From DailyDoseOfWeirdNews.com, I'm Darren Marlar and this is your Daily Dose of Weird News. Before we dive into the weirdness, I want to congratulate Adriel Railton, she's last month's winner from the Marlar Sheet giveaway. Adriel will be receiving a Weird Darkness t-shirt and a coffee mug. This month I'm giving away a Daily Dose of Weird News t-shirt and coffee mug, so everybody who signs up for my newsletter, the Marlar Sheet is automatically registered to win, and you can sign up now at DailyDoseOfWeirdNews.com. Is there a smell that we can all agree is just horrible? Yes, a British survey found the smell of a wet dog is something we can do without.   Now, TV is reconsidering a reboot of All In The Family and The Jepressons. How is this possible with the snowflakes that are living in this country right now? They're offended by everything and they immediately pick it when their feelings are hurt. The Jepressons and All In The Family are two of the most racist shows ever to be on American television. Are you going to remove all the offensive stuff? You can't. If you take away everything that would be considered offensive in today's world from these shows, all you would have left are the opening theme songs and then the ending credits. You've heard about Nordstrom's $425 pre-muddied jeans, right? Well, Reebok is poking fun at it with its $425 pre-sweat-stained sweatshirt. You don't even want to know what Pampers is now selling.  That ruling came as part of a pet custody battle in a divorce case, and the wife wants the couple's two dogs, Kenya and Willow, to live with her, with visitation privileges for her ex. The husband, described by the wife as a cat person, disagrees. So the matter ended up in the courtroom of Judge Richard Danuluk, who was outraged at the couple for wasting scarce judicial resources. During this decision, he wrote that where Kenya and Willow should live would be like arbitrating the family butter knives. Am I to make an order that the other party have limited access to those knives for 1.5 hours per week to butter his or her toast? Dogs are wonderful creatures, he writes, but after all is said and done, a dog is a dog. But for now, the dogs are staying with the wife's parents. In a Solomon-like move, Danuluk warns that failing to settle the matter could result in the dogs being sold and the proceeds split. You know, maybe the dog can file for emancipation and be rid of these two jerks. A burglar was caught on camera breaking into a Long Island salad shop, eating nearly a dozen bananas and passing out on the floor. The robber dropped his driver's license before stumbling out of the sexy salad at around 1.45 in the morning. I know you're not supposed to assume, but I'm guessing there might be a very slight chance with the story that alcohol may have been involved. Just a guess. The Sun reports Americans spend a whopping six hours a day gossiping. That's the findings of an independent national poll from all 50 states about the time they spend dishing dirt. Not surprisingly, women gossip more than men, logging in six and a half hours daily talking to friends about subjects from their husbands to celebrities to other friends, but men aren't exactly silent. The guys put in an average of five and a half hours. Their subjects were most likely to be their bosses, coworkers, and sports figures. The Sun is reporting this, though. Is it the Sonic Gossip Magazine? A new study out says that teens who use smartphones and tablets at least five hours a day increase their chances of obesity by 43%. Apparently all those food picks really pack on the pounds. A recent study indicates that America is facing a critical shortage on clowns. The report found that membership at the country's largest trade organizations for the jokesters has plunged over the past decade. Officials say membership in other clown organizations has also plummeted. How is this distressing news, though? I would think a world with fewer clowns would be much less distressing. But then my first clown experience was from Stephen King, so... A NASA scientist is warning that the Earth is woefully unprepared for a surprise comet or asteroid strike. Well, of course we're not prepared. You just said it's a surprise! Johnny Depp made a surprise appearance at Disneyland this week, heading to the Pirates of the Caribbean ride dressed as Captain Jack Sparrow, a Depp-surprised guest as they rode by in their boats. It kind of backfired though, because some parents kept saying, �Hey, look kids! It's Katelyn Jenner!� Kim Kardashian is now on a Mexican vacation. And I repeat my often asked question, �Vacation from what?� A 12-year-old boy attempting to drive across Australia by himself drove more than 800 miles before police caught up with him. Apparently it takes a long time for Australian parents to realize that their kids are missing or their cars have been stolen. A woman gave birth to a baby while visiting a zoo in Nebraska. Ironically, the giraffes were watching her. In Bath Township, Ohio, 20-year-old Joseph Murphy called 911 and said that he needed a police dog. Well, when the dispatcher asked why, Murphy said, �She stole heroin from me!� So yeah, the police showed up and body cameras show officers questioning Murphy. On the video, Murphy can be heard explaining that a woman stole money from him, but the officers wanted to know about the heroin that he mentioned on the emergency call. A short time later, officers were surprised when Murphy pulled a brown, waxy substance from his pants. We'll let you guess what that was. Police seized the substance and a felony drug possession charge is expected after test results are returned from Ohio Bureau of Criminal Investigation. Incidentally, Murphy was also arrested for DUI after crashing a Mercedes with a blood alcohol level at 0.121. Murphy also made national headlines on New Year�s Day, accused of urinating on a Florida troopers leg during a disorderly conduct arrest on a Disney property. This is your brain on drugs. Any questions? The Turkish government has decided to block Wikipedia. So there are now millions of Turkish citizens walking around trying to remember the name of that actress in the breakfast club. What was her name again? In Goodyear, Arizona, 49-year-old Daryl Ingram was charged with child abuse because police say he used a stun gun on his son multiple times. Why? The 11-year-old boy didn't do his homework. Yeah, I'm thinking there might be better ways to motivate your kid to do his homework. The Pittsburgh Pirates have cut the league's first Lithuanian player and replaced him with the first African. And the shouts of racism begin in 3, 2, 1. In a Silicon Valley parking lot, 41-year-old Jason Sylvain tackled a security robot, allegedly drunk at the time. Him that is, not the robot. Mountain View Police Department spokesperson Katie Nelson said an employee for Nightscope detained Sylvain before officers got to the scene. The spokesperson added, when we arrived, we met with Sylvain and, as we were speaking with him, he appeared confused, had red, glassy eyes and a strong odor of alcohol emitted from him. Locals weren't apparently eager to defend a fellow human for standing up to our robot overlords. Mountain View resident Eamon Callan said, I think this is a pretty pathetic incident.  Getting sloppy drunk and tackling robots is no way to go through life, son. Cashmere has shut down all social networks for a month. That might work in Cashmere, but in this country it is a sure-fire way to get people to finally leave the house and begin looting. Martha Stewart has opened up an internet wine business. Apparently she came up with the perfect recipe using the toilet while in prison. In an interview with Reuters on his first 100 days in office, President Trump says he misses driving, feels as if he is in a cocoon and is surprised at how hard the job is. Surprised at how hard his job is? We are in big trouble, people. Apparently many Americans experience supreme difficulty deciding between Applebee's or iHop. Fortunately, Detroit has a solution. The first-ever combination iHop-slash-Applebee's-restaurant is opening later this year. Alright, so what do we call this? AppleHop? No, no, no. Even better, iHopblebee's. Research shows people who swear more have bigger vocabularies than those who opt for an expletive free life. In fact, those who were more confident using swear words were also more articulate in other areas of language use. And ironically, their expanded vocabulary only included words with four letters. The Barler House store has just been updated. You can find t-shirts, mugs, phone cases, tumblers, audiobooks and more all on one page. Check it out at DailyDoseOfWeirdNews.com. When you take Tylenol, the main ingredient is acetaminophen, and it does more than relieve your pain. The popular medication also reduces your empathy. That's how much you're able to understand the physical and social pain and suffering that others feel.  