 Great. I'm excited to be here today to talk to you all about some of the work I did as part of my dissertation research. So currently a postdoc at the EPA, but this is primarily work that I did with Brad Murray, my PhD advisor at Duke, as well as the CSDMS integration facility. And specifically, I worked really closely with Eric Hutton. So definitely want to acknowledge Brad and Eric and all this work. So I don't think this crowd needs a ton of motivation here, but deltas are really important landscapes. They've long been ideal for human settlement. And they are flat and fertile. So people have lived on them for a long time. So currently, they're really densely populated or tend to be densely populated landscapes. They're also really important for things like transportation and trade. They have very important waterways and they host all kinds of natural resources that have been important for us. But despite the importance of these landscapes, we don't fully understand the drivers of delta morphologies. And this is especially the case when we think about how humans have been impacting morphology over the past, the recent history as well as farther in the past. And so unfortunately, again, despite the importance of these landscapes, they're increasingly vulnerable. And this is in part due to things like you static sea level rise as well as increasing rates of subsidence. And a lot of these these factors are things that we have done as in terms of anthropogenic modifications of the landscape. So river channel evulsions are a natural process that happens on deltas. And by channel evulsions, I simply mean that they're just changing course relatively rapidly. And these low landscapes, the Delta Delta take landscapes are built through the stacking of these different lobes and the way that these lobes form along the shoreline are through these repeated channel evulsions that redistribute where the sediment is going to be deposited along the shoreline. And so for the case of the Mississippi, you can see that over the past few thousand years, there have been a number of different channel evulsions that have caused these different lobes to stack upon one of one another. And these evulsions, although they are a natural process are currently not great for us as humans. So we have built up a lot infrastructure around rivers, for example, New Orleans. And so if the channel were to relocate now, not only would that impact us economically, but it also could cause all kinds of problems in terms of flooding and damaging infrastructure and threatening human lives. So we, in the case of the Mississippi, about almost a century ago now have been regulating the flow of the Mississippi down its current path versus letting it evulse to go down the Echafalaya River. And so an interesting thing to note here is the modern delta, the modern birdsfoot lobe actually sticks out quite a bit farther than the rest of the lobes in part due to this fact that we're regulating where the channel is going to go or where the channel is going. So these are really natural processes that happen on deltas. But again, we don't fully understand all the drivers of when, where and why these channel evulsions are going to occur, even though they've been focused on a lot of research as of late. And so I think everybody in this room has probably seen some iteration of this ternary diagram, but just to hit home that rivers or deltas are influenced by a whole mix of things, including rivers, waves and tides, which is again represented by this ternary diagram here, the relative influence of those things. And there's also things like grain size and sediment cohesion that are going to impact delta morphology. And this is increasingly important to understand these relative influences because we, as humans, as I mentioned before, have done a lot to shape these landscapes as well. And so in my research, I've been particularly interested in understanding the impact of rivers and waves and how these two, how these two factors are interacting to shape delta morphology and also what do these interactions do in terms of affecting evolution behavior? And that's a particularly important question over large space and time scales. So as we think back to the Mississippi, we're talking about thousands of years of evolution and really large spatial scales. So there are a couple key questions that I sought to address in my work. And again, just trying to figure out what are the the feedbacks between the fluvial and coastal processes that drive morphology and evolution behavior, as well as how are these morphodynamics affected over large space and time scales? So again, because these things are happening over a long period of time, we would expect things like sea level rise to change or sea level to change. And so not only do we need to understand how these things interact, but we need to know how they're going to interact in the future with changing forces. And so no previous delta model seemed fit to address the sort of questions that I wanted to ask over these large space and time scales. So I ended up developing a new delta evolution model using the CSDMS tools. And so this model was designed to look at again these large space and time scales. And it's also been sort of generally designed not with any particular delta in mind, but it can take and represent deltas with a range of fluvial and coastal processes. And I'm also going to be representing everything down dimensionally. So this model is scale invariant. And we decided to base the model on couplings using the basic model interface, which I'm sure everybody's heard a lot about this week. And so as a first step, I developed this river of ocean and floodplain evolution model, or what I'll be calling Raffam, and I coupled it to a preexisting coastline evolution model or what I'll be calling CEM. And the nice way as a nice thing about doing things through this coupling is that it allows for a lot of additional coupling. So for example, a marsh module or more complex subsidence module in the future. So I'm going