 Next, we're going to start hearing about specific mitigation measures beginning with shrubs. And we'll hear from Dr. Burgess from Air Sciences Incorporated. Thanks everyone. We're kind of getting now to kind of a meet to what we're all talking about today is two kind of two new categories of potential best control. I know it's like I'm mostly going to be talking about Shrubland and after me John Baster will be talking about. I work for Air Sciences we're a contractor for UND and we're out of Portland. So just as John's presentation on my presentation we're going to be a little longer than the other presentations. So just a quick outline. I first want to do a little bit of background as to why the city is interested in pursuing shrubs specifically as a control measure. Then I kind of want to go into just some literature. We'll talk kind of about some Aeolian science fundamentals about dry land environments. So we'll talk about dust emission in general. We'll talk about specifically how vegetation controls dust emissions. And then I want to talk about modeling approaches. We're going to mostly focus on a model that was developed by one of our panelists Greg Oken. So we're thinking about using that as a potential method to kind of guide us in this dust control approach. So we'll kind of talk about the model. We'll talk about how we could possibly implement it in a real world, you know, a slide situation. And then kind of the end I kind of want to focus on a kind of pilot study we could do to kind of test to see if a Shrubland dust control measure would work. And what we need to do to make it work. And kind of getting to what has been already covered. The big thing to establish a dust control measure is, you know, we have to establish that shrubs are effective at controlling dust. We need some robust methodology to quantify the amount of reduction in PM-10 emissions that we are getting with that control method. So, you know, that's the big challenge here in a lot of your questions throughout the day. I think I'm pointing out exactly how do we estimate control efficiency. So coming up with a methodology to do that and then using that methodology to define criteria so we can look at an environment, look at a Shrubland community and estimate what type of control we would expect to get. And that gets to another point that was said earlier is that there is a need to know how effective an area is at controlling dust when it is not windy. So we need some method to do that when we don't actually have. So Shrubland as a dust control measure makes a lot of sense in Owens Lake. If you drive up Owens Valley you'll see that Shrubland is the dominant environment throughout the whole Owens Valley. Shrub and Shrubland in general stabilizes a lot of areas around the lake naturally, if you're ready. And they're also stabilized in a whole bunch of shoreline dune systems that surround the east side of the lake. In particular, two species, perry, saltbrush, and greasewood are two that are very common around the lake. And there's paper back in the 90s from the Dahlgren and all that found that they were actually very tolerant. And not just drought and high saline environments, but just general conditions specific to the Owens Lake flyouts. And we've actually seen in some managed vegetation areas that were intended for salt grass, we've seen these species sprout up just on their own. And just lastly, managed vegetation areas, which were initially identified as salt grass communities, but tend to be salt grass communities, they've been relatively successful and this is kind of an extension of that idea. Here's just a couple pictures of what these communities look like. This is a mature greasewood area on the northeast side of the lake. It might be kind of hard to see. This is a sparser greasewood community and you can see some salt grass in there as well. This is along the south side of the lake. And just for comparison, this is what's called a farm. This is one of the establishment of vegetation areas that's entirely modeled off salt grass. You can see the vegetation is much shorter. It's very extensive and obviously salt grass. So the big reason why we're interested in looking at shrubs specifically over or basically developing different methods for shrubs versus what is already established for managed vegetation is salt grass is very different than shrubs in many somewhat obvious ways. Shrubs are taller. They are more porous. They are less pliable under high winds and they have different aspect ratios. And for all these things, all these reasons, literature tells us that the ways in which they control dust change compared to salt grass. So we really need a different framework if we want to use and quantify dust control in shrub and apartments. Okay, so now just some general background on fundamentals of dust emission. So if you guys are fully aware of this, I apologize. But first thing is just kind of the mechanism what actually causes dust emission. We're perhaps what most people often assume and I think it's the most logical way that PM-10 emissions are emitted in dry land environments is what's called aerodynamic entrainment. And this is a process by which the wind exerts air in that drag on individual PM-10 particles and allows those particles to eventually be entrained and suspended. As it turns out, PM-10 sized particles are, basically there is very real or there's, the inner particle forces are strong enough that it takes a very high wind speed to get the sufficient shear stress to get the PM-10, to liberate PM-10 sized particles alone. And so for that reason, aerodynamic entrainment is actually by far a very, very, very small driver of PM-10 emissions in dry land environment. Two other mechanisms dominate and they have to do with the saltation of sand particles. So sand will start saltating at speeds at friction velocities and wind speeds far lower than what you will get with the PM-10 sized particle. And so as those particles start to saltate, they absorb momentum from the air and it's the impact of those larger sand grains with the ground surface that provides the energy to liberate the PM-10 sized particles. And there's kind of two different dynamics that can happen. One is depicted here with saltating large sand grains. Another case is where you can have larger aggregates of a lot of PM-10 particles and the impact will essentially break the aggregates. And so, I'm trying to think about, and the other point of this that's very important is that, you know, as PM-10 and also saltating particles start moving, they absorb the momentum from the wind. And so this absorption of momentum is a measure of essentially a lot of energy that's going into particle mobilization. And we have an expression for that commonly for friction velocity where you start. And this, the friction velocity or the downward fleximum momentum is physically manifested in the vertical wind profile. So this is kind of a depiction of this wind speed on the X, the vertical wind profile off the surface. So as we have a downward fleximum momentum through turbulence, we get the logarithmic, sorry, wind profile on the surface. And so as the surface becomes rougher, those large roughness, I guess the big thing says, as the surface absorbs momentum, that either goes into static roughness features like vegetation or rocks and also a lot of particles. And as we put larger roughness features on the surface, that absorbs more momentum. And the critical piece of that is, as we absorb as large roughness features absorb more momentum that modifies the shape of the logarithmic wind profile and it effectively decreases the wind speeds at the ground surface and therefore decreases the amount of energy that's available right at the surface where all the particles are. So decreases the momentum going into particle mobilization. So there's many models available to us to describe specifically how we relate a friction velocity to a horizontal flux of saltating sand and then the vertical flux of PM10 off the surface. In general, most of these models end up being a third to fourth hour relationship between the third power of the friction velocity scales with the saltation flux. And I have one thing I forgot to say, there's a term called the threshold velocity, so basically we have no saltation, no part of movement until we reach some specific friction velocity. Once we get to that, we have a third to fourth power increase in the saltation flux. So very rapid increase in the horizontal flux of saltating sand as the pressure velocity increases. As for PM10, generally it is often assumed that PM10 can scale with the horizontal sand flux and there's a lot of things on the ones like that kind of build that assumption into all the regulatory decisions. And we've seen a lot of talk today about sand flux and that's all kind of built on that assumption there. And yeah, of course, there's different models for both all these relationships, but these are just kind of the overall goals. So when we get to dust control mechanisms, the big thing here is that all of the mechanisms that have been tried that have been attempted, they're all relying on this assumption that sand saltation is the main driver of PM10 emissions in dry land environments. And therefore, if we can shut down the horizontal saltating sand flux, we shut down the PM10 emissions. And so there's kind of, in everything that we talked about today, there's three approaches to do this. Hummarine has to do with increasing the cohesion of the particles or otherwise preventing their erosion when they are hit by saltating particles. Air flow modification has to do with introducing roughness features, creating more turbulence and reducing that ground wind speed. And then trapping is a different process that's assuming, well, if we already have saltating particles, can we provide loci for those moving particles to deposit either in divots and holes like in tillage or in the leaves of vegetation? As for vegetation, there's generally three methods of vegetation uses to reduce dust. This is a figure from an old paper, and I'm going to be showing a lot of pictures from this Wolfman-Nicholing paper. Obviously, vegetation covers the surface in those places that we generally assume that we don't get emissions. It extracts momentum from the air that has to do with the same air flow modification that we've been talking about before. And then lastly, vegetation can trap particles, and it can do it in two ways. You can have vegetation actually hit, or saltating particles actually hit the vegetation and stop. Or in the lee of each vegetation element, we will have a wake. We'll have a region of slower moving air flow, and that is an opportunity for the saltation flux to decrease. And so we'll see deposition of saltating particles and vegetation lee. And so a lot of what we know, and specifically a lot of the background for Dr. Oakland's model, is really based on the characteristics of that wake or that region of slower moving air in the