Brad Pitt says he has been alcohol-free for six months now. Am I wrong to interpret that as requiring lots of alcohol to stay married to Angelina Jolie? Doctors have always assumed that both human ears were basically the same, but a UCLA study of babies may change a lot of assumptions about the way the brain works because it found that the right ear is better at picking up speech-like sounds while the left ear is better at processing music. So if one ear is for talking and the other is for music, what ear does rap go into? In Australia, family managed to save the life of a lizard they found at the bottom of their pool by performing CPR on it. As a thank you, the lizard is saving them 15% or more on car insurance. If you signed up for the Marlar Sheet, it's free and everybody who subscribes is automatically entered into monthly drawings for prizes. For May 2017, I'm giving away a Daily Dose of Weird News T-shirt and mug combo, and you can sign up for the Marlar Sheet free at DailyDoseOfWeirdNews.com. American Airlines is planning to decrease the front-to-back space between some of its economy class seats by another two inches. Okay, won't that make it much more of a tight squeeze when you pummel somebody with a baby stroller and drag them off the plane? A woman in Georgia walked into her apartment's bathroom and found a python slithering up the wall. Gwendolyn Howard says she called the apartment complex for help. They told her to file a work order. What? This isn't a leaky faucet. I have a python climbing up the wall! Twitter lit up with support for the Minnesota teen that didn't have a date for the prom, so she took her acceptance letter to Harvard as her date. I wish these supportive people had been around when I went to my prom with my copy of The Hobbit. Most people don't know that back in 1912, Hellman's mayonnaise was manufactured in England. In fact, the Titanic was carrying 12,000 jars of the condiment scheduled for delivery in Veracuse, Mexico, which was to be the next port of call for the great ship after New York. The people of Mexico who were crazy about the stuff were eagerly awaiting delivery and were almost inconsolable at the loss of the mayonnaise. So much so, in fact, they declared a national day of mourning, which they still observe today. It's known, of course, as Cinco de Mayo. Okay, that's not actual news, but hey, it's a comedy show. How about a TV comeback for the show Roseanne? Roseanne Parr, John Goodman and Sarah Gilbert have all signed on for an eight-episode reunion series. If you're wondering about the other daughter, Becky, well, it doesn't really matter. We know that role is interchangeable with any blonde actress anyway. President Trump said that he's open to meeting with North Korea's leader Kim Jong-un. Trump says of the potential meeting, I would be honored to do it. Trump and Kim will gleefully exclaim at the same time, Dude, where did you get that great haircut? A woman is suing Qatar Airlines for spilling coffee on her during a January flight. Upon hearing her threat while still on the plane, Qatar Airlines went all united on her and dragged her out of the plane after hitting her with a baby stroller. Federal agents just seized 300 pounds of yak meat that was illegally smuggled into JFK airport. I'm imagining there's not a lot of yak meat smugglers on LinkedIn. The hacker claims to have stolen the newest season of Netflix's hit, Orange is the New Black. The hacker is demanding Netflix pay a ransom or else. Good luck with that, pal. I'm going to assume the folks at Netflix are smart enough to back up their shows on an external hard drive. A 92-year-old Canadian man says the secret to staying young is going to raves. Then again, he might have said not going to graves. You know what? He was mumbling. It was hard to tell. In Japan, a 24-carat solid gold Darth Vader mask is going on the auction block. It could go for as much as $1.4 million. They're hoping to raise enough money to help the Empire rebuild the Death Star. Again. A report says more animals died on United Airlines flights in 2016 than any other airline. On the plus side, it does make them easier to drag off. After a year-long search, Kelly Rippa has finally chosen her co-host, Ryan Seacrest. Way to go, Kelly. You have somehow found a way to hire someone even more past their relevancy than you. A groom in China could not convince his parents and friends that his bride-to-be was the right woman for him, so when they all refused to come to the wedding, the groom hired 200 fake guests to fill his side of the ceremony venue. Even worse, all the wedding gifts they gave were cheap knockoffs. The world's oldest man, who claimed to be 146 years old, has died in Indonesia. Sadly, just when he was finally able to afford retirement. A former FBI translator working in Detroit secretly flew to Syria three years ago when she married an Islamic State terrorist leader that she was supposed to be investigating. The bride and groom promised to love, honor, and cherish each other until suicide-bombing death do them part. The Trump administration is planning to roll back nutrition standards for school meals. In fact, Twinkies will now count as a vegetable.  It's not the little heart on her left cheek or the floral decoration around her neck or even the writing above her left eyebrow or whatever that's going on with her forehead that have people so stunned. Nope, it's more the fact that her eyeballs have been tattooed. Varn was taken into custody along with Jonathan Mikhail Robinson on charges of kidnapping, armed robbery, and property damage. It's alleged that she mugged a man taking his mobile phone and money before inviting him into her home.  Austria is trying to figure out a way to tax Google searches. No, that's not a joke. Austria is trying to figure out a way to tax Google searches. Are we getting a little over-terrorist paranoid in America? Obviously, we always want to err on the side of caution, but Colgate University went on lockdown and students were ordered to remain in place for four hours Monday night while police investigated reports of a gunman on the upstate New York campus. There was a guy with a gun, alright, but it was a student using a glue gun for an art project. What do you expect from a university named after toothpaste? ABC is going to bring back the gong show with Mike Myers hosting. Okay, if he says shawing or groovy baby even once, I'm going to gong him and change the channel. A robotic drill could be the future of surgery and could help cut the time of a routine brain operation from two hours to two and a half minutes. Developers believe the computer-driven tool, which works like Google Maps, could play a pivotal role in future surgical procedures. Because this is exactly what we want, complex life and death brain surgery done as fast as possible. I've got a tea time in 15 minutes, so let's do this! Police in California were forced to taser a man who got into a heated argument with his wife. The argument began when the man failed to notice that she had her hair done. As a husband, let me say that would do it. The study says it is more energizing to walk stairs than drink caffeine. See that's why I double down and only go to Starbucks on the second floor. A former Russian Defense Minister spokesperson says the Russians have been secretly planting nuclear bombs off America's coast so that they can be detonated, causing huge tidal waves that will destroy American cities. Wait a minute, is this a news report or is this a leaked premise for the next 007 movie? A New Jersey florist was arrested for stealing flowers from a cemetery. She claimed that she was simply tidying up the cemetery. Which is why she was wearing her usual nighttime gardening ski mask. If you liked this video, please give it a thumbs up and be sure to subscribe if you want to see more. And click that little bell next to the subscribe button to be notified when I post new videos. And if you're already an official Weirdo, please share this video with your friends. Also, be sure to sign up for the Marlar Sheet if you're not already signed up. Everybody who has registered is automatically entered to win a monthly prize drawing and for May of 2017 I'm giving away a Daily Dose of Weird News T-Shirt and Mug Combo. You can sign up for the Marlar Sheet newsletter, free at DailyDoseOfWeirdNews.com. For more weird news anytime, visit DailyDoseOfWeirdNews.com. I'm Darren Marlar and I'll see you next time, Weirdos.


UN Secretary-General Antonio Guterres hinted today that he was deeply concerned about hunger becoming widespread as the one Ukraine threatened food security in different parts of the world. Speaking alongside Australia's Chancellor and Foreign Minister in Vienna, Guterres also talks were going on to evacuate more civilians from conflict zones in Ukraine. He expressed confidence that more evacuations will happen in the future. However, he played down the prospect of peace talks over Ukraine happening anytime soon. We are in contact with the Austrian, with the Ukrainian and the Russian authorities in order to multiply the initiatives similar to this. These contacts are going on. Our policy was, if you remember, we only announced each of the evacuations after it was completed. If you want to solve a problem, you need to deal with those that cause the problem or that can solve the problem. So it makes full sense to talk to the leader of the Russian Federation. It makes full sense to talk to any other relevant actors in the present crisis.


