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Climate Resilience and Urban Sustainability: The Need for City-Wide Stormwater Models

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As the world grapples with the realities of climate change and rapid population growth, our traditional methods for managing stormwater have shown their limitations. The conventional focus on site-specific solutions, while essential, does not fully account for the complex, interconnected nature of urban water systems. This session will introduce a comprehensive, city-wide approach to stormwater modeling as a more adaptive and effective solution to these contemporary challenges.

Key Learnings

  • Gain a better understanding of the impacts that climate change and population growth have on urban water systems.
  • Learn about vulnerabilities and areas for improvement in our current stormwater management practices.
  • Learn about developing increasingly resilient, integrated, and sustainable solutions for urban water management.

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      Transcript

      MEL MENG: Hello, everyone. Welcome to our presentation about how citywide stormwater models can help reduce the flooding risks and make our communities more resilient and sustainable. My name is Mel Meng. I am a support engineer from Autodesk. Hey, Jacob, do you want to introduce yourself?

      JACOB RISCHMILLER: I'm Jacob Rischmiller. I lead our water resource practice group here at ISG.

      MEL MENG: OK. So this slide is just our standard legal disclaimer. It basically says that any forward-looking statements about our future plans, results and product capabilities are based on what we know right now. But things could change. Also, remember that these statements are relevant only at the time of this presentation. And we're not obligated to update them. Finally, don't make purchasing decisions based on these forward-looking statements.

      Before getting into our presentation, I would like to share this opportunity of shaping the future of Autodesk products by joining our research community. Sign up using this QR code displayed, and answer a brief three-minutes survey to join the community. Once you join the community, you can share feedback and influence your Autodesk experience. You can receive a exclusive look at Water solutions and deployments. And, also, you can contribute to industry-leading digital innovations.

      OK. Let's get started. Thank you for joining us today. Jacob and I are passionate about this topic and excited to share it with you. You might be thinking, do I really need two civil engineers to tell me more about climate change and natural disasters? If that's on your mind, we're glad you're here. We're tired of endless news and opinions, too. What we want are actions. We believe there are many practical steps we can take to make a difference.

      Today, we'll share insights, practical tools and effective methods to help us better prepare for extreme flooding events. Here's what you can expect from our presentation. Extreme storm and flooding, we'll start with two successful stories about how communities are handling the challenges of more extreme storm events and the high cost. Paradigm shift, to address these challenges, we'll need a paradigm shift. Flooