If I subtract the pixels where vegetation is growing that prevents erosion and sedimentation, from the pixels where erosion is happening (USLE), do I then get the pixels where vegetation has to be replaced?
Best regards Ingrid
Thanks for posting to the forums. Could you elaborate on what your research question is or what you’re trying to achieve? What do you mean by:
do I then get the pixels where vegetation has to be replaced?
Thanks for helping me better understand the question.
the research question it, in which areas vegetation , especially trees, should be established or replaced, to reduce erosion and sediment transport to rivers. So, I understood, as the model calculates the total erosion, AND the Export, And the Sedimentation transport which are stopped by the vegetation, that those pixells, where there is no vegetation to stop erosion or sedimentation transport, are areas, where vegetation should be / could be established, to reduce the remaining erosion / export /sedimentation transport. So, is that correct?
Hi Ingrid -
Using the SDR outputs to consider where to do revegetation can get complicated, since avoiding erosion in the stream involves considering both the areas creating the erosion and the downslope areas trapping the erosion, which it sounds like you’re thinking about.
The USLE output will show which places are producing the most erosion in the first place. This is one place to start, since places with high USLE could be good choices for revegetation. However, some of the places with high USLE might also have low sediment export because there’s good vegetation downslope to trap the erosion that’s produced. So if what you care about is downstream water quality, even though the USLE is high, doing revegetation there might not help much, since the downslope vegetation is already keeping the erosion out of the stream.
The sed_export output will show which places are producing the most erosion that makes it to a stream, which may be a better indicator than USLE if you are concerned with downstream water quality. This does take into account the downslope vegetation, such that if you do restoration in the areas with high sed_export, you’re more likely to have a larger impact.
You can also look at which places have particularly low avoided_export. But, low avoided export may happen because the vegetation is not good at retaining sediment (so could benefit from restoration), or low avoided export can happen when the vegetation is good, but there’s not much erosion being generated upslope for it to retain. In the latter case, doing restoration there won’t help much.
So perhaps looking at a combination of high sed_export values and low avoided_export values would help hone in on the places where doing restoration would have the greatest impact.
Dear Stacie, so many thanks.
so that means, I can substract the sediment transport and the avoided export from the sediment export output? Actually, that is also what I want: to identify the vegetation, which is either not good at retaining sediment, or is absent.
That’s not something I’ve ever tried to do, and thinking about it, do not recommend it.
Sediment export represents the amount of erosion from a particular pixel that makes it to a stream. Avoided export represents the amount of erosion that same pixel retains, both from the pixel itself as well as erosion generated upslope. So it’s not really appropriate to subtract them.
Let me ask some of my colleagues - @adrianvogl @RafaSchmitt @Lisa - any ideas about how we could use the SDR outputs to calculate the best places to do restoration? It seems like something more complicated than just adding or subtracting some of the model outputs.
I think you would probably need to run a scenario with natural vegetation everywhere and compare the results for (a) retention and (b) export to the current baseline. Then you could form some compound index to find where vegetation makes the greatest difference?
Dear Rafael, I am not sure. Where there is everywhere natural vegetation, there is normally no erosion, and therefore no sediment export. but only retention. If you have that vegetation, where there is sediment export and you substract the pixels, where vegetation prohibilts sediment transport, and to be sure also the vegetation, which prohibits erosion, you should be on the safe side, to have the pixels, where you could plant the vegetation to prohibit erosion and sediment export? Or where do I make a mistake in thinking?
The problem is also, that you do not have corresponding termini: You have sediment export and sediment deposition on the one hand, but avoided erosion and avoided export on the other. Therefore, I do not even see, that avoided export would not refer to sediment export, as only sediment transport needs the sediment to be taken away by water flows…
Hi Ingrid, using the SDR model to prioritize/optimize restoration is a tricky question. As you note, the greatest restoration benefits are likely to come in places where restoration would a) trap sediment coming from upslope that would otherwise enter waterways; and b) keep sediment in place on that pixel that would otherwise erode, which is difficult to estimate from either the current outputs or a fully restored scenario. One option to locate good places for restoration is to run a bunch of scenarios simulating restoration at each pixel (or, more realistically) patches of pixels, to see where the marginal change in sediment export to waterways is greatest. Another option, which we employed in the RIOS software (now deprecated, but materials available here), was to estimate those places on the landscape based on a combination of factors. You can see more about how to do that in the RIOS User’s Guide here on pages ~27-32. We are no longer able to provide active support for RIOS, but the restoration ranking equation could be useful to inform your work.
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