Okay, we're coming in this like next plus or minus or like our plus a little bit. We have an exciting new part of the CSD mass meeting. And this is a combination of the spring school that we just taught in a week before the CSD mass meeting. We had 22 participants here and focused, we're focused on cyber training skills, basic GitHub, basic Python, learning about these tools that CSD mass puts together and the community puts together. And one of the things that people then do as part of this course is team projects where they try to apply what they just learned and like take advantage of tools that are already there. All of them are scientists. They come with different backgrounds and different topical interests. And you'll see that through today, but we'll have like each team up on stage and like show us how far they got in their team projects. The idea is that these are contained projects. So we tried to like beforehand define or like as a team they defined an idea of like this would be something that students could use as an to introduce a concept or like a fairly like exploratory first step, but they are presented as notebooks or teaching modules that later on people in the community can use. There are five different groups. The first group consists of Alex Marina, Bunti and Jed. And they all were interested in long-term landscape evolution or tectonic processes were more deeper processes and river incision, etc. They have a modular course set up. So they'll like each walk you through like one of the like a sort of process modules that they have made available through a new notebook. So I'll hand it to Alex. There is enough time for people to ask questions. So like be aware like we'll have time for questions and for like interactions. Hi, everyone. I'm Alex. I'm a final year PhD student at Imperial College. So just to introduce what we what we're sort of aiming for and what we've produced. So we're basically aiming to produce like a teaching resource to allow students to develop some intuition on that long-term landscape evolution. Okay. So the main thing we're interested in allowing students to understand where the impacts on different erosional parameters you might use. So erodibility diffusivity, spatial patterns of uplift and how that impacts long-term steady state landscape, the impact of our graphic rainfall and then using the new little layers package. The impact of differential rock strength and then how some of those things might be recorded in provenance records. So just to sort of give everyone a primer. We are a sort of the model set up where assuming it's just a square grid of 100 by 100 plummeters and all of the model of the fume diffusivity according to just a standard diffusion equation and then an effective effective landscape evolution model. So just like a primer and then I'll hand over to Jed. We're going to talk about erosional parameters. Yeah, so kind of as the first step and this is also just as much for us to kind of get a grasp of the right range of variable values to use in the model. We ran the same model with all the same parameters except for changing between a range of five different diffusivities and KSP. So for rock erodibility, just start looking at how the kind of base land lab model of again fastcape eroder and linear diffusion results in different landscapes. So we can see here those different combinations of erodibility and diffusivity and how that and the main parameter that we extracted. Drainage density just for seeing again, building kind of an intuitive sense of how these change the overall form of the landscape so can see moving from very high erodibility and low diffusivity where we get much more dissected landscape landscapes with high drainage density and then moving into very high diffusivity with lower erodibility where we get more subdued landscapes and overall lower relief over the course of and these were all run for the same number of time steps in the model. And I think I will then turn it over to. Okay, so. As Alex said, uplift rate is one of the factor control the evolution of the surface right and. Different assumptions result in different circuits landscape evolution and in this model I show some of the basic assumptions of uplift rate when first we think about like the constant uplift rates and then the second binary when they are to uplift rate different at the top and at the bottom and in the third case when we use the linear functions like uplift rate is related to like the linear function with the y axis and the fourth one don't share when I assume the public functions between uplift rate and y axis and the last one, the more fancy one when we adopt the components in land lab called normal fault to control the uplift and you can see that when we use different assumptions, the result is different topography and also different drainage area and inside the models of student can. Try to use different assumption and understand like the results and okay. So the next component was the our graphic precipitation component so here we wanted to kind of explore how to incorporate different precipitation patterns into the land lab framework so in order to do that you need to add a water flux into the model. That then will go into a discharge component taken by the fast keep a rotor and algorithm. So, and we device for scenarios so the first one is just a binary one where the top have has a higher precipitation than the, the lower half of the grid. Then we did a linear components where it's just linear with respect to the y axis values. And following on that we have as the orographic kind of more orographic scenarios so the simple case here is just the precipitation scales with the with the elevation values, they're normalized to fit into the range of precipitation values that we would expect. And I took Boulder as the reference place because we're in Boulder. And then the final one which was the most complicated one was them.  So I didn't want to do that. So what can I do. I was like, okay, well, I need to include some sort of proportionality with the elevation. Then I took the maximum point of any north-south transect and decided that every point north of that maximum value would would have a higher precipitation value that all the points south of the maximum point at each north-south transect. And then I assumed that the wind that it would be a system created by a wind coming from the north. So it would, the north-worth side would get more precipitation at the southern side. And it, it's basis assumptions is not great model, but it kind of fits the what we would expect, you know, the northern side having more precipitation and scales with precipitation with elevation and then the southern side having less precipitation. So it's just kind of encouraging students as well to create their own modules and to show that it's easy enough to make new functions and to integrate those functions into the land lab kind of main framework. And just as like a final synthesis chapter, we, oh, yeah, we also use the litholayers package to explore the impact of, if you sort of are uplifting lithological layers with different strengths, the impact that might have on the total sediment flux. And then by tracking what rocks are being eroded, you can also sort of generate the synthetic provenance record through time. So I'll just skip over that quickly and just sort of describe the, there's a final synthesis chapter where we're trying to put all this together to sort of mimic a real landscape. So here we have both like a domal uplift stratigraphically led rocks of different strengths and orographic precipitation. And we explore how that evolved through time. So here we just have the rock strength broadly increasing with depth, but a little bit of randomness to simulate sort of natural variability. And then we just uplift like an anticline. And then just going through time, we can see different rock types being exposed to the core and topography evolving. And because of the orographic effect, it's sort of asymmetrical. And then gradually we build a more complex landscape using different rock strength, variable rainfall, yeah, all in land lab. So the idea is that by the end of the course a student is able to build sort of quite complex things having built it up module by module. So yeah, happy to take any questions. Very, very nice work. So just out of curiosity, are we these these vertical things that we see stick out in the south? Are they then the next step? Are they diffused away or what? So actually with if we haven't quite worked out how to integrate the little lab with the fusion, because the you'd need to have that basically like a particle tracking system with the little package of the perfectly like like grid based and you can't assume a lateral transport. So actually, this isn't technically this doesn't use diffusion in this particular model. But yeah, in the real world, they would diffuse out and soften at the time. I guess they're like equivalent to the flat lines. Thanks.  So the URL here, if you want to use them, they need a bit of polishing. So we're sequences, the teams like totally choose their own topics, right? We sequence them a little bit in a source to sync order. This was very arbitrary, but like that's how I propose to do it. So the next group focus on upland landscapes and was looking at like susceptibility for landslides. And they're going to show their codes that is for landslides and failures. So this was team landslides susceptibility. Anybody who is going to speak for them. Scott, you're the fires, fires and landslides, or are you then still combining the fires and landslides. No. So this is Joe, Nick, Sebastian and Emily is over there. And David. Yes. So hi, I'm Sebastian. We are very excited to present. Oh, sorry. I'm Sebastian. We are very excited to present our very small project. Well, we all know that climate change has a great impact on the occurrence and intensity of extreme events. So for instance, fires, and also extreme rainfall events and landslide. And so we were very curious to see how the combined effect of fires, extreme fires and extreme rainfall events and landslide would result. So we made explosives by combining land lab components in the smaller notebook. Everybody I'm Nick. So, as Sebastian said, we were curious about how wild finder wildfires changing soil, cohesive cohesiveness, cohesivity, and increasing erodibility would impact the occurrence and size of landslides and then as sediment flux as well. So we used the, well we used a stochastic fire generator created by another CSDMS team that we modified for our model here. And as well as the highlands bedrock landslider component and the space sediment transportation component. So here we're just initializing some of our steps and creating the burner function. So the way the fire generator works is choosing a random grid cell from the DM that we load and a random fire radius, and then any cell or grid cell that falls within that radius has its erodibility boosted by a set factor. So here we initialize our components and use the BMI topography component to load a 30 meter DM of the Oregon coast range which we chose because it's a well studied area, a lot of parameters that we could find and include in our model, as opposed to just choosing something. So this is the DM that we started with. You can see there's a well developed drainage area with some pretty steep slopes.  