literal extent of the predicted SLR.
@n-marine , yes, the model requires the SLR input layer to be points, but there is a larger problem here. The SLR input is only useful when there is spatial variation in sea-level rise across your study area. In other words, if some parts of the coastline are expected to experience more/less sea-level rise than other parts. That does not appear to be true for the SLR data you show here.
If the lines you show are intended to represent the coastline under different SLR scenarios, then you could consider using those lines as the landmass input to the model, and run different scenarios with a changing coastline. I’m not sure anyone has done this before, and it may not be easy. The landmass input needs to be polygon, so that model knows which side is land and which side is water. And the DEM, bathymetry, population, geomorphology, and other inputs may also need to be modified in order to accurately represent these new conditions.
For the spatial variability, in the image I show you the black is the current landmass polygon and the lines represent the extent of SLR under the IPCC 4.5 and 8.5 scenarios. Does this count as spatial variability?
If i were to represent the distance that the shoreline recedes in the 8.5 scenario, would i pick a point and measure the distance between the landmass polygon edge and the 8.5 line and insert that value in the third coloumn (like i showed in the og post). That value would then be represented by a physical point placed on the edge of my (black) landmass polygon, yes?
And for the distances between the points, do the points need to be at the same distance between each other?
No, in this case spatial variability means some parts of the coastline are expected to experience more/less sea-level rise than other parts. It really only makes sense on very large regions. For example, one place is expected to have sea-levels rise at a rate of 5mm/year, and at another place the rate is 3mm/year. The rate of sea-level rise varies across space. Here is an example of this sort of data: Sea Level Trends - NOAA Tides & Currents
If you have data about rates of sea-level rise, the location of points do not matter. The model will determine which of the shore points created by the model are closest to which sea-level rise points, and join the data accordingly. Sea-level rise points do not need to be evenly spaced.
ok so my data needs to be in mm/yr with each section of the coastline having different rates of SLR. For example P1= 2.5 mm/yr, P2= 2.9 mm/yr, P3= 1.9 mm/yr?
I just don’t understand how what i show in the picture is not spatial variability. The black is the current coastline, the pink is the extreme SLR scenario coastline and we can see the the lines are jagged and show some parts to recede more into the coast than others. You can even see a point on the image where the scenario lines touch the border of the island showing no SLR there, while other points recede alot; to my understanding that is spatial variability. I looked at the NOAA link you sent and i see different coastlines have different rates of SLR, and to me the image i sent also shows theres different rates of SLR at different points (because the coastline recedes at different lengths inwards).
In this image the white line is 0.87m SLR, light blue is 1.36m, and dark blue is 1.8m.
You are saying i cannot tell the model the distance the shoreline recedes at different points under a certain scenario, instead i need to explicitly state the mm/yr change at each shore point (of my choosing).
(Is there a way to calculate the SLR at different points? i mean i have the visual information of where my island border is and where the shoreline recedes to with SLR)
Yes, sea level rise rates are appropriate. The particular units don’t matter.
I could be wrong, but my interpretation of the image is that the coastline recedes more in certain places because of the local topography, not because different parts of the coastline experience different rates of sea-level rise.
For example, let’s say in this area, sea-levels are rising at a rate of X mm/year, vertically. For a section of coastline that is a steep cliff, this might not represent any horizontal change in the position of the coast over the next 20 years. Whereas a section of coastline that is a low-lying, flat area, this same rate of sea-level rise might result in significant horizontal change in the coastline over this same time. Therefore, there is no variability in the rate of SLR across space, it is X mm/year everywhere. There is however, spatial variability in the topography, or elevation. And this should already be accounted for in the model using the Digital Elevation Model input, where relatively low elevation areas are coded as more exposed to coastal hazard than high-elevation areas.
If you are interested in knowing which areas of the coast are most at risk from sea-level rise, and how that changes according to the SLR scenarios you have, I think your SLR data already illustrates that quite well.