to briefly describe the two models and then get into the results. So in Raffam, the river cell widths are wider than the channel width such that such that we're not resolving sub cell scale fluvial processes. But an important thing to note is that the river levees, the flood plain deposits that form from overbank sedimentation right adjacent to the river, those are contained within a river cell. As you can see in this cross section here, so the levees. And so the flood plain cells that I'm talking about when I talk about the flood plain generally, I'm not talking about the levees, but sort of the more distal flood plain away from the levees. And so the river course is determined using a pretty simple steepest descent algorithm where the this algorithm is going to iterate along the elevation grid until it reaches sea level. And the elevation changes along the river profile are calculated using a linear diffusion equation. And in all of the results that I'm going to show you here, subsidence is uniform across the domain. And any new land that's created behind the shoreline. So as the shoreline progrades, there will be marsh is created behind that shoreline and that marshes maintain maintain some small elevation above sea level due to organic sedimentation processes. And we also impose a quasi equilibrium generalized prune rule, erosion of the shoreline as sea level transgresses on shore. And so as either base level rises or the river progrades because of that linear diffusion equation, the river bed will also agree. So at a certain point, the river bed will become relatively perched versus the distal flood plain location. And so I use what it's just a normalized super elevation ratio where the channel elevation channel bed, channel bed super elevation is normalized by the channel depth to calculate when an evolution would occur. So I set that as a critical parameter to determine at this point, then an evolution could potentially occur. So for a super elevation ratio of less than one, it means that the river bed elevation is lower than the flood plain elevation versus greater than one means the river bed elevation is higher than the flood plain elevation, I think I said. So for less than one, it's below the flood plain elevation greater than one higher. And so once this critical super elevation ratio is reached in a given river cell, the new steepest descent path to sea level is calculated. And if that path is shorter and therefore going to be steeper than the prior course, the evolution is successful. So the river actually changes course. Whereas if the river path, the new river path to sea level is not shorter and therefore it's not steeper. In that case, the evolution is not successful. And instead, a crevasse play is deposited adjacent to the river there. And so the fluvial sediment flux from RAFM is then redistributed along the shoreline via CEM or the coastline evolution model. And CEM conserves near shore sediment. And it assumes an approximately constant shore phase geometry and long term shore phase geometry. And it uses gradients and a long shore sediment transport to calculate erosion and accretion of the shoreline down to the shore face depth. And in CEM, the offshore wave approach angle changes daily, we call this mix of influence from different wave angles to wave climate, which is represented by two different parameters. A being the asymmetry parameter. So it's the fraction of wave influence from waves approaching from the left. And U is the diffusivity coefficient. So it's essentially it is how what fraction of wave influence is coming from high offshore wave angles versus low offshore wave angles. So this is important in that high U greater than 0.5 or a high angle wave climate, as I'll be calling it, that sort of that wave climate tends to grow shoreline perturbations. And it's anti diffusive versus a greater influence of low angle waves or a U less than 0.5 will tend to smooth out shoreline shoreline perturbations and be diffusing these short line shapes. And so I've used again, I already used the BMI to couple these things, but I also use the CSDMS cluster at the time beach, which is sad to say snow longer with us, but I use the beach to perform a bunch of parameter studies to look at how things like change in use sea level rise rate and wave height affected both the delta morphologies and the evolution dynamics. And before jumping into those results, I want to show you just a few videos, just to give you a sense of how the model evolves over time. So in these videos, there's no sea level rise, but so we're just going to be looking at the channel procrating. And here it's pretty explanatory. The green is the land, blue is the ocean, the blue line is represents the river cells. And for this case, the wave height is relatively low and the U values 0.3. So it's a diffusive wave climate. And then on all the work that I'm going to show you a is 0.5. So that means we have a symmetric wave climate and a symmetric influence. You have waves coming from the left and the right. So I'll set this off. And so again, relatively low wave influence. So the river procrating relatively quickly, I should also mention that the backwater links here are just a characteristic length, which is the channel depth divided by the slope. And time is non-dimensionalized by a channel filling time scale. So river procrates quickly, waves aren't doing a lot to smooth the shoreline. If we bump up the influence of waves, again, with the same A and U values except for a higher wave height, then procreation is inhibited. The river's not procrating as quickly because more of that sand is being spread along the shoreline. And so evulsions don't happen quite as quickly. And something that's interesting to see too is that the old delta lobes tend to diffuse away, whereas before the lobes persist, or the shoreline shapes weren't diffusing as quickly. Okay. So now I'm going to show you a profile view that follows the river course. So here the river cells, this is 10 river cells, is equivalent to one backwater length to