leaves of vegetation. So this is just an old schematic again that has come out of the same Wolfman-Nicholing paper to show you generally what air flow looks like when it flows around a shrub. You get slowing of wind of the shrub. Streamlines tend to converge around the tops and on the side. You have this region of substantially reduced mean wind speeds in the lee. If the vegetation is not very porous, you'll get a recirculating eddy kind of shown here. But if the vegetation is porous, you'll get a bleed flow through the vegetation. And so you won't get an eddy as much there, but you'll get a little smaller eddy. And then eventually that slow moving air of the wake essentially is eroded both from the top and from the sides. And the wind speeds in that wake will equilibrate with the upwind wind speeds over some distance. This figure isn't really to scale. We'll put more on that in a second. So in dryland environments where shrubs specifically are widely spaced, as it turns out, one of the most important factors is what is the spacing between these vegetation elements. So basically to what extent are the vegetation elements protecting areas by leaving them in their leaves. So this is yet another figure from this early Wolfman-Nicholing paper. This has been republished multiple times, but they've generally classified dryland environments and dust emissions into kind of three broad categories. On the top here is kind of the most emissive category. And this is a case where the spacing between the plants is such that the fast flow is able to return back to the surface at each wake. Each wake is able to totally dissipate before we get to the next plant. As you move to tighter spacing, they specify there's a term called wake-hinterplace flow, and that eventually skimming flow where theoretically all of our ground surface is sheltered somewhat by slow moving flow in the wake of some vegetation element upwind. I think this is just a single figure from a cool paper, Suthaburi et al. And just kind of giving you a pictorial example of what these three regimes look like. So this is a wind tunnel study. These are clumps of real grass. And then on the floor here they have the dissolve sand, but they color sand white here and then red. And so what they've done is they spun up this wind tunnel and looked at how that white sand deposited in the leaves of the vegetation here. So this is a picture that's actually taken looking down in this red area after they run the wind tunnel. So in this most widely spaced case, you can see how the vegetation, or basically you can see white sand depositing in the leaves of each one of these grass elements. In this wider case, you can see how the deposition mostly dissipates by the time it gets to the downwind plant. In this case, you can start to see those areas of deposition kind of start to connect a little bit and see those weights connecting. And then once you get to this point, they basically saw no, I'll say negligible sand motion at all. They had to identify individual grains that popped up, but more or less they had completely shut down any motion by the time you get to there. So they're suggesting these are three, ice layer roughness, weight interface, skinning foam. Okay, so now we're getting into models. So the whole idea why I want to talk about models is I think, given where things are in literature, we have a really great opportunity to use existing models in an applied way for estimating control efficiency. So the original approach to do this is called drag partitioning, and the logic for drag partitioning models is if we know our friction velocity, we can partition that momentum that actually went into mobilizing particles, and that which was absorbed due to turbulence from larger static roughness features. And if we can figure out what portion of friction velocity actually went into the particle mobilization, we can use one of those mass flux equations and estimate our mistrate. This type of approach, there's kind of two camps of how to do this, but in general the models are really difficult to implement. Well, they have issues. They don't necessarily agree with observations, especially when there's a lot of vegetation. They are difficult to implement. Practically they have trouble when vegetation gets tall. A lot of them rely on what's called lateral cover or frontal area index, which is basically the ratio, the cross-sectional area of all the plants get divided by the area that the plants reside on. And this assumes that the plants are homogenous, the spaced, which is not necessarily a good assumption. And so anyway, I'll stop bashing this approach. So, and to make Greg open, who is sitting with us, he used a different approach. And this model is, I think, much better for us to implement in a way like this. So what Dr. Oakland came up with is an idea that really kind of works off that third vegetation mechanism or the trapping mechanism that we talked about with vegetation. The idea is that we'll actually, we assume that we have a model where we can explicitly place vegetation on a landscape surface and we can say that we don't have emissions where the vegetation is and then each vegetation element essentially reduces the overall saltation flux simply by reducing the wind speed in its own wake and therefore reducing the saltation flux specifically in each plant's own wake. Okay, so just brief background on Greg's framework here. The model basically assumes that if we have a friction velocity, we can get that from a measured wind speed and an aerodynamic roughness length. We can drive the saltation flux using one of the mass flux equations that are available to us. This is just an example of one. If you remember, I was saying that in general, the saltation flux Q scales to the third power of U star, once U star is bigger than U star T. So if we have a U star, we can estimate a saltation flux for a given friction velocity and this. Right now, we're assuming no vegetation on the ground surface. To introduce vegetation, we can assume first no emissions occur where plants exist and then we'll reduce U star specifically in the leaves of vegetation and thus use the same equation to reduce the sand flux specifically in those spots in the leaves of vegetation and we'll look at the integrated effect on the saltation flux across the whole landscape. For this approach to work, what we need is some model that describes how an individual plant element will decrease the wind speed of the shear velocity immediately in their own way. This is an example that Greg Open presented in his paper. The data is from a sand fence. On the axis here, you're looking at the U star or the friction velocity in the wake of the plant normalized by the friction velocity in front of the plant and this is in distance downwind of the... Sorry, I keep saying plant. In this case, it's a sand fence. Distance downwind in meters divided by the height of the fence. So here you can see immediately when the shear stress is dropped by about 30% of what they were and then this returns back to normal within, in this case, 15 element heights or so. So once we have an equation for this and the cool thing is we can basically fit an empirical function to any data that we have and then we can use this same mass flux equation and estimate a mass flux at any spot of a given X over H distance from an upper plant. And so then for us to get an estimate of what the overall saltation flux is on a landscape all we need is a probability distribution of what are the odds that anyone points on this landscape is a certain distance away from the nearest upper plant. So we can prescribe this with a gamma distribution, for example, or we can use remote sensing and we can actually explicitly measure this for a real place. And so you have to get total flux. All we have to do is we can estimate the horizontal mass flux for all X over H and multiply that by the probability that that X over H exists on our landscape and just integrate that across all over X over H and we get our total mass flux. With this approach, there's been several papers that have started to think about how can we improve this approach and I guess understand more aspects of how the model works and so there's been a couple papers that have really started to hammer in on what the shapes of these vegetation wakes look like. There's been studies that have done both wind tunnel tests and field tests. This is a paper by Mayotol who instrumented several individual graft elements and then two types of shrubs in the Kalahari Desert and so they placed a line of anemometers downwind of the plant and then looked at the decrease in the wind speed over some period of time. So the blue here is showing you a decrease in the wind speed and the lee of each plant and you can see that there's a great deal of variability. All the downwind distance here again is scaled by the plant height but you can see there's a great deal of variability both in the amount of decrease in the wind speed and immediately of the plant and then also how far that wake extends back behind the plant. This is just some graphs showing you the exact same data and just in different forms. So now we're looking downwind distance x over h and then the y axis is the normalized wind speed or that's normalized by the upwind wind speed. So you can see similar graphs what you're seeing with that previous plot but immediately in the leaves of vegetation we're getting somewhere around a 70% reduction in wind speed and those return to normal. In these cases they found for certain vegetation 10 generally papers are saying somewhere between 7 to 15 plant element height. The cool thing from this mail paper is that they have started to get asked well what are the properties of various plants that could be affecting the shapes or the properties of these wakes. So on the right here they found a linear relationship between the optical property and the amount of reduction in the immediate wake of the plant. So basically saying the more porous, let me say it this way, the less porous the plant the greater the reduction of wind speed in the immediate wake which I think is pretty intuitive. Here they, this is a less solid relationship but there's something going on with the optical properties. Basically as the property increases the speed at which the wake recovers is actually longer and best hypotheses out there at least my understanding has to do with the size and the energy within the turbulent eddies when you get changes in the optical property. This is a very similar example in the wind tunnel. They took a bunch of, these are fake house plant or like plastic fake plants. They did basically the same thing. So instrumented these plants in wind tunnel, looked at normalized wind speeds in the lee and they tried to identify similar types of things. So here they found a similar relationship between the plant porosity and the decrease in wind speed in the wake and then immediately this plot is showing you more or less same thing. Here