 The first speaker will be Vanessa Gable talking about river incision across the lithologic boundary. Thank you. So what I want to tell you all a little bit about today is the work that I've been doing trying to understand how fluvial incision gets expressed across lithologic boundaries. And the area where I'm studying this is the High Plains of North America. So to get everyone oriented here, what we're looking at in this figure is a DEM of the modern topography of the study area looking to the northwest. So the high red peaks are the southern Rocky Mountains in Colorado. And as you move to the north and lose some elevation you're moving into Wyoming. The sharp break and slope that you can see is the area that I'll be referring to as the mountain front throughout this presentation. And this broad flat surface to the east are the High Plains. Now what I've outlined in white here is the preserved surface of the Ogallala formation. The Ogallala is a mid to late Miocene formation with an end deposition date around 5ma. And it's significant because it captures a time when the plains switched from being in an aggregational mode to a degradational mode. So as the Ogallala is being deposited, the plains are capturing sediment. And after the end date of Ogallala deposition, plains that are traversing the mountains or rivers that are traversing the mountains start to incise into that surface. And what you can see from just a cursory study of this DEM is that incision has really been focused around the mountain front streams have carved deeply below the Ogallala in that location. And the amount of material that's been eroded seems to attenuate quite rapidly as you move east. And so I'm interested in understanding why incision into this surface occurred in the style that it did. So when I say style, I mean both the magnitude of incision as well as the spatial extent. So why is it focused at the mountain front? So to answer this question, we need two things. We need a paleotropographic reconstruction so that we can actually quantify how much materials been removed. And then we also need a numerical model so that we can test different erosion scenarios. So for our paleo surface reconstruction, what I've done is interpolate between the Ogallala formation where it is well preserved on the plains and sparse patches of fluvial gravels that are found within the mountains. What the presence of those gravels in the mountains suggests is that at the time of Ogallala deposition, the sedimentary systems were much more continuous. So we graded from high elevations in the west to low elevations in the east much more smoothly than we do today. And so when we do this interpolation between the gravels and the Ogallala formation, the surface that we can reconstruct supports that hypothesis. And so the surface that you're looking at now will be used as the initial condition for all of our subsequent model runs. We're using a landscape evolution model that where the change in elevation at every point in our model is the sum of an amount of material eroded minus an amount of material deposited at that point. Erosion is governed by the stream power theory where the area and slope are calculated within the model, but the erodibility efficiency is a user defined value. So what I've done for my model setup is define a low erodibility for the mountains representative of granitic rocks and a higher erodibility for the plains more representative of sandstone. For the deposition calculation deposition is a function of the sediment flux and some effective grain size. And that effective grain size is a value that we really don't know either. So in addition to testing different values of erodibility, I'll be testing different values of an effective grain size. So what we want to do in these model runs is basically start with our initial reconstructed topography and erode it towards something that looks looks more like the modern topography. In order to evaluate our model performance, we need to understand what that sort of difference that we're looking for is. So what you're looking at here is a DM of difference where all the areas that are lighting up our places where material has been removed in the modern. So this green curve is just showing us the amount of material removed so we see up to around 400 meters of elevation removed right at the mountain front. And as we go into the plains, essentially no material being removed so no elevation change between the ancient and modern landscapes. So, when we run our models, what do we see. So what I've tested for in just these preliminary results are three values of an effective grain size moving from point zero one up to 100. And in each of these we're also looking at three amounts of contrast in erodibility between the mountains and planes from the planes being 10 times more erodible than the mountains up to 30 times more erodible. What we see in these top two plots is that the model appears to be quite insensitive to the contrast in erodibility and the shape of the surface that we produce is is also quite insensitive to the contrast in erodibility and the effective grain size that we choose. What this what these curves tell us where it's below the modern curve closer to the mountains and above the modern curve on the plains is that rather than getting focused wells of incision we're getting a much more dispersed erosive signal. That's like distributed down river valleys. So this really isn't capturing the focused well of incision that we're looking for. What the grain size really does seem to control is the runtime of the models. So much so that when we move to this bottom plot, we see something that looks more promising for the erosive signal, but the grant, but the runtime is exceeding 5 million years so we're running for too long. So where do these results leave us? Basically what we know at this point is that we need to more fully test the parameter space of both the erodibility and the effective grain size. There's going to be a range of solutions that give us the curve that we're looking for. The model seems to be insensitive to a contrast in erodibility, but it's also possible that the contrast is just much higher than what I've shown you here. So basically another possibility is that we need some additional forcing to replicate the modern topography, whether that means honoring, differing erodibility values in stratigraphy or inducing some sort of external forcing like tectonic tilting or climate change. So with that, I'll take any questions. Great. Thanks, Anessa. And as a reminder to folks, please raise your hand if you'd like to ask a question. I can't see the chat or I'm not sure if, okay, no one's raising their hand. So I have a question. When you were talking about the different erodibility for the mountains and the plains. Yeah. How were you doing a sort of an abrupt transition or were you a step function or were you doing a more gradual transition? And did you have problems with numerical stability? Yeah, it is an abrupt transition. And so that is one of the things that I, yeah, it's an abrupt transition. So that in itself is, you know, probably not particularly realistic. And also what I'm kind of starting to think about on this last slide is honoring stratigraphy. So I think one of the things that might be going on is that closest to the mountain front. You completely removed the Ogallala and started to incise down into the pier shale, which has a much lower erodibility, even than the Ogallala. So, so using one erodibility value for the plains is probably not particularly realistic way to model it. Thanks. And we have one more question from Nicole. Yes, Brini. She says, great job, Vanessa. Maybe I missed it, but how did, how did you initially estimate erodibility? Yeah, so the initial estimate of erodibility is, so I've kept it constant for the mountains and just varied it for the plains. And that value that I used for granite is taken from an average value published by Katie Barnhart and others earlier this year, where they basically combed the literature for different values of erodibility that people have used for different lithologies and compiled them all. And so I took an average value from that work. Thank you.