relate back to before. And the blue line is following the river bed elevation, the green lines of the adjacent flood plain elevations. And in this case, the critical super elevation to trigger an evulsion is one, which you'll see pretty clearly. So again, this is with no sea level rise and no base level rise, which can also drive in channel aggregation. You'll notice as the channel is pro-grading, the river bed is aggrading, and the blue line is getting closer to the green lines, which means that the super elevation ratio is getting closer to one. So once that ratio is met, and a new steepest distinct course to sea level is determined, then the evulsion occurs. And another interesting thing to note is that as the channel shortens and steepens, that wave of channel degradation migrates upstream. And so now I'll jump into what the parameter study results look like. And so in all of this, I'm holding the background wave characteristics, or the, I'm sorry, the background river characteristics constant. So it's just changes in the wave climate that are dictating changes in the fluvial or the delta morphology here. So these plots here are a range of different morphologies where we have increasing wave height along this axis from the left to the right and increasing influence of high angle waves from the top to the bottom. And we can represent the relative influence of the waves and the river using this fluvial dominance ratio or R, which is essentially just a ratio of the fluvial sand flux QR and this QX max value, which is the maximum possible longshore transport from waves, a longshore transport from from the river mouth to the left and the right of the river mouth. So it's essentially a measure of both the wave height and the value or influenced by both wave height in you. And so this R is essentially a ratio of how quickly is sand spread along the shoreline away from the river mouth where are greater than one would tend to represent what we think of as a river dominated delta and are less than one we would tend to think of as a wave dominated delta. So if we start over here on the left hand side of this set of plots at relatively low wave height, the sign of or the value of you or the sign of the wave climate diffusivity doesn't have a big impact on the delta morphologies. And this kind of makes sense. If the waves are small, they're not going to have a big impact on what the delta looks like. So that you doesn't really matter. But if we move farther to the right, the sign of the where wave heights are increasing so that you at the R value is decreasing. The sign of the wave climate diffusivity does matter that you value does matter. So looking up at the top where we have a relatively diffusive wave climate that you values left some five shorelines are relatively flat. They have a diminishing aspect ratio because the wave climate is working to smooth out all those shoreline perturbations versus going down to the bottom, the shoreline is locally smooth, but shoreline perturbations are not are allowed to grow because of that anti-diffusive wave climate. And another interesting thing to notice that for a diffusive wave climate, the old delta lobes are tending to diffuse away relatively quickly versus especially down in this bottom right hand plot. The old delta lobes actually persist as these like cuspate like features after the river of ulcers away from them. And so the relative or the directional spread of offshore wave influence also impacts the evolution time scales. And by that, I just mean, how quickly does it take for an evolution to occur? And so in these plots, I'm showing on the y axis that time to evulsion or how long it takes the evolution to occur on the that's on the y axis and on the x axis, it's increasing sea level rise rate. And I've plotted four different you values. So the top ones are diffusive and these bottom ones are more anti-diffusive and a range of wave heights. So the blue and the green are relatively low wave heights, whereas the warmer colors are the higher wave heights. And so first looking at where we have a greater influence of from the waves, so the bigger waves of the warmer colors and where you values are smaller or more diffusive, evulsions will tend to take longer. And you saw this in the video, evulsions will tend to take longer because that shoreline progression is inhibited. Sand is being spread farther away from the river mouth. Whereas with a larger you value, these of the evulsions are able to occur more quickly because propagation isn't as inhibited. And then interestingly, looking at sort of the smaller wave side of things, the wave climate diffusivity isn't as important again, because the relative influence of the waves relative versus the the fluvial impact, so the fluvial forcing, it's relatively small. So propagation is going to occur the both regardless of what the wave climate diffusivity is and evulsions are not are going to occurred about the same rate. And we can also look at how sea level rise impacts the evulsion timing. So it's more intuitive to think about the diffusively wave dominated delta. So typically we think about wave dominance as tending to slow down the rate of progression again. And so therefore, or we think about base level rise as driving evulsions happen happening more quickly. And this is the case for the diffusively wave dominated deltas. And we look up here. So looking to the right on the plot, the time scale of evulsions for these of these warmer colors decreases. But we didn't find that that was the case for the river dominated deltas, or for these wave dominated deltas with a bigger value or a more anti-diffusive wave climate. And that's pretty counterintuitive and in contrast to what people have tended to talk about. And so we thought about developing some analytical time scales for base level rise driven, progradation and evulsions and progradation driven and progradation driven evulsions. And if we can compare them, it makes a little bit more sense. So this TB is a minimum time scale for base level driven evulsions. And