they kind of identified some other things that they or I think they, yeah, they fit one over X relationships to these and this is relating the aspect ratio of the plants to basically the speed at which it recovers and their hypothesis here is that if you have a very tall, narrow plant that erosion of the weight from the size will cause it to dissipate faster. So there's all of these, so these two papers I think are really interesting in shedding light on how these plant wakes work. But one thing that has been shown by Lee et al. Which is a paper that did a fairly thorough validation of the open framework overall. What this paper did was validate the open model against larger A65 sand catches and we'll talk more about that in a second, spread throughout the Western United States. And what they did was they showed the model really does a very good job and we don't even necessarily need to parameterize the wake properties of individual plants. And a very simple wake parameterization actually works very well. So what the study did was collected well there is a whole bunch of these BSD sand catchers. So these are instruments we have one set up in the back of the room if you want to go check it out later. It's basically just a box with a hole in it. So it's sand salt, it can bounce in that hole and collect and you just go back at some later time but I'm in there on a wind pane so theoretically they're always facing into the wind. So for this study of the 65 sites 13 we're actually in Owens Valley. For the Owens Valley case they were observed for six months or so in 2009 in Salt Rush, Greasewood and Salt Rush community. So very appropriate for what we're talking about. They, because of the large differences in the magnitude of the sand flux they observed they calculate air. They essentially took a log of all of their sand fluxes got a root and a square error of that and then unlocked them. So they defined this method as a relative error. But it's really quite remarkable that there are uncertainties when they compare to actual observations are quite around 200% which is very cool. And once they literally scale that it gets even better which is really, really cool. Yeah and so this approach is, this paper has been really thorough and I think when it comes to us about how do we develop this further our general thought is kind of approximating what they've done in this paper but do it kind of for a specific case for this application. Okay so almost done here. So gain back the objectives that we want to do for some work to kind of develop this idea. The big point here is to it's quite clear that if we have a very mature traveling environment that we can reduce emissions as much as needed but we do need a methodology that we can actually quantify that. So yeah we need a way to quantify control efficiency and then we need a way to then define specific landscape parameters like we need vegetation of a certain spacing and certain height that engineers at the city can use to design how they're going to implement that control strategy. So this is just kind of our idea for proposal and one thing we're really excited to hear from the whole panel is ideas on what we could do to do this better but we're more or less following methods that the adult did just kind of with a more specific eye on how to implement this in a real-world case. So we've kind of identified three different sites around the lake that have existing trouble and a variety of covers from something that is more or less fully controlled, perhaps skimming all the way to something that is a much more isolated traveling environment. We want to instrument them with all that we'll need to force and and run the OKA model with all the various parameterizations that we've kind of talked about and played with all those different problems. So we'll play around with at each site we want to we want to have met a meteorological sand flux observations and in addition to that we'll want to measure plant gap spacing. I'll talk about that in a minute. So we're going to measure the height and width brought the threshold velocity of the surface more specifics about just kind of our ideas here. In addition to getting just one wind speed we'd like to collect multiple heights so we can get an estimate of the roughness length. So we're thinking 642 and top of vegetation with a tower similar to this which we have implemented on the lake we can measure sand flux either with BF&E as done with Liadol or cox sand catchers are another type of sand catch that is less sophisticated and is used more widely on the lake but perhaps not as a thorough measurement. We have examples of both those instruments back on the back table there. Census have been talked about. These are also used on the lake. They allow us to get real-time data stream on salt-taving particles so we actually have a time resolved way to scale and see. They don't allow us to get an actual flux but they can at least see relatively when we're seeing salt-taving sand on the surface. We'd like to collect threshold velocity that's widely done on the lake using a device called a PI swirl and there's established methods to get a plant block for the plant gap spacing there's a whole bunch of papers that are developed from all sensing methods that we can use to estimate or measure that plant gap spacing explicitly. We can do that either with high-resolution UAV imagery and 3D structure using other structural motion or LiDAR. We can do that with other structures that have not only developed methods to identify the individual plants but then also build that gap distribution from that data set. When we do this, we get a much better full representation of the space in the plants for their arrangement. Some of these papers have started to work on can we actually get size or height so I guess probably obvious where I'm going to at this point but our thought is once we get all this data we'll be implementing the open model as I've kind of described using med station data all the in situ data that I've talked about we'd like to kind of test the parameter space in a very thorough manner as done with we at all and and kind of play around with implementing different weight curves brought forth by all these different papers and just kind of see what gives us the best fits to our field data to our sand catch data. One thing that hasn't been covered a lot in the literature is the effect that wind speed has on plant weights it's known that as wind speeds increase plants do become more streamlined so their weights do change but there's probably also changes in the fluid dynamics and things like that in a place like Owens Lake that happens to be a lot windier in a lot of other places in the west that's one question that we're particularly interested in and then again validates this again observations and so then the idea is for implementing this model appropriately the idea would be that we can then play around with full parameter space so define a whole bunch of different plant gap distributions and different plant height distributions throw those into the model and basically find out where our thresholds are to establish control efficiency and in this case to estimate control efficiency what we have to do is we have to run the model with no plants at all so assuming that everywhere that X of Rache is equivalent to infinity so basically take out that part of the model and use that as our denominator when calculating control efficiency once we go through this approach to you know identify what characteristics are needed of a specific plant community this gives us the information to this gives PDOP the information they need to determine if that is a feasible thing and I think the point I'm trying to say here is that I have how one would actually go about introducing shrubs in a specific environment and the reason why I'm not getting into that is that is a very location specific question and if we are to get into that the first question is what type of trouble and do we need what are the characteristics do we need fully mature shrubs how dense do they need to be once we establish that question we can give that information to engineers and they can evaluate whether that's feasible for any one specific spot so our hope from all of the panel is that you guys can evaluate these ideas and we're really looking forward to any feedback that you guys can provide of course that this is successful and we're able to push forward with this study the idea that this would form the basis for our information to the district in the future and lastly if there's any aspect of this talk that was too brief or you didn't pick up on we are going to be distributing our report within a week or so that basically covers everything that I talked about so if there's any other questions that might fill in for you in or I'll be available after the next talk too so thanks thank you so to keep on schedule let's move rapidly on to the next talk which is also from Air Sciences John Bannister tell us about shallow flooding wetness cover refinement test thanks for the opportunity to present my name is John Bannister I'm also with Air Sciences appreciate the opportunity to present and thank you everyone I'm also looking before like I did a good job with kind of foreshadowing a lot of what I'm going to talk about shallow flood control efficiency water use on the lake and that's all related to what I'm going to talk about so I'm going to talk about the shallow flood wetness curve refinement field test and also related soil and moisture effects on dust control my attention here is just kind of give a broad overview shallow flood control efficiency on the lake what's been done in the past and what we'd like to do going forward as with Evan we're going to be providing a full report with studies that have been cited literature that's been cited and a detailed study plan after the meeting so I'm not going to go too much into detail here but before any questions I'm happy to answer as you go I'm going to give a quick background of shallow flood on the lake I promise not to tread too much on ground, it's already been covered then talk about the shallow flood wetness curve refinement field test possibly the worst name that he's been playing in the work acronym that was conducted in 2015-2016 then from there talk about soil and moisture in shallow flood areas in general and how that might be investigated further and then finally get into a brief overview of a proposed field study that we'd like to implement going forward so the objectives of this field study are going to be twofold number one is to perform the wetness curve refinement field test as it's allowed in this step the purpose of this test we're going to get into in more detail is to refine the control efficiency curve used to establish required wetness covers for shallow flood areas and to achieve this is to observe various saturated wetness coverages and determine control efficiency achieved under those variable wetness coverages related to that and this stems from observations we've made in previous studies is to perform a separate but concurrent study on the effects of soil and moisture for dust control on a land lake it's possible to establish methods to reliably characterize soil and moisture over a large dust control area and then relate those spatial temporal patterns of soil and moisture to a sand watch control efficiency. So shallow flooding has been talked about a bit already it's by far the most widely used dust control measure on a land lake with about 60% of the control fly up right around 30 square miles currently under some form of shallow flood dust control and that can be pond sprinklers or laterals overland flow I watched that earlier that I think the last year the lakes used something like 60,000 acre feet of water per year all of that water was used in maintaining shallow flood areas basically when you consider I think the city of Los Angeles annual water demand is something like 500,000 acre feet per year so Owens Lake they put 12% of the water demand for Los Angeles is used in Owens Lake shallow flooding so let's just give some perspective on how important it is given the state of water in the western U.S. and how we think that's going to change in the future how important it is to make sure that shallow flood areas in Owens Lake are being operated as efficiently as possible there's no need or no benefit to using more water for dust control reasons there's no need to use more water as necessary as long as the requirements for dust control are met there's other things to consider but for this talk I'm just going to be talking about dust control shallow flood dust control in a nutshell just applies sufficient water across an area to reduce PM-10 emissions below target level so some key terms that I'll go through briefly you've heard before sand flux is just a horizontal particle motion across the supply surface as I mentioned studies have shown that on Owens Lake the vertical PM-10 flux off an area is proportional to the horizontal sand flux in that area so because of that relationship it makes sense to use horizontal sand flux as an index for vertical PM-10 emissions off of an area because you can instrument an area specifically measure the sand flux in that area and to get an idea of how much PM-10 that particular area might be producing sand flux is measured it's recorded in units of math for area over time so for instance grams for centimeter squared per hour and on the lake it's typically measured by a time result combination from caulk sand catches for the sand mass and senses for particle hits over time control efficiency is a relative reduction in PM-10 emissions resulting from a dust control measure with that relationship of sand flux to PM-10 control efficiency is often calculated by a reduction in sand flux in an area in particular for shallow flood areas the control efficiency is simply one minus the ratio of sand flux in the control area over some reference sand flux and we'll get into where those reference sand fluxes might come from here in a second and in wetness cover is defined in the SIP as the percentage of an area is substantially evenly distributed standing water or surface saturated soil so that's a key clause right there they have to be standing water or surface saturated soil soils with less water than that moist soils or damp soils are not considered control for compliance purposes in shallow flood areas only saturated or standing water so typically the wetness cover estimates for Owens Lake shallow flood areas have been done by the analysis of images the types of images and analysis methods have changed over time as technology changes or for the particular application that's been done so to all these ones aircraft initially and then more recently satellite specifically Landsat satellite and then visible spectrum has been used to determine what is covered and now the standard we use is short band 6 and Landsat 8 review of shallow flood as of now on the lake the shallow flood areas can kind of be put in two broad categories the first category is the original 2003 depth control areas they're comprised just under 24 miles of the lake they have a target control efficiency so they need to meet control efficiency of 99% and to meet that the requirement is they have 75% saturated water wetness cover the second area smaller just over 9 square miles are the 2006 supplemental depth control areas those again have a target control efficiency of 99% but they are only required to meet 72% wetness cover and I'll get to the difference there in a second the supplemental depth control area includes a very small portion that are reduced compliance efficiency areas so areas that need to be flooded to a level to achieve a control efficiency less than 90% how were these wetness covers determined the 2003 depth control areas the original shallow flood depth control areas Dr. Holder mentioned previously the flood irrigation project what I'll be talking about here I'm actually not aware of the results of the south flood irrigation project I'll be talking about the north flood irrigation project and those results lead directly to the current shallow flood control efficiency curve in the north flood irrigation project the control efficiency was calculated by comparing area average sand fluxes in dry areas compared to adjacent wet areas the wetness cover was measured by the manual analysis and digitization of visible spectrum aerial photographs the study was conducted in the northeast portion of the Owens Lake Playa that north sand sheet that was mentioned earlier the study was performed between approximately 1993 and 1995 I believe the data points that were used to develop the control efficiency curve here came from six high wind events all in 1994 so for these wind events the control efficiency in the dry area was compared to control efficiency in the wet area the observed wetness cover in the wet area was determined using the aerial photographs and these data points were plotted percent wet cover to control efficiency and then this curve was developed relating wetness cover to control efficiency for shallow flood areas for the 2006 supplemental dust control area 2016 step I believe it's the first year in 2008 that instead of just saying 99% control at 75% wetness cover these areas were allowed to achieve a target control efficiency at a wetness cover determined by what became known as the shallow flood control efficiency curve this red line right here that appears in the sift this red line the shallow control efficiency curve set of the data points that were developed in the north sift step so this curve then determined for the 2006 supplemental dust control areas what required wetness cover is necessary the vast majority of that area requires 99% control efficiency which turns out to be 72% wetness cover in 2008 so there was a question you know as the lake changes are these wetness covers as efficient as they can be as they optimize LEDWP was curious about that commissioned Air Sciences to perform a retrospective analysis of operating shallow flood areas in 2008 this was done by looking at areas under current shallow flood operation taking control efficiencies in those areas by measured sand flux compare that measured sand flux to available historical values as control measures have gone in then looking at the wetness cover that was observed in those areas during normal compliance over flights landside over flights and just taking the calculate control efficiency comparing it to the observed wetness cover and seeing where we land so this data I'm presenting here this full report will be provided in the technical packet these graphs represent screen data based on the basically the quality of shallow flood areas with highly separated wet and dry areas with large dry patches where it's determined to not be representative or areas with a lot of managed vegetation or not managed vegetation a lot of natural vegetation so the full data will be available in the report but regardless not being conclusive it's definitely interesting to look at the wetness cover the wetness cover is below the required 75% or 72% so if nothing else is indicated this is something worth studying further in the 2006 settle-in agreement that was then carried into the 2008-2016 steps it was then allowed the city to have the option to conduct field testing to refine the wetness cover requirements to achieve 9% control efficiency in shallow flood areas so this clause in the settlement agreement is the basis for conducting the shallow flood wetness curve refining test that the city has the right to do a field study to see if that curve can be refined so the first design study to utilize this clause was performed in 2015-16 the curve refining study as I said the first design study was basically taking naturally operated areas and evaluating those and the study plan was developed in collaboration between DWP and Great Basin with the intent being that the study layout would as well as possible kind of follow the concept used in the fifth study having a untreated dry area adjacent to treatment areas instead of just being measured what they naturally occurred at they were designed to hopefully achieve various wetness covers sand flux was measured under natural wind events obviously so over the course of the season sand flux was monitored continuously along with met data and the wetness cover estimates were performed by high resolution square imaging for the reason I will get into shortly. This is showing T26 the area where the test data came out of that so the most complete data but the study also includes areas of T29 and T10 and T13 I know the death control areas are all named T number right? Jen mentioned earlier that the main line has turnouts, 35 turnouts so the number that associated with the death control area is kind of the nearest main line turnouts and a rule of thumb is lower numbers tend to be towards the south and as you go up around the east side of the lake they get higher so T26 is kind of in the northeast portion of the lake not adjacent to but in the general area of the north that study occurred so the preliminary results from this study are shown here again we have a lot of high control efficiencies for wetness covers that were much lower than the 75% originally required the data in this plot was filtered for this presentation to kind of be analogous to the type of wind events that were observed in the north tip study so wind events with continuous hours greater than 21 miles per hour although it shows the preliminary results I don't want to gloss over the fact that this study had a lot of challenges as a first design study for this there were a lot of what we call lessons learned so some of the problems that came up number one I would say was wetness cover in the study area and the issues involved with wetness cover I think are two fold there were challenges in operating these areas the specific wetness covers that were lower than typical shallow flight weather and not only were they lower than typical shallow flood wetness covers but we were attempting to hit wetness covers exactly in a traditional shallow flood area the area can be oversaturated you can allow water to run off as long as you're over the 75% compliance limit that's great no one that's wonderful in this if we ran every area higher than normal we have a bunch of high wetness covers it would probably have great control efficiencies but wouldn't give us really any information that we didn't already have so attempting to run these areas at very exact lower wetness covers was a challenge besides the operating challenges I think there are also challenges in estimating wetness cover in these areas related to a few things the size of the wet features in these areas being sprinkler irrigated areas the drying cycles that were observed in these areas and finally the presence of transition areas or transition wetness areas going from wet to dry and then second the question came out of control efficiency calculations and how do low sand fluxes in the untreated area affect your final control efficiency calculations right so first I'll touch on the challenges with wetness cover and I'll do a brief digression here on how shortwave infrared is used to estimate wetness in shallow flood areas areas with standing or saturated water absorb light in the shortwave infrared spectrum so the compliance measure for Owens Lake is to use shortwave infrared images look at the reflectance of those images and then determine wet and dry areas based on the shortwave infrared reflectance you can see here is an example we can currently take in images one in the visible spectrum, one in the shortwave infrared these highlighted areas in the visible spectrum to my eyes look pretty similar to everything around that right but when you look at it in the shortwave infrared you can see the dark areas pop up showing high absorption of shortwave infrared presence of water is determined using shortwave infrared for shallow flood currently is using what's known colloquially as a teeter point which is simply another way of threshold value threshold reflectance value is determined pixels in the image which have less reflectance than the teeter point or wet considered wet areas with more reflectance than the teeter point are considered dry this is something that's been used, methods been used at least as long as I've been involved in shallow flood compliance every shortwave infrared sensor that's used for compliance measurement a teeter point is developed for that sensor, the most recent one, the Landsat AOLI sensor the teeter point was developed by Kenneth McGuire of the Desert Research Institute in the study for the district so using this method basically a binary classification of every tectonic image is either wet or dry right into the resolution of the image and how that's affected by the feature size you're trying to measure the Landsat has about a 30 meter pixel so 30 meters on a side and it gives you one square reflectance value for that pixel the sprinklers in these areas that were used for wetting have a throw radius of about 10 meters so they're relatively small compared to Landsat AOLI especially if you consider that entire throw radius of the sprinkler is not going to be evenly saturated water and everything outside is perfectly dry there's going to be very wet area in the center and maybe we're out the edges it's a complex lay of the ground so if you look at two concurrently taken images for this study because there were these concerns about the size of the Landsat AOLI it was decided to use a plane based swear sensor that was flown by company called SPECTEER out of Reno, Nevada they're able to fly over the lake and provide us with short wave infrared images of about a 4 meter pixel size there were calibrations done to make sure that SPECTEER's images would be comparable to Landsat images, calibrations unknown areas so we can pair them one to one here is we can do this do a concurrent flyover but in this case to illustrate this point or to investigate this point we have the swear SPECTEER plane fly over the area at the same time we use a Landsat with acquiring an image to take two concurrent images of the same area compare what we get from those two images Landsat with a 30 meter pixel estimated this area this highlighted area here to be 29% wet plane based image just here was estimated at 47% wet and when you zoom in you can see the difference Landsat obviously is not picking up some of the wetness in here just by the average over that 30 meter pixel the average reflectance is going to come in at a point higher than the swear SPECTEER point classifying that area as dry whereas with smaller pixels you have much finer resolution differentiating between the pixels and classifying wet areas much more finely the second problem or challenge that we had in this study was the dynamic nature of these areas we suspected that these areas were going through wetting and drying cycles more so than traditional shallow flood areas for that reason I mentioned earlier sprinkler shallow flood areas that are in normal shallow flood compliance are typically overwetted, have a lot more standing water have a lot more surface runoff whereas these areas were trying to hit exactly not over wet them at all and when you do that you end up with a lot more transition area not saturated, not dry and that area tends to dry out quicker so here's three images to investigate this effect we had SPECTEER fly over the lake in June of 2016 the first flight occurred immediately after the sprinklers were shut off in the area after about an hour and a half the next flight so the wetness now goes from 51% wet right after the sprinklers were shut down to just 20% wet an hour and a half later to 15% three hours later so with this kind of dynamic drying effect you can imagine when you're relying on a snapshot image to estimate wetness in an area when you've got this dynamic wet dry the wetness estimate you get is going to be highly dependent on when you took that image and no matter how much you try to take the footage at the same point or the same point in the day or the calories of the sprinklers there's always going to be some uncertainty on where you're hitting on this curve so for the study the sprinklers were typically operated in two or three separate one hour sets during daylight hours and as I mentioned these challenges each resolution the drying cycle they're exacerbated in the study we believe because we're trying to get these exact wetnesses so these aren't necessarily problems you'd see in sprinkler shallow flood areas that are under normal compliance but it did occur in the study so as you can imagine with these challenges I've just outlined the wetness cover estimates we got in these study years were highly variable a single month lease where an image was used to track wetness coverage that decision was made based on the assumption and previous experience that shallow flood areas had been fairly stable over time they didn't go to these wetting and drying areas sorry wetting and drying cycles that obviously proved to not be the case and a month in retrospect was far far too long between wetness estimates but that's what we had so the single monthly swear image was used to track the wetness coverage and then when a wind event occurred the wetness coverage for that wind event is assigned according to the nearest swear wetness estimate so if a swear image was taken one day and then nine days later a wind event occurred the wetness coverage that is assigned to that wind event encapsulating control efficiency to wetness coverage was taken for that swear image nine days earlier not ideal the second point I mentioned in regards to control efficiency calculations and control sorry sand flux in the untreated areas I just wanted to illustrate here I don't think anyone needs me to do the math but I just wanted to drive home the obvious point that the calculated control efficiency is not simply determined by the sand flux in your controlled area your treatment area but also by the sand flux you see in your reference area so sand fluxes that remain the same in the controlled area under a wind event depending on what kind of reference sand flux you get, what kind of sand flux you see in the untreated area your control efficiencies can vary greatly especially when you get to very low natural sand fluxes in your untreated area a very low natural sand flux in your untreated area you could have sand flux in your treated areas but still come up with control efficiency that's bad to give kind of an example in the north fifth study for the events that they use to calculate the original shallow control efficiency curve the reference sand fluxes so the sand fluxes they found in their dry areas over the area averaged about 16.1 grams per centimeter squared per hour during the wind events the sand fluxes we saw during the wind events during the shallow control curve refinement study averaged 9.4 and most importantly we yielded two distributions here there was a large number of low sand fluxes in the untreated area during the curve refinement study so given all that I still think it's important to even with all these challenges there were still high control efficiencies observed at low wetness covers again, not conclusive proof that this is too high but definitely an indication that there's something there that bears investigation especially when you consider what I just mentioned about control efficiency and sand flux in untreated areas these very low control efficiencies every control efficiency 90% of what's observed is associated with a very low sand flux in the untreated area so for whatever reason the untreated dry area was not as much as we would expect it had low sand flux for some of these events and as a result we can have a very low sand flux in the treated areas and get low control efficiencies so the final part that I haven't gotten to yet because I think it bears a little bit deeper dive into the transition areas in these steady areas with these targeted wetness covers there was a lot of ground that couldn't be clothed by the saturated but also probably couldn't be clothed by the dry you'd either have very wet soils underneath very thin dry crust or large areas that don't pass saturated tests it's a field test for saturated soil something called a tap test it's basically going out tapping with a staff or your shoe to see free water come up that's considered saturated so obviously a lot of these areas would not see free water under that test but definitely wouldn't classify these as dry so how much of these areas there are, how they affect control efficiencies there's all a question I think bears further investigation and understanding these effects is going to lead to a greater understanding of how shallow flood areas control that, especially spring that's just a field test to kind of begin investigating