So we're using a time step of one year and simulating 10 years of fires with a high, a higher currents interval of the fires at about one year. Our soil properties. We had an initial soil depth of half a meter for the coastal range. And then our boundary conditions allow for flow out of the sides of the models. That was a choice we made to simplify the model process. So here is our fire function running as you can see, um, seven fires occur over the 10 year simulation, and it ran for about a minute and a half so fairly quickly on this DM. And here is a plot of the fire locations and the erodibility change after each fire so each fire centered around or at one of the centers of the circles, and then basically multiplies the erodibility of that cell. Or all of all the cells within the fire radius. This is the sediment flux after the fires. As you can see it mostly follows the major drainage pattern up to the north, but there are a few going out to the sides here. And then after this we run the bedrock landslider and space components to sort of move some sediment around and see how that will affect our sediment flux. In this image, we have areas of deposition in green to blue and areas of landslide occurrence in the warmer colors. And as you can see, we've had quite a few different events move some soil around. And then again, we plot our sediment flux and it looks very similar to our first plot but some of the channels are a little more defined and if you were to review the scale bar here, you can see that there's a lot more sediment being mobilized after the landslides have occurred. So that's what we modeled this model did not take into account recovery of vegetation did not take into account recovery of vegetation due to, you know, that would increase soil cohesivity or sort of a proxy for erodibility over time. And we didn't have the model recreate more soil because one it's over a 10 year period which is not really a time scale for bedrock to become soil. And I think that covered everything. Thank you. Questions. For the fire function you have a perfect circle kind of where the impact is right. What you know is, can the fire function take into account wind direction or kind of topographic boundaries that it counts. Sometimes fires are stopped by riches or anything. Can you tell a little bit more about that. So, I'm sure that could be incorporated but our model was very simplistic in the location of fire. Just to stand next to you Dan. Just from my understanding is it so that the material that's deposited by the landslide that you give that a different erodibility and that's why you you increase the sediment flux. Yes, so the erodibility is increased by the fire and basically modifies the parameters that the bedrock landslider uses to move sediment. We didn't change the erodibility of landslided material, but increasing the erodibility increases the number of landslides. Okay. So this component is made to simulate deep seated landslides, but we found it more user friendly and fit our needs better for our shallow seated landslide so we used a soil depth of half a meter. And the tool can do deeper seats landslides, but we didn't utilize it in that way. Just to follow up on Danos question is the mechanism that increases the flux farther downstream from the landslides the fact that you put a lot of material in the upper parts of the creek profile and steep in it or. Yes, so basically we've moved extra material into the stream channels, which we can see here on the green depositional areas are largely at the bottoms of the slopes, which is increased soil thickness in the channels which the space component moves to the outlet. So it's, it's not transport limited, but limited by how much stuff is there in the creek bed. I don't think we took that into account. Thank you. So the fire model do you have a propagation of the fire from the source of the, I mean the initial ignition point. No, we just set a radius and have everything within the radius increase in erodibility by a set factor. It's kind of interesting how like everybody's minds, like straight away goes through like all these like more complex add on like functionality. Right, like, I think I literally when we set up the team project and told people, I told them like we in the course itself there's only like 10 hours or so that you like literally doing team projects but there was a weekend and people crammed through a weekend a little bit more and I think So, this group is also like more in upland environment and basically they started as like abrupt event was a really large group of people and we thought of some of the same processes but with a different application. And so it's my name is Archana I'm a third year PhD student at Montclair State in New Jersey. And today our group is going to be talking about using the land lab toolkit to simulate sediment flux after force fires.  Fire season is lengthened due to warmer springs, longer dryer season and burn area which then impacts the soil and vegetation making a dryer. There is less fire, but the events that happen are larger and more catastrophic and we also know that sediment flux increases after fire events. And so for our project we wanted to ask this question and figure out how might climate change in two different scenarios, a medium emission scenario and in extreme emission scenario. How would that sort of general scenario effects sediment flux after force fires. Hello everyone I'm Scott the anima 25th year PhD student at the University of Nevada. And so our, our kind of methods here are we're going to set up a GitHub repository as we've kind of looked at here we're not going to go into the details just we have it in a presentation format, but that all this stuff we can learn in this past week and a half. As our China said we're going to have two precipitation scenarios and we're really just simulating for 100 years to kind of see how these are going to affect sediment flux throughout our our model domain or our landscape. And then we also developed a stochastic fire model we didn't use the one that was currently in land lab because circles are hard and we like squares as you'll see. And then we're going to use this stream power with alluvium conservation the space and entrainment the space model, Sam absolutely crushed it on getting that up and running. And so we're going to have increasing scale, increasing chaos and that's going to just scale with our fire. It's a binary switches and on off, as we'll look at. And then we're going to just use these output radiuses have some relationship with cohesion, and then we're going to run stochastic precipitation across that fire across our model. So this is what our fire distributions are going to look like and so on our y axis here this is just number of fires it's just a distribution that we're sampling from. And then on our x axis here we just have our fire size proportional to our grids is just a length relative to what our model domain is. And so we've got these these small these these these moderate scenarios, and then we've got these large catastrophic wildfires. So an important bit is this is what our fires are going to look like in model space where in this, this more frequent smaller fires we only have five per our time step, and they're going to be small and then for our, our less frequent but large catastrophic wildfires, we're just going to but as you can see they kind of take up a huge, huge area within our model. And then, so we chose to climate scenarios, and as as Marina put it we chose boulder because we're in boulder. And we've got this climate one climate to fortunately they're they're roughly the same but we're going to still sample from these stochastically, and just kind of look at primarily the effect of fire over time. I'm Sam. I'm a master student at West Virginia University. Okay, so where did we run this model, you may ask. The watershed is really fake. And what we did is we made a like kind of tilted with some random noise and then we ran a stream power model over that to give us a drainage network. One kilometer by one kilometer, you can see in the right corner. This is the hillshade of this watershed.  Sorry. We added so that's a bedrock elevation and then we added soil depth to that we just added two meters arbitrarily. So here's where we instantiated all of our land lab components. We use linear diffusion, just for simplicity, and then like Scott said before space. Here's the time loop that we ran. So you can see for each loop we choose a random precipitation from our climate data, and then we also update the K values, each time from the stochastic fire model. So here's what we found. So this is the control there's no fires in this. So we can see that sediment flux kind of makes sense. It's where the drainage area accumulates, just to make sure it all works. So here's one of the model runs with fire so the red squares are fire. And you can see, sorry, easy gift maker wasn't working this morning. So we're doing this. But you can see where it kind of increases sediment flux and if you notice the color bar, it actually increases that quite significantly. So here's just another fire run. So yeah, the watershed with the most fire kind of has the most sediment flux, which is cool. And here's one of our larger fires. I guess it's actually more than one larger fire. But yeah, notice the color bar again, just the maximum sediment flux is pretty significantly larger than the smaller fires. So what does this look like with precipitation, I guess, okay, this is it without precipitation. So fire is on the bottom. And you can see that sediment flux tracks pretty well with fire. And then when we add precipitation, we lose that effect a little bit, because we see that precipitation is actually pretty important for the sediment flux. And we kind of lose the effects of the fire, which was an interesting result. So here's the same thing with larger fire. So just notice the middle plot we have on the y axis, the percent of watershed impacted by fire goes up to like 50%. In a similar result, we didn't do any statistical analysis, but I think it's pretty clear that a lot of the precipitation trends are reflected in the sediment flux and the fire trends really aren't. Yeah, so clearly this was a simplified model. And so for our future work, we really do need as someone asked earlier, we need more realistic fire habit. And yeah, like I said, squares are nice, but incorporating elevation vegetation, wind direction, all those kinds of things we think would would work quite nicely. We also need to better constrain the relationship between our fire magnitude cohesion, and then our changes in our chaos or our roadability value. And I think that it was just an on off switch, but it would be nice to kind of to to trend that with our fire growth and actually scale it properly. And then we also want to apply this to a real location. We need a real DM real fryer projections and then a little more complex climate data. And then we also want to compare it to actual measure sediment flux going forward. These are references and we also just wanted to thank our instructors for this week. This was really fun as we can all attest so maybe give them all a round of applause because it's been really great. Any questions. Thank you so much for your experience fire by how much did you change the roadability order of magnitude no idea that's right. Gotcha.  