I don't have time to go into the details of these. But the TP is this is a minimum time scale for progradation driven evulsions. And so if we compare the two time scales, we can think about when that sea level rise rate will play it will will have an impact on evulsion timing. And we can do a little rearranging to look at when that time scale for progradation driven evulsions is much faster than base level rise driven evulsions. And so if that's the case that those progradation driven evulsions are happening much faster than base level rise can influence the channel filling processes then sea level rise just isn't going to have much of an impact on the evulsion timing. So we can do a little rearranging with these time scales and come up with this relationship where we can look at what the sea level rise rate and some characteristic geometry from the delta lobe and understand when this progradation when the time scale for base level rise will be relatively high versus the progradation. So just to give you a sense for the Mississippi actually we would expect that the times the base level rise driven aggregation is not as important as the progradation driven aggregation. So this just means that base level rise may not or sea level rise may not have as much of an impact on how quickly evulsions occur and the absence of thinking about all of this stuff. And then another thing to quickly notice that the evulsion time scales and this is intuitive the evulsion time scales are going to depend on how that super elevation ratio that's required to trigger an evulsion. So how much n-channel aggregation is required to trigger the evulsions. If the super elevation ratio is small evulsions will tend to occur more quickly because you just don't need as much n-channel aggregation. And so I also thought about looking at the evulsion length scale which is also a really important character stick of these processes and most evulsions in nature in the lab have tended to scale with the backwater length which I briefly defined before but to bring up again is geometrically just defined as the channel depth divided by the channel slope. So it's a characteristic length scale and again all these evulsions have tended to fall scale somewhere with this backwater distance. And it's a geometric distance but it's also the part of the river that tends to feel the effect of base levels where the hydrodynamically. So it's impacted by things like by where the actual like sea level is hydrodynamically as well. And so because of that there's been a lot of work that's come out recently focused on understanding how this back how backwater effects hydrodynamically can create a preferential length scale for evulsions. And in this this view of evulsions these there's a preferential length scale for evulsions that tends to occur because of the alternation between high and low flow conditions and that essentially I'm so oversimplifying it but it causes a location within the backwater length or that scales with the backwater length where sediment is preferentially deposited and so evulsions tend to occur at that location. But I don't include any of those backwater hydrodynamics in the RAFMC model and we still find a preferential evulsion length scale that scales with the backwater length. So these are just three snapshots of those profiles and from before that you saw so and you'll remember that in the coupled model the riverbed approaches the super approaches super elevation most quickly or the critical super elevation ratio most quickly where the break and slope in the flood plain is and so the river becomes super elevated most quickly at that break and slope and this is interesting because instead of being driven by backwater hydrodynamics this is more of a geometrically driven evulsion explanation. And I looked at a range of different or two different critical super elevation ratios one and point five which are bounding of what we would find or what these values typically are for evulsions for observations of evulsions in the field and found that again these are a set of different model experiments for each of the colored envelopes where the line represents the mean of the set of experiments and found that this evulsion length is not as sensitive or is not sensitive to the sea level rise rate or to the wave climate characteristics but it fundamentally is a geometric is geometrically controlled in the model. So this is in contrast to those backwater driven evulsions where here we find that the evolution link is geometrically and morphodynamically driven and so a recent paper and before the paper came out I had been thinking myself like we know that geometry in that model the results that I've shown you as an in-member is this even realistic and a paper just came out that called into question the validity of that model geometry. So I went about looking at rivers across the world and I used just a very simple way to look at flood plain elevations where I took the river center lines and I created a 15 kilometer buffer for these rivers for example and looked at what those flood plain elevations profiles would look like which is represented here at the distal I'll call them distal flood plain elevations and then I mapped the most recent major evolution sites on the profiles which are represented by the dash lines and then I can compare what the slopes of the flood plains are upstream and downstream of the river of the evolution node. I'm sorry. And so for the Mississippi River the upstream the average upstream slope is about six times higher than the slope downstream of the evolution node whereas for the Brahmaputra it's not quite as dramatic but it's about two and a half times higher the average background slope relative to the slope downstream of the evolution node. So while the the model geometry is potentially an in-member it looks like potentially in these settings the flood plain profiles might be diffusing more slowly than the river profiles like and wrap them. And also interestingly there's been there's really good agreement between