how prevalent these areas were we performed we had field crews walk probably not the best, you can't really see but there's lines here that represent several transects that field crews walked while a swear image was being taken and when the crew was walking these transects they would be recording how much the areas they recorded as dry how much they recorded as moist or damp and how much they recorded as saturated the swear image was going over at the same time and then we just performed the tater point wet dry analysis along those same transects in the swear image here's the result for each transect of each bar the blue here represents the portion of that transect it was recorded by the field crew as saturated ground the green represents the proportion of that transect that was recorded as transition or moist ground and then the red line there is the wetness cover determines the long mat transect by the swear wet dry tater point analysis so the results are interesting right all of these transects have a large proportion of transition area moist ground or damp ground the swear in some cases didn't pick up very much at all of that transition ground in some cases picked up quite a bit of it in some cases it's unclear so I think the interplay between how does moist soil control dust or health control dust or sand flocks how does our estimating methods deal with these areas, how does it see them does it see them goes into better understanding how these areas are working and without understanding these issues I think we're working with liners on when it comes to really getting a handle on what's going on in some of these shallow flutters really briefly I said it would be high level but moist soil and how does that contribute to dust control in theory here's the dust control and the mechanics of end diagram in this diagram soil and moisture falls solidly within the armoring section it prevents particle motion initiation but it doesn't provide any trapping that you would see with ponding for instance it doesn't modify the air flow so in general the presence of soil and moisture less than saturated it's going to increase the cohesion in soil due to the surface tension in the water between the particles which in turn increases the erosion threshold friction wind velocity which then obviously reduces sand motion and saltation so this is not a new concept rising this as well established that this mechanism occurs but a question is does this apply to Owens Lake? Owens Lake is a unique place, soils are unique is this something that's going to hold in the environment we're working in to try to answer that question or at least approach the answer to that question LADWP commissioned a study a wind tunnel study to look at it in a more controlled environment this study was conducted at the Trent University Trent Environmental Wind Tunnel in Peterborough, Trent University Peterborough, Ontario, Canada this study was chosen this is probably the premier Aeolian Science Wind Tunnel in North America it's completely environmentally controlled they have a lot of experience doing particle motion and erosion studies this study was at Owens Lake soil from Owens Lake as a matter of fact as well as other areas was collected shipped up to Canada they took this soil the premise was they would put it to a certain moisture content put it in a wind tunnel fully instrumented for PM-10 emissions saltation, particle motion and then run it under varying wind speeds and varying environmental conditions to see what happens as far as particle motion goes the test cycles were as follows the material was put in the wind tunnel it was then subjected to four different test cycles a test cycle consisting of three 5 minute wind intervals of increasing speed so 5 minutes under 6 meters per second wind 5 minutes under 9 meters and then 5 minutes under 13.5 repeated then allowed to drive for 12 hours in the tunnel under wind two cycles repeated two more times and during all this time the soil was wetted initially to variable moisture contents and then throughout this entire process just allowed to dry naturally not disturbed until the final cycle because during these three cycles obviously drying occurs in a crust form on the top of the soil this four cycle that crust was broken up by they tried various methods the best one I think ends up being a forward hit with a hammer fracture in the surface so the results of this study first we wanted to get an idea of how emissive these soils were make sure that we're going to see the kind of emissions you would expect we know these soils are emissive let's make sure that's happening in the wind tunnel so the soil was dried to a very low moisture content and then completely pulverized it was placed in the wind tunnel and in a single test cycle of ramped wind speeds was executed first 5 meters per second 6, 9 and 13 the y-axis here is the cumulative particle count this is about 10 to the fourth there so as you would expect as the wind speeds increased the particle counts increased until at 30 meters per second the reason this line cuts off is because the instrument saturated so incredibly emissive the lab team was not happy a big mess but at least we proved that these soils are emissive so they had the testing cycles and here I'm providing an example multiple cycles were done on different soils with different starting moisture content under different relative humidities but as an example here is a test executed on the same soil that was done for this test and I'd like to give you an idea of the scale of this plot compared to this one and as you can see this number is 5 so we had single digit particle counts coming off of this soil through 3 cycles then any crosses and form was broken and the highest number here is 10 so orders of magnitude even after extensive drying so again another indication that these moist soils are providing control in excess of what they've been given credit for so to bring all this together and get towards the wrap up here we're proposing a new field setting similar in some ways to the original shallow flood wetness curve refining field test with the intention of still fulfilling that purpose of refining that shallow flood control efficiency curve with the addition of adding in additional methods and instrumentation to also investigate the extent and effect of moist soil in these areas so and again this will be provided this is just a real high level overview this study will again be conducted in T26 it's about 160 acres this area here under a control untreated dry area and then a 40% target moisture cover and then a 60% target wetness cover the rest of T26 will continue to be operated as shallow flood area 75% control the area will be surrounded by TM10 monitors, MET stations video cameras sorry we'll still camera the district has understandable concerns this is Keeler right here populated area the district has concerns about TM10 missions from this dry area reaching Keeler so the purpose of these is to make sure and track as best we can what is actually coming off this area if this area is contributing to TM10 at the shoreline here's a close up of kind of a preliminary play out of the study areas you've got the control area these red lines as you can see them are sand fencing to prevent sand ocean from the control area if there is any into the study areas to kind of block that off the areas are going to be aligned with the predominant north south winds the target wetness covers are again going to be a system of sprinklers left capped and opened in a pattern to achieve the target wetness covers we think and I'll get into it in a second with improved operations and monitoring we can do a better job of hitting those target wetness covers and keeping them there and then an extensive monitoring network for sand flux and now soil moisture content and water application through flow meters is going to be sprinkled out of the line so I'd like to talk a little bit because I think the biggest challenge in the first study and one we'd like to do our best to address is wetness control in these areas we're still shooting for that target wetness without shooting too far over or letting it drop too far down so there's still going to be some dynamic effect in these areas and that's inevitable but hopefully it can be minimized or tracked better some operational adjustments now this area is it either is or will be soon on SCADA control which will allow for better tracking and better control of the sprinkler on schedule possibly allowing for fewer shorter sprinkler sets instead of those long ones then with the prolonged drying in between maybe get more shorter sets to keep it more consistent right and then the modern balance model for T26 has been developed mostly just for operational use for tracking changes in evaporation natural precipitation and then calibrated with monitoring results to give them idea of how operational changes are affecting the wetness cover in the area and second developing monitoring measures that we hope can combine remote sensing that you saw moisture sensors with a goal providing an estimated ground condition whenever a wind event might occur regardless of how we sense these areas when you're only using remote sensing you're always going to have a limit on how many images you can take you can't have a satellite over there all the time taking images so unfortunately I wish you could but those wind events are going to occur whenever they're going to occur we want to, as best we can at least estimate the conditions on the ground when a wind event occurs not have to rely on an image that was taken days or a week beforehand The Institute of Soil and Moisture Sensors there is a concern on Owens Lake that's always brought up with Soil and Moisture Sensors the salinity of the soil and how well or can these instruments work in soil with the resulting we've been doing some testing in the lab and in the field on a 5T Soil and Moisture Sensor that my colleague has been working on and can answer questions on but there's been lab calibrations done for soil from T26 and in field testing in T26 it shows even in these soils with their salinity you can develop calibration curves and you can see changes in gravimetric water content via soil conductivity in these areas so there's still more work to be done to prove out these methods but I think they're promising and we're confident that SWIR imaging obviously is going to still be a big part of the study because we want to meet those requirements to the Shellsley curve recline and study but in addition to doing the teeter point wet dry analysis we'd like to expand the investigation into the continuous SWIR value and whether there's information to be gained by looking not just at whether the SWIR reflections fall on either side of a single value but looking at the value as a continuum and will that give us some insight maybe into these transition areas right especially in conjunction with in place soil and moisture sensors that tell us what