So how we how we did it was we just ran a couple, ran a fire scenario, gotten initialized landscape and then gave it a precipitation and saw it out to the fact that's a great point. So you said that you thought that the impact of the fires was not that great on the sediment load precipitation was the greater impact. Why do you think that is why are fires not having a bigger impact. Maybe, because we only changed the K value by an order of magnitude, we didn't really play around that much. If, if only everyone had seen the like fire talks at the meeting before getting started on these projects right. I mean, one thing that I find interesting. I mean, some of the questions that you asked today are questions that could be added in like sort of a discussion topic for students to like ponder at the end of like doing these simplified experiments and say like, what do you really think that is like an additional complexity or what if we would and do in hypothetical on that. Like each of these are in the end like presented for like students to be used or learners to be used or like as an example for a set of like simple notebooks to build upon so we have a whole bunch of people who are interested in coastal behavior. And they took not out of the landlap component set but they worked with a model that's called pie delta RCM and the two developers or the two active developers that are working on that model are here. So like they'll get like a surprise and like may have some feedback. Or it can be super proud because their model was accessible enough and easy and UV enough and documented enough that other people could start like tinkering with it right so So that's a group that worked on vegetation effects on coastal systems. Elena is a more Liz Kelly and Lexi are presenting. Hi, yes, my name is live, and Lexi and I will be doing the presentation and is more and Kelly will be filling your questions. So today our talk is titled exploring the interaction of salt marsh and mangrove vegetation on river delta evolution. So we know that vegetation influences delta morphology and evolution with so our research question is does a delta that grows with mangrove vegetation evolved differently than a delta that grows with salt marsh vegetation. This is motivated because vegetation eco to eco tones are shifting due to climate change. So it's likely that coastal areas currently occupied by salt marshes may transition to mangrove. An example of this would be south Florida. So in this image you can see that currently mangroves dominate southern Florida, but we think that possibly they will start shifting north where salt marshes are in the north. To address this question, we use the delta RCM vegetation model. So the vegetation model was built firstly on the delta RCM model. So the delta RCM model is the delta river delta formation and evolution model with channel dynamics. The vegetation component was expanded to include vegetation effects. So in this model that was published in 2018 vegetation colonizes grows and dies. This increases a bank stability and improves resistance of flow and the original parameters for vegetation such as stem diameter carrying capacity, logistic growth rate and rooting depth represent marsh grass grass type plants. So what changes do we make to this model. So the parameters are now defined by a gamma file. We converted X range to range because the original model was written in Python two and wanted to run in Python three. And we use mangrove parameters for comparison to salt marshes. So in this table you can see that we changed some of the parameters from thought marsh like some diameter from point zero zero six meters to point one four. So the amount of the capacity is much different between salt marshes and mangroves as well as the rooting depth. I'm going to pass it over to you. Yep, so I will be talking about our Jupiter notebook and how we kind of set it up. So at the very beginning, we didn't have pygamel installed so we had to install it. And then our next statement just imports, YAML which we use to import the YAML file and image IO which we use to create the GIF. It's really helpful for you. And we import the delta RCM class from the Python file. And then the next line of code, we actually import the YAML file and what that looks like, at least our YAML file has all these parameters in it. Which these were originally defined within the Python file itself so we just made that easier for users to change their own values and we decreased things like the water particles and sediment particles just to make it run faster. And our total time step is 5000 which represents about 150 years. So then our second to last block is just setting up the model so instantiating the model with our parameters and changing our values for either salt marsh or mangrove like what Liz was saying from our table, and then running the model, which takes very long time. And then our last block of code just creates the GIF files. So here's one example of out like just one of our simulations which was a mangrove simulation. And the top left graph shows the elevation so the white is your elevation and then the darker it is the more negative it is. So our top right graph shows the vegetation, which is from zero to one based on a density of vegetation density. The bottom left is discharge and the bottom right is water surface elevation. And so we we decided to save time steps at approximately 25 year intervals. So that's what you're seeing here is the evolution of 25 year intervals over 150 years for a mangrove run. And so kind of transition. This is what the four different scenarios we use kind of based on the original paper parameters. And this is specifically for salt marshes. So the way this works is that from top to bottom, we have a decreasing flood frequency. So what that means is the 75 is 75 time steps in between a flood. So 100 time steps between a flood is less frequent than 75 time steps between the flood. And then on the x axis, we have the sand percentage. So 25 is 25% sand 75% mud, and the right is 75% mud 25% sand. And really just what we want to notice is that the flood frequency didn't really seem to impact the vegetation or growth that much they're pretty similar. And then the like in the marshes we have a lot of small channels forming off the main channel. Whereas when we go to our mangroves you can see there's a lot less kind of like white space in the vegetation so we saw that there were a lot less channels forming. But these are again the the same 25% 75% sand and flood frequency. And we also notice that when we did the mangrove vegetation for 25% sand we had a lot less colonization around the entire semi circle. And then we're going to do further analysis using the top left scenario. So that is the 25% sand and 100 day flood, which Liz would talk about next. So yeah we compare those top two left plots, which were the base conditions in the original model. Okay, sorry. Yeah, so I hope you got that. So if we compare the results between the salt marsh and the mangrove deltas between the vegetation and the mean free surface elevation we can see that there are differences. So in the first plot on the left, we have time in years on the x axis and vegetation cover in pixels on the y. The salt marsh and mangrove vegetation start out a little bit different, but they do converge around the 60 year mark and then slightly diverge again at the 150. In comparison, the on the plot on the right we have again time in years on the x axis and mean free surface elevation in meters on the y. And again the salt marsh and mangrove vegetation deltas start differently, but instead of converging the differences only grow. And so if we can tie this back into our research question, does a delta that grows with mangrove vegetation evolved differently than a delta that grows with salt marsh vegetation. We found that yes, we found spatial and temporal differences between vegetation cover free surface elevation and as well as the other variables. So these are key findings and implications. First that we were able to simulate delta growth under different dominant vegetation conditions using the delta RCM vegetation model. Secondly, we found spatial and temporal differences in delta evolution between the vegetation types. It's important because the evolution of coastal areas under different types of vegetation is important for planning and management of coastal areas as well as thinking about all those ecosystem services that mangroves and salt marshes provide. So with that, they will be happy to take your questions. Great job. My question is thinking about your plot that showed the differences in elevation between salt marshes and the mangrove simulations has that been observed like in the real world, do we know. Hi. That's a really good question. So it really. So I guess I'll also answer it a little bit with the lateral accretion, because mangroves do accrete laterally and so you do see those increases they're known as land builders right so they both go in X and the y direction is the way that I like to explain it to people. So those differences. I'm not so sure off the top of my head in terms of salt marshes, but I do know