the amount of in-channel aggregation required to trigger an evulsion and that evulsion length. So at the evulsion length scale. So in my work it's this for a super elevation ratio of point five it's evulsions tend to occur with other evulsion length scale tends to be about one backwater length than closer to two for a super elevation ratio of one. So that's without any backwater hydrodynamics. This recent modeling paper the variable discharge case so that's including the backwater hydrodynamics has a scaling that's very similar whereas for the constant discharge case the scaling is is way different than the results that we find from this model from my modeling work. And then also looking at some lab experiments the scaling is pretty similar. So that begs the question what are the differences in the models that are giving such similar scalings but for very different reasons. And so in Rafa you'll remember that as the channel per grades and evulsions and then the course shortens and steepest there's a decent amount of upstream channel degradation that will occur as a as a result of the channel shortening. And so the super elevation ratio the super elevation upstream of the evulsion node has been decreased because the channel is incised after an evulsion occurs. And if we think about it a little more simply to the where these evulsions can occur where super elevation is the critical super elevation has reached most quickly is limited by where sea level is. And that is because this LB is the backwater length is a characteristic or geometric characteristic geometry such that and for in our model because the river mouth is tied to a channel depth below sea level. This the riverbed will tend to intersect sea level at the backwater length. So what that means is that there the of where evulsions are going to occur in our model is tied to sea level. This is because aggregation is going to migrate upstream and that limits how far upstream an evulsion can occur because super elevation is migrating upstream. But the evulsions must also occur sufficiently far upstream such that the super elevation can develop in the first place. That occurs as the riverbed approaches sea level. So regardless of the initial model geometry evulsions are going to attend occur occur at a place that scales with the backwater length in our model. And this is different than the modeling work that recently came out last month in GRL where the delta reoccupies one of four different channels. The essentially after an evulsion occurs it's the river is going to pro grade from that evulsion node and the information from the discontinuity and channel slope is not going to be transmitted upstream. So the upstream channel degradation does not occur in the same way like it does not occur like it does in our model. And so because that super elevation is maintained over the repeated over repeated evulsions the the evulsion length grows higher in the constant discharge scenario whereas with variable discharge scenario the evulsion length tends to be tied closer to the river mouth in their modeling work. So this begs the question which of these two explanations is most relevant. So thinking about lab experiments the we would expect in these experiments that the channels are not always really well-defined their sheet flow outside of the channel so those floodplain elevation can keep aggrading at this a relatively same pace as the river the channel bed and so the hydrodynamic explanation may be more relevant or is potentially more relevant in these scenarios but we think about natural deltas or natural channels there's a range of floodplain connectivity. So especially when we think about anthropogenic modifications this degree of floodplain connectivity is very very different and so I'm going to leave that up there as an open question. I don't think we we don't we haven't sorted this out yet but it's important to understand how quickly the floodplain is aggrading relative to the channel bed. And so all of this has really important implications the evolution timing and length scales has important implications for things like restoration projects. So for example planning sediment diversions all of this information is super relevant and it also has important implications for things like interpreting fluvial stratigraphy because when and where evulsions that occur is going to impact the fluvial flux. How much sand is being delivered or what type of sediment are being delivered at the river mouth so that impacts what kind of deposits we would find. But really quickly I just want to put a plug in for you all we would love to have more couplings to this model because it will expand the type of questions that can be asked and then it can be done because it's been set up using the CSDMS infrastructure it can be done really easily using the BMI and RAFM is soon or imminently going to be a part of PMT and so just to throw out some ideas that there's all kinds of important things that could be included in the model to expand the scope of the questions that can be addressed. And so with that I just want to thank you and say that you can download the code from the site it's also part of the CSDMS repository and if you're interested in developing more couplings I'd love to talk to you and help you as much as I can thanks. Great, thanks Catherine I think actually the PMT already includes RAFM if I'm not mistaken. It's it's real close it's real close okay questions for Catherine we have time for a couple of questions I have one I'm just curious this is a little bit of a side note but do we have a sense of what it is that sets the critical super elevation ratio? It varies like orders of magnitude event so for the Mississippi there's data that show like it can be on the order of point one and for other scenario or other situations it can be up to three all kinds of things like agitation or the the levy strength and it's not totally clear there's a lot of a lot of work has gone into that and it's not fully flushed out yet other questions okay if not we'll move on to