moisture the soil is at the time and then finally another promising aspect we think is synthetic aperture radar or SWIR SWIR images are available from Sentinel-1 satellite platform they occur about two times a week SWIR has been investigated already as a method for measuring soil moisture can detect soil moisture under the surface about two to three centimeters day or night acquisition that provides an 18 meter resolution image so methods we hope and again this is a concept we're working with and we're going to bring this here we appreciate input on how this method can be refined or improved but we want to combine these soil and moisture sensors that provide a continuous measure on the ground at any time combine those with remote sensing imagery to develop a model the instantaneous what's the condition on the ground so in general the concept would be to identify reference points on the remote sensing images where the changes and the reflectance values of those points correlate to general shifts in the image reflectance install a network of soil and moisture sensors across the study areas of these reference points and then develop a relationship between sensor moisture content and image reflectance and then develop a model relating sensor moisture content to an image reflectance profile so when no image is available you can kind of estimate what soil profile might be based on the values you're getting from your in place soil and moisture sensors in high concepts right if we've got a soil and moisture content sensor here it's got some area of influence that we're going to define around it right when we have an image we have a soil moisture content that can then be related to an anticipated reflectance value at that point based on analysis of previous images so we've got a sensor reflectance that relates somewhere to the distribution of reflectances observed in this area of influence over the course of many images we can determine that this distribution of swear reflectance in this area or SAR reflectance remains pretty similar to an image to image perhaps an offset in the sensor image could indicate an offset in the distribution of swear reflectances or SAR reflectances around that sensor as I said it's in general the direction we're moving and input on how to best achieve this is well appreciated what we're requesting and I appreciate taking the time this has been a challenging study but I think it's an interesting one I think it's important and overall we're looking for a way to execute this as well as possible so we've collected in obviously a review and comments on our field study proposal specifically what's the best way to conduct this curve refinement field test this is an allowance for DWP and CIP some of the interest we're selling what's the best way to do that how can we do that in a way that's going to provide information that will be applicable and we can use with confidence to adjust that curve and the method of control efficiency calculations and if low fluxes are observed in the untreated area how to deal with those is there a de minimis level to be filtered is there another way perhaps use a reference value to determine control efficiency how can that be done kind of related to that is if soil moisture dust control if soil moisture does prove to be an important factor in dust control in these shallow flood areas what's the best way to implement that in the future how could that be monitored how could that be tracked is that something that can be implemented on a field scale and then suggestions that I just talked about for providing that uninterrupted estimate between square images of ground conditions both for saturated wetness cover and soil moisture growth I appreciate it, thank you very much for questions and break and that is from Dr. Holder again and it is the district recommendations for the panel well you'll be very glad to hear that I only have just a few slides so I'll take very long in our approach to alternate dust control measure development for your consideration is quite a bit different from what was presented by Evan John so basically I wanted to sort of refocus things back on the purpose of the panel as said in the 2014 stipulated judgment and then the initial task that you're supposed to be addressing so as you can see on the slide there the purpose of the panel is for the OSAP to evaluate and assess and provide ongoing advice on the reduction of airborne dust in the valley review scientific and technical issues related to the research development and implementation of waterless and low water use vacuum and other approaches to reduce dust in the owns valley and specifically in the stipulated judgment it actually wrote out the initial task so that's what you're working on now and was already talked about it quite a bit but it's to evaluate the effectiveness of alternate dust control measures and we are slightly different and instead of actually having specific dust control measures that we're interested in having you evaluate we've kind of divided it into three main categories and how they can be implemented on the lake so they're listed over on the right side of the slide so the first one would be for use in temporary dust control measure areas and I've got some examples coming up here also for control measure implementation and environmentally sensitive areas where you don't need to have vacuum so maybe some kind of non vacuum measure that could be used that would be something that could be implemented in those areas that would be considerate of the resources there and their protection and then also in off lake areas so off of owns lake bed so for the temporary dust control measures I have divided that up into sort of two main categories one would be sources that are located within the total dust control area that is has been ordered for dust control on own lake an example might be transition area where they're trying to transition from one vacuum measure to another vacuum measure so there's pretty strict requirements there they're written into the SIP and the board order and all the laws that are applicable that only allow a certain amount of areas to be transitioned at any one time and then there's also areas that might be come in method due to breakdowns and variances that might be allowed by our hearing board so you might need a temporary dust control measure in some of those areas like the jet crash that happened back in 2009 or whenever it was there's also been breakdowns in the pipeline and some of the turnouts that have large areas dry out and become missive and cause violations that might be suitable for temporary dust control measures while the repairs are being done but then also there's areas that might need additional control within the dust control area so like in managed bedge grow out areas where you're not getting the control or the cover that you need within an area this would allow maybe additional grow out time if you could implement a temporary dust control measure in some of those areas and then sources outside of the total dust control area on the light bed might be areas that have opened up but have not been ordered yet so some of the areas that Phil showing in the map that shows all the red school designs that shows all the areas that have been observed to be a missive if some of those areas actually get you know go through the whole process of the dust ID model and then they're determined to cause violations of the shoreline it could potentially be ordered but if we can implement controls in those areas or identify them before it went through that whole process then you could be able to implement something either on a temporary basis if they're infrequent sources or on a left and back home level because they hadn't been ordered yet and then also the off lake sources with the areas outside of the total dust control area if you look at the other two categories we've got control measures for environmentally sensitive areas those are becoming much more prominent and more important on the lake over the course of time as dust control has been implemented on the light bed and they're something that we're very concerned about so there's quite a bit of area now that have been avoided to protect the resources and some of those areas may ultimately have to have control at some level implemented within them and some sort of alternate dust control measure could be appropriate for some of those sensitive areas either for protection of cultural resources or paleontological resources or some kind of habitat value or something like that and then there's also potentially environmentally sensitive areas that would be located in future dust control or maybe you could plan ahead of time of avoiding them and then try to develop a measure if you already have some kind of measure available that you could implement those within the dust control order rather than having to go through the whole process that we're going through now and as we've said before there are significant sources of dust above shoreline the regulatory shoreline and some of those are going to have to be addressed at some point we're currently doing the dust control project in the Healer dunes but there are some other off-light sources that may have to have dust control implemented enough and some kind of alternate dust control measure would be a clarifying question what do you mean by above in that case above an elevation higher in elevation thank you that's the end of my presentation I think I was left with my five minutes thank you Dr. Holder I'm going to propose the agenda says we take a break we come back for questions and so I'm going to suggest that we go to questions right now and then have a hard target of four o'clock for starting up our final group of presentations so that we don't lose our presenters or cause them to deal with even heavier LA traffic as they make their way to wherever they're going next so in that way the panel can control how long a break they have by the number of questions the panel asks so I will with that open it up for questions and Dr. Venkatram they call me Venky Venky yes very interesting presentation from Dr. Burgess and Sharps are being used are they being used right now as a means of control switch on volume because somebody had mentioned the fact that they die very quickly because as soon as the roots reach the starline that was never for trees they have no requirement for them now the species are a lot of the species that have been tested and they have pretty deep root systems a lot deeper than that so why not consider fences or something that doesn't require water to achieve what you want to achieve with sharps I can't speak to why I have not had experience in the issues that Sam fences or the issues that have been faced with Sam fences is there anyone back there maybe Jaime Mutin Roll was a Sam fence project and the fence project that was limited to a small BPA and that was a permanent Sam fence installation for a lot of regulatory issues with