based on your comparing trees and the tree root systems I wish we had a picture of a red mangrove, because I can explain a lot better. But you can, you can think of red mangrove root systems as kind of like spider claws is what I tell people, and or spider legs and so they're able to trap sediment but also the organics come into play and they're able to. Their leaves fall and kind of degrade within their mud systems, they're able to trap those leaves and it doesn't really leave the system so they kind of do accrete up as well. So you do see that sort of but I'm not too sure. Yeah, I can expand on that as well so this free surface elevation. The differences there are really related to the vegetation properties itself so like if you think of a salt marsh that it's like really high density and there's like lots of plants. They're everywhere, whereas the mangroves are trees so they're like a little bit more spread out. So what that graph is showing is not like. It's really related to like how the water is like interacting with the vegetation itself so more of like a hydrodynamic impact, but this model has yet like a smart was saying has no vertical accretion for either the salt marsh or the mangrove, which would be really important to include in a model of Delta growth because typically in like a salt marsh that organic sediment that Ismar was explaining makes up like between like 30 to 80% of the material that's actually on the platform. Depending on the mineral sediment loads those areas so yeah it's a bit more complex than that this graph shows I would say. Super cool. It's fascinating work I think you guys should write a paper. But I'm really wondering about how the water surface elevation is higher in the mangrove cases that you were alluding to the hydrodynamic properties but I would have guessed, since there's so much more rarefied that they'd be less resistance to the flow and so the flow would be less effectively channelized when it looks like it's more. I'm wondering if the deeper roots and the fact that it makes it harder to kill those. And so they're more on a longer time scale or morpho dynamically confining the flow more than hydrodynamically. What do you guys think. Yeah, I would I would agree with you. Yeah, I have. I can talk about this all day. So in the Caribbean specifically just off the top of my head we have four different species of mangroves right. But the main to that a lot of people focus are on our red and black mangroves that have completely different types of root systems right. And so that's not really simulated in the pie Delta RC and veg model, but depending on the root system that you have the type of mangrove in terms of which type of mangrove you have, you're going to get different types of channelization, and also the hydrodynamics of the system so depending on how much salinity for example or soil stressors. You have there's going to be different kinds of mangroves and different parts of the delta egg region right and so those root systems really do affect the channelization. And as I explained with the spider leg analogy, like mangroves have proper roots which I explain as like forks sort of. And so they trap sediment, sand sediment completely differently than red mangroves would. So channelization is different depending on the species as well. I just want to make you run. Awesome talk. I have a question about so at the beginning you talked about how in some areas you know mangroves are might be overtaking where salt marshes used to be. And so you ran these as separate separate model runs. And so I don't know if you had any comments about how, you know, if use a mix of properties how the delta changes or if you start with like you run the mangrove simulations but start with the marsh salt marsh elevation and symmetry how if you thought about that at all. Yeah, that was actually like our initial goal was to have the mangroves like encroach on the salt marsh in the model itself. But we just ran out of time. But yeah, I think that would be really interesting. Awesome, given this is given the time this was an awesome project. Our last team also focused on delta processes. And it shows you one of the merging conflicts in our community where they use a different version of pie delta rcm the more updated version that did not have yet vegetation characteristics so like got to do something. This team. Include a 10. Donna Lawrence, Katie and Juliana are going to talk about delta rcm and delta processes. So we're just going to introduce ourselves real quick. My name is Caitlin or Katie Turner and I'm at Louisiana State University and I'm a PhD student. I'm Julian Davis I'm at UNC Chapel Hill and also a PhD student. Hi, I'm Lawrence Willis I'm a PhD student at UC Irvine and also a PhD student. Hi everyone I'm Jenna left it up to you. I'm a master's student at UT Austin. And Tian Dong who's a postdoc at UT Austin who had to leave early on here with us today contributed quite a bit to this project. And then we would also like to thank Ethan, Josie and Mark for all of their help for getting helping us and arena for helping us get this model to run. So, one of the main things we really wanted to do was connect real life situations that are happening to our Jupiter notebook. So we used wax like Delta as kind of a case study using the pie delta rcm model. So one of the things that coastal Louisiana is really experiencing right now is land loss, and that is due to a range of factors such as subsidence sea level rise and as well as this lack of sediment that is happening partially can be due to the upstream damming that's been occurring in the Mississippi watershed. And so we actually experience in the wax like Delta Mississippi area, 50% less sediment rates than their early historic values. So this is definitely due to damn trapping trapping, trapping sediment. And the other part that's going on is when we have the a chaff ally river having this kind of pipeline of levees, we're not getting sediment going into the surrounding areas which is why, if you've ever looked at the Louisiana coastal master plan there are a lot of diversions coming in. And so this was kind of our, our inspiration for this project. And so you can actually see with wax like Delta, it was created it was a man made flood diversion. And so you can see the growth of this delta over time. And so we wanted to see how if we change sediment, how is this going to impact delta delta growth. And so the first part of this was to characterize stream flow so we wanted learners to understand what, what is happening upstream. So our first part is looking at using a Python package called data retrieval which takes USGS stream flow and showing them different ways to calculate the flow frequency curve, as well as the exceedance probability and intermittency factor, because the intermittency factor really tells us how long we're going to have flood waters that will contribute to growth. So it walks learners through what all of these processes are and what they mean, as well as how to plot them. And so we can see a few of the plots that they'll be able to replicate themselves. And yeah. Cool. Yeah, so then there's some educators, educational questions and comments here like, can you comment like what the intermittency factor white meat might mean etc. And then we wanted the students to use a more for dynamic model to basically simulate delta growth. And in this context, PI delta RCM which is reduced complexity model for delta growth was the ideal candidate because it can run within the Jupiter notebook and basically build a delta in a couple of hours. So actually the developers are here. And it's available through land lab. So we basically set it up in this notebook and then designed a couple of experiments that the students would be able to play with basically different set of characteristics corresponding to different real world damming scenarios and Julian's going to walk through that. Finally, we wanted to simulate different effects that dams can have dams can take a range of forms but here we're kind of just reducing the complexity of the problem to think about an earthen dam, like you see on the right that doesn't allow any water or sediment through, and then a dam that has a slew skate allowing some water suspended sediment and bed load to continue moving downstream, like you see in the image on the left. The table below shows the scenarios that we have run. As Katie said it's inspired by the wax like Delta but we're not claiming to be reproducing that system. So we are looking at two different sediment concentrations which you see in the rose. Originally, a sediment supply of point three and then point one five. And then in the columns were changing the amount of sand versus mud so changing the sand fraction to see what would happen if bed load is reduced, and as you move to the right in this table, the delta is totally made out of finer grain sediments and mud with no sand present. We call those baseline and then a through a will be using that notation again so just as a logistical thing. We do take a bit of time to run as the other vegetation group said, which is why we have do not run this step in our educational module. We recommend this as a lab with a homework, the component where these students run the models overnight and do the hydrograph things on day one day to look at their output. If you don't have that much time we have also uploaded the results of our modeling that students can look at. So we then ask them to follow through some of these steps, import the data and begin doing some different visualizations. This figure shows our outputs and those format is the same so the top left is our baseline. The bottom row has the initial sediment concentration. Bottom row sediment has been cut in half, and as you move left to right, the amount of sand decreases until you only have mud, all the way on the right. This shows delta elevation and values in light green to yellow are elevations above the water surface. We ask the students to make different observations about what they see in these deltas. What we encourage them to look at is the frequency of different elevations that they observe like which deltas are more effective at building upwards versus outwards, and that's what these histograms are showing. We then ask them to look at bifurcations and the number of channels. So again here, we are showing those six simulations and the colors here are flow velocity, higher velocities in yellows. And we ask the learners to compare these different deltas, think about how the changes in sediment could result in the changes in delta morphology that they see, and then make comparisons over time. These show the deltas at the end of the model runs. And here, we look quite a few time steps earlier, but smaller deltas and ask the students to kind of think about how these deltas grow and change through time and how that varies with sediment characteristics. We also invite the learners to make some predictions about other parameters they could change in this model. How could they simulate subsidence or sea level rise. We ask them to the documentation and encourage exploration of other ways that they could change the deltas that they can make in pi delta RCM. I'll pass it back to Katie to wrap it up. No, we're good. So part of this learning component is to link it to like the broader impacts as well. And we finalize it with just like a general discussion section where they can look at the broader impact of the entire watershed. This is just an image of the Louisiana or Mississippi River watershed area, and we're showcasing the cascading effects of dams along the watershed, where resources are extracted all throughout. We also provide a link to the master plan for the Louisiana coast, where they can look at restoration projects that are currently active, and the different scenarios that they can use such models to kind of forecast for the master plan also like reduction in budgets and mitigation efforts as well. So we want to like invoke them to see other broader impacts that link science to society as well. And that's pretty much our model. Any questions. Thank you so much for your work and building this really cool educational module. And, of course, being up in Minnesota, I appreciate doing on the Mississippi. And I was wondering if you guys have any insights into how much the locks and dams in the upper Mississippi actually affect the settlement supplied to the lower river considering the sharp dropping gradient to the lower Mississippi and the large amount of sediment buffered in the valley itself. There's actually a reduction of about 50% of historical values, which if you're thinking about land building, that's, that's a lot. And so it's starting to cause, we have other issues down in Louisiana, I go to LSU so I get to study it a lot. And so subsidence is also part of our issue and sea level rise, but it used to be that the sediment could actually help counteract that but because we don't have those same sediment, it's actually getting more difficult. So even when those diversions go in, it is going to be kind of a diversion game of, okay, we can open this one but we can't leave it open too long because it'll create shoaling on this channel. So it's still, it's the diversion network that they're creating down there is incredible. And so it's really kind of stemming from this issue that there is a lot less sediment. If you had another day or two. Where would this go. So I personally think it would be cool to see how the stratigraphy changes. So if there's a way to like incorporate more grain size variations, see how the stratigraphy would look like in a vertical sense, while the delta is building up. So sometimes we see the delta is pro grading versus a grading. And I think it would be cool to explore that aspect. As other groups have said we also had, you know, an original idea and then what was feasible in the time given. So something we talked about originally would be running a delta for a certain amount of time and then starting to modify the characteristics, instead of starting with an empty basin. But we think that would require modifying the source code and that was a bit beyond what we felt we could get done and present. So I think that's another direction we'd like to take this. Did you want to add more. Okay. What do you envision as the age level for the learners. So we were actually given an approximate age level which is helpful. And it was more advanced undergraduates and early graduate students. I was thinking about this it really seems like a hydrology class or geomorphology class because it really links those two together and a lot of the times if you take a class and say civil engineering and then one in geomorphology, you can kind of miss those links so it was really for us to link it together. I want to thank everybody for such hard work that was done to like get to these projects. These participants know that you will be nagged by like the people from the integration facility a bit to like get this into the educational repository and there's like 100 other people that now know that these exist, right. So that may want to use it in classes or they may want to use the material like for their own like hydrology class geomorphology class etc. I think these are wonderful I think some of you like really showcased, like sort of the progression of how a student or a learner or like someone who pulled this from a repository would interact with this and have questions and things. I just focused a little focus a little bit about the contributions that you did make changes to code or like small improvements to like how users would interact and I just appreciate like how many in engineers creative like solutions you found for all these like obstacles that were there in the in the process of putting a notebook together like this.


Homeless man Suze Burger King for a million dollars, over three months spent in jail without proof. When it comes to the ways we interact with society, there are a lot of things we take for granted on an everyday basis. We expect to be treated with basic decency and respect by the strangers that we interact with, especially in situations where we're spending our money. Unfortunately that does not always occur and sometimes when it happens and people are treated poorly the consequences are astonishing. But if there's one thing that's true in this world, it's that for all our lofty ideals about all men being equal in the eyes of God and the law, different types of people are treated in very different ways. Just as in the prince and the pauper, the very rich and the very poor may as well be living in two different worlds. The way this one man was treated for the sheer fact of how he lived has angered many who have called for a change. Nobody wakes up one day and says, I want to be homeless. Many people walk by or encounter people who live on the street on a daily basis in big cities and in small. It is often a misconception that these people chose this life or made poor choices so that is why they are where they are. In some cases that is definitely true but in others there are many other reasons. Whether it be mental illness or just falling on hard times, there are many reasons that can lead a person to become homeless. Emory was the latter who tried to live a productive life and do the right thing but kept finding himself falling down and unable to get back up. Years before he ever stepped foot in a burger king for breakfast, Emory made an awful mistake. Down and out on his luck he needed money badly to pay for basic life needs. Unable to find a stable job or even an odd job Emory made the bad decision of trying to steal in order to get money. Emory decided he would forge a check in order to get some free cash. This was a bad decision as he was not an experienced forger. As you can imagine, Emory was quickly arrested on charges. Luckily for him though he got off with a break and only received probation. The probation he received would later cause mass trouble for Emory. Emory now free and back living on the street was trying to stay on the straight and narrow. He decided he would live a more productive life and was actually picking up small jobs to earn cash that he was able to use. While he was still homeless he put the life of crime behind him. It was a November morning in Boston when Emory walked into a Burger King. Like every other customer in the store, the 37 year old man was there because he was hungry and while it may not be the healthiest way to start the day, breakfast at a fast food restaurant is nothing if not quick and inexpensive. Emory went to the counter, placed his order, then handed the cashier a $10 bill, just as millions of other people would do around the country every single day. But this time it would result in the kind of treatment no other Burger King customer would have to deal with. The cashier immediately looked at Emory as if he was trying to determine what type of person he was. While it wasn't blatantly obvious he was homeless he also wasn't totally up to keep. The cashier looked at him up and down and Emory had no idea why. Rather than ringing him up and handing him a receipt then moving on to the next customer while his food was prepared, the cashier stopped and took a close look at the bill. The cashier was acting very odd and Emory was beginning to get nervous. He felt like he was being profiled and asked, is everything alright? The cashier told him to wait a minute as he walked to the back of the restaurant. At this point Emory began looking over his shoulder totally embarrassed by what was occurring. What he didn't know was what the cashier was going to come back and say to him. As he stood there he noticed the cashier walking oddly back towards him, almost with a grin on his face. As the cashier approached Emory asked again, is everything alright? The cashier then smiled and said, good try to Emory. Emory had no idea what the cashier was talking about and asked him what did he mean. Emory was then surprised when the cashier accused him of trying to use counterfeit money. The cashier had said the $10 bill that Emory had handed to him was a fake and that he was calling the police. Emory now totally embarrassed could not believe what was going on but it was about to get worse. Being treated differently from most people wasn't exactly unfamiliar to Emory. He was a homeless person, which meant he was used to people looking down on him or thinking he was up to no good, whether or not they had any cause to. This was different, he was not being accused of a crime. It is one thing to look down or feel pity for him but it is an entirely different thing to accuse him of using counterfeit money to purchase his breakfast. This was not a good situation for someone like Emory to be in. But in this situation where he was just trying to buy a meal like everyone else, it came as something of a shock. Still without any food in his belly, Emory was willing to just take his $10, all the money he had to his name, and leave. While he found it ridiculous that he was being accused of this he didn't want any trouble. He figured that if this Burger King wasn't willing to treat him with respect, he would get his breakfast elsewhere. There were plenty of places to eat and he was not going to give them his business or