environmental impacts potentially to migrating birds and other types of vegetation but yeah outside I don't know if the district has an issue with it but there might be issues with fish and wildlife or that doesn't believe that Sam fencing enhances public trust or the the word I'm looking for habitat value out there the closest thing to sharps would be the poorest roughness elements in Dr. Holbert can talk about that well the sharps and the keyword dunes are also like that and we're using sharps so that is recognized as an appropriate control mechanism there are also shrubs that are in the 42 species that are approved for catchment there's quite a few shrubs in there in terms of Sam fences I think the main constraint there is that to get the control efficiency level you would need quite a few days of Sam fence and hasn't been supported by the landowner at this point okay I'll note that we have probably questions that will take us till four negating the committee's break so I would encourage you then if you need a biological break please go ahead and take it at your convenience next is Greg I'm really glad that you talked about the temporal and spatial resolution questions with images because it's I think that explains probably a lot of the frustration that Anne talked about specifically in terms of you see one thing in the data but your so really this is a question about what exists in the documents that exist there's the possibility to change how you might do new fathoms but does the possibility exist to for the district to advise how you evaluate the second in other words how much flexibility does the district have to change its monitoring? flexibility exists in the regulatory documents to change how performance criteria are evaluated depending on the criteria some of those procedures are more specific in the regulatory documents but all of them reference authority to the air pollution control officer to approve different methods of evaluation and in general the district is always open to better and simpler ways to evaluate performance criteria these drones was cameras on relatively high altitude you can do it every week drone flights at high elevation he's done more work on that but that's a great idea this is someone who maybe to inject a little bit into that conversation someone who's tried to get permission to fly drones particularly near military air spaces is that a feasibility? is that possible in the Owens Lake region? so we have worked with drones on Owens Lake we have not implemented a SWEAR sensor at this point there is no commercial option for mounting a SWEAR sensor drone so you have to engineer that yourself with a last SWEAR camera which is totally doable yeah this is Scott let me jump in I'll take a little exception to that it's possible it's done pretty routinely my question there might be the times you might want to sample it might be blowing like the beat Jesus and it's not a good idea to fly drones I'm afraid they work well on a nice sunny afternoon let's put it that way you may one point the military operations on the lake are a significant problem there are two military flight practice lines straight over the lake so they fly routinely under 200 feet fast enough to scare you a lot and that has caused issues it doesn't mean that you can't operate but it is an issue to consider the wind is also a problem and there have been other reasons why the city hasn't pursued drones as a that is something that we're exploring patine patine do we have another the district has utilized slier on fixed wing aircraft during times when land-fed imagery is unavailable for long periods of time there's over 30 square miles of shallow flooding back on this implemented so we're the scaling issue utilizing drones to give a very elegant talk but have you considered if done in detail to estimate the sand flux or the dust flux have you looked at that as a function of particle size which then I think I would just jump to John in terms of the low emission rates efficiency if you use a number count based efficiency calculation you would get much more accurate results that goes back to your theory is the efficiency or function of particle size and then back out of the no we have not we have not looked into that at all the tricky thing with that is that the particle size distributions within the soils on the lake change anywhere you are on the lake and that is certainly for a research estimation yeah I haven't looked into specific mass flux equations used for different particle particle size distributions and whatnot so yeah that would be really great to get some more talks on and then good talking devices available too instead of your sand flux yeah so the senses that we have back there they are they are very much in perfect instruments and trying to get real time sand flux observations with the actual mass flux estimate in real times is still a very real challenge on a lot of honestly problems sure actually you mentioned John about combining SAR data and sensor data and one thing I would say is and I wasn't 100% sure you're considering this but maybe something to consider is you can measure these things as much as you want but unless you have a good number on evaporation and evapotranspiration and temperature then your model will never be able to capture what is happening on the ground the second thing I'm not looking to answer that is what measures are put in place to deal with evaporation and evapotranspiration you are using the shallow flooding because temperature can be quite high and there's a lot of evaporation I wonder how much benefit to getting and one other question can sort of be answered together is is there any interest or effort or possibility of turning the shallow flooding area to prime pond gradually by introducing different water quality I can address maybe partly address your evaporation question I think Jennifer Wong no longer here she's probably the best person to answer that but LEDWP operation staff on the lake is in charge of basically maintaining compliance in the shallow flood areas so they operate those areas based on their experience and the procedures they have so they'll change the water application based on climate conditions as they observe them I guess Jennifer if I speak better if there's a four more way they do that but as far as I know a lot of it is experience based and where is this water going do we need to up the water in this area a little bit more we're a little dry let's put some more water on there now I think it's very much at the moment more of an art than a science so just to sort of share some of my thoughts on your answer that if you are looking to find a model that would give you some way of depth to be seen where everything is going and how you can not cross the boundaries you don't want to cross by going below 75% or not if you don't have the right numbers on it in terms of transportation and temperature then it's going to be very very difficult to do that just by having and I'm hoping you're not thinking okay we will have all the data sets we'll do some machine learning if someone comes then we'll see if it's going to come out because for these natural processes we can see so much and machine learning on that if you don't have the right numbers on the natural like the climate numbers or things that really really actually when any of that is very very difficult to do a prediction just based on having a historical data on how long what percentage you'll be getting based on that just because you're combining SAR so you're now going to get there right just to clarify are you talking about making a prediction for future wetness based on the understanding was that you'll be going to have to build a model based on the data that you have from SAR and sensors to help you to understand the fluctuation right well that might be something we work towards in the future but as of now I think our intent is more to be able to estimate the ground conditions at a moment not where they're going to go in the future even if you just want to estimate just simulate and be able to estimate and calibrate your models and be able to estimate at any given time if you don't have those numbers you'll constantly overlap okay thank you yeah I mean we'll definitely be recording those I mean meteorological data will be there so some studies looking at that on the next like looking at for example people who have grass in their house and the water and water it doesn't matter how much of water it is you're in a severe drought it cannot maintain it vegetation it's very relevant to what you're talking about here but it's like a different kind of a study so my point is you don't have to look into sort of those climatic things it's going to be very difficult to have in life. Thank you. On to our final two questions we have it from first from Scott then held in the room and then Scott on the line yeah I just want to make a comment to you John trying to measure soil moisture and how it affects emissivity or the erodeability of the surface you're not going to do it with any of the instruments that you're planning on using this is a millimeter scale problem with soil moisture and in that campillary break occurs less than two centimeters in the surface I've seen it rain like gang clusters in the morning water standing in the furrows and sand blowing over the tops of the beds and thus being emitted by 11 o'clock in the morning so probably the only way that you're going to be able to get a good estimate of the surface water content is by infrared thermometer of the surface and take a look at the evaporation stage. Okay so a final question for this session from Scott on the line. Yeah thanks I'll stick on the soil moisture and the evaporation question a little bit just thinking about this I recognize that the interest is to reduce the amount of water being used but I would look carefully at A how much efficiency you expect to gain before too much is done because it's a very costly concept but also the fact that once you start irrigating in a patchy network like that you do tend to as you're familiar with the complimentary or Boucher hypothesis and this goes back to some of the things that I've already heard on the phone but these are things that can actually enhance evaporation because you essentially have wet islands surrounded by dry islands so in the long run you may end up evaporating more water than you had originally done with a fully wedded surface that is far cooler as was just pointed out so this is a complex this is not an easy problem and there's some pretty severe complexities about the scale at which you wet the ground so it's not easy and it's not straightforward necessarily you will significantly decrease evaporation and I guess the question will be how much evaporation do you expect to reduce that's an important question to go into this kind of studies what do you expect to see okay so thank you for that comment and I thank all the speakers for their presentations this afternoon