be treated so disrespectfully. Emory at this point politely asked the cashier if he can have his money back so he can go eat somewhere else as they did not want his business. The restaurant refused to give him his money back. Emory was in complete disbelief. While to most of us $10 may be a nominal amount but to a homeless person who only has $10 to their name it was everything. He could not just leave without his money as he needed that money to eat the day, it was all that he had. He asked them to please just give him his money and he will go. They said no and had other plans for him. The workers at this Burger King instead of just returning the man's money decided that they would call the police. They were confident that this man was using stolen money to make a purchase and they wanted to teach him a lesson so he would not return and try it again. The question you have to ask yourself is if this was not a homeless man would he be accused of such a thing? Would an ordinary person be put in this kind of situation and accused of using fake money? It is something that Emory asked himself as he waited. Emory decided to stay and wait for the police to come because he needed that money badly and couldn't leave without it. He tried to talk some sense into the cashier and the rest of the staff while he waited for the cops to arrive. He figured that when the cops arrived they would sort it all out and realize it was not fake money that he was using. The police would give him his money back and he would be able to go on his way and find somewhere else to eat. Boy was he wrong. It was still early in the morning when a squad car with officers pulled into the Burger King parking lot after receiving a call that a man had tried to purchase a meal using fake money. It is not a usual call that officers get but nonetheless when they are called, they show up. The officers walked into the Burger King expecting a commotion but saw a man calmly standing there as well a few workers mulling around. They were unsure who were the involved parties were but were immediately called over by the employees so they can explain the situate one. The workers at the Burger King told the officers what had happened and why they made the call. The officers had asked the workers to see the $10 bill as well as many other questions such as if Emery has ever tried this before and if he was a frequent patron. After watching the officers speak with the employees, Emery felt confident that he would get his money back and be able to leave. He figured the officers had to recognize a $10 bill when they saw one. As Emery stood there and waited he had no idea what was coming for him. The police walked over to Emery and asked him his side of the story. Emery explained what was going on and implored the officers to take a look at the bill. Thinking that once they did look at the bill this whole misunderstanding would go away Emery was relatively calm. The officers said they had looked at the bill and they believed it was fake. They questioned him a bit more to ask where he got the bill from and Emery could not believe it. Then without hesitation they arrested Emery on the spot. Instead of starting the day off with a hot meal, Emery Ellis was starting it off with a ride in the back of a squad car. On the ride to the police house Emery could not believe what was happening to him. He felt he was profiled for being homeless and felt this was totally unfair. As they pulled up to the police station it began to dwell on Emery that he was in serious trouble. While he did nothing wrong he did not have the means to defend himself. Emery was officially charged with forgery of a bank note, a crime that can carry a life sentence. On top of the hefty jail crime he could be facing the arrest would have an even more harmful impact on Emery's life than it might have for another person. As mentioned earlier Emery was currently on probation for forgery although this time he really didn't do it. This arrest triggered a probation violation for him which meant he would be held without bail. Emery would have to sit in jail for no reason at all until his final probation violation hearing. This was a bad situation. Emery Ellis was not sitting in jail, locked up behind bars, for almost three months. As Emery sat in jail wondering why this was happening to him he also had to question his past decisions that landed him here. It still felt brutally unfair that he was in prison because someone profiled him and then the police didn't believe him. Emery had to wait for the bill to be verified. This is done by having the bill sent to the Secret Service, the arm of the justice system that deals with counterfeit money. They would then inspect the bill to determine if it was real or not. After the investigation was completed by the Secret Service and justice system they determined the bill was not a counterfeit. Their investigation proved what Emery had been saying all along, the $10 bill was real. The prosecution then admitted that no crime had been committed and the charges against him were dropped. A judge also subsequently determined that there had been no crime, thus no probation violation and Emery was finally released from jail. But his next ordeal was just about to begin. Just because he was out of jail, everything wasn't automatically right with the world. Emery had lost over three months of his life to this foolishness, not to mention being subjected to the fear of being locked away for the rest of his life. As an icing on the cake, he didn't even get his $10 back. Emery was not back on the street without any money and his dignity lost. To make matters worse he was fearful of now returning back to jail for things he did not do but would be accused of. These were not good times and made it harder for Emery to get back on his feet. Emery was looking to seek revenge, to right this wrong. Emery seething with anger wanted revenge. He wanted someone to pay for the three months he lost and the embarrassing ordeal he was put through. Instead of turning to violence though he turned to the law. He felt someone had to pay for what had happened to him both literally and figuratively. Emery secured the services of a lawyer to get some sort of restitution for the way he'd been treated. He secured the services of a lawyer called Justin Drexler, who filed a lawsuit against Burger King, the cashier, and two guys foods, ink which was the French's E. Justin Drexler sat in his office as Emery told him everything that had happened to him. Justin felt just like Emery did that someone had to pay for this and he was the man to make that happen. Emery felt confident his attorney could get the job done. Justin worked quickly to draft up a formal complaint. The complaint said that Emery suffered public humiliation and shame, sleeplessness, anxiety, and depression because of his arrest and incarceration.  The suit alleges that Emery was discriminated against because he appeared unkempt and seeks damages for civil rights violations, defamation, theft of Emery's money, and compensation for the months he spent in lockup. In total, they were seeking $950,000 in damages. Justin spent much time crafting this complaint and ensured it covered every aspect that Emery told him. He felt the complaint should properly demonstrate the pain that Emery went through and to let the public know how this man was treated. Though their lawsuit did not say that Emery was discriminated against because he was black, his attorney, Drexler suspected that Emery's race was a factor, combined with his disheveled appearance. He said that if a white man in a suit such as himself had handed the same $10 bill to the same cashier on that same day, there would never have been a question of its legitimacy. Even if they were, he said, the cashier would probably have apologized and said he couldn't accept the money and it would have ended there. The police never would have been involved, Drexler said. Drexler knew that this could be a controversial point to make but he felt it was necessary to point out the hypocrisy in all of this from the cashier's actions all the way to the police officer's actions. A person like me would have gotten an apology, but a person like Emery somehow finds his way in handcuffs for trying to pay for his breakfast with real money, the attorney added emphatically. People will say, he was homeless. Who cares if he went to jail for three months, he added. Unfortunately Mr Drexler had a fair point and was making an argument most people could agree with. Drexler when describing his dealings with the insurance company for Burger King said, and even when you negotiate with these insurance companies for the franchisee, they'll say, well, he didn't lose any wages. Drexler continued. He lost his G damn freedom. You think wages mean anything. Two guys foods, the operator of the Burger King where the incident occurred, offered Emery a $10,000 settlement but was turned down. We didn't think that was nearly sufficient, Drexler said. $10,000 is a nuisance money offer. Still splitting his nights between friends' couches, shelters and, when there's no other option, the street, this isn't about the money for Emery. Acts of discrimination, subtle and not so subtle happen every day and most of them don't see the light of day because most of them don't result in any consequences, said Drexler. Drexler continued, if Emery was in it for a quick buck, he would have just taken the $10,000. How many homeless people do you know that would turn down that money? A Burger King Corp spokesperson said the company does not tolerate discrimination of any kind but cannot comment on the specifics of this case. The company went on to say that the franchisee, two guys foods, Inc is responsible for employee training and handling legal matters about the location. The lawsuit filed was first reported by the Digital Legal News Service LAW360 was filed in a Suffolk Superior Court. They are seeking damages for $950,000. While this is not about money Emery feels he should be compensated for the three months he had to spend in jail as well as all the other things he dealt with. To him the $950,000 would make someone pay for what happened to him and he can have a second chance at life. This story was eventually picked up by the national news and went viral on the internet. It sparked a conversation online about treating people the right way, discrimination, and how things like this should be handled in the future. Emery was glad that this story made its rounds as he felt it was important for people to know he was a real person to and that even though he was homeless it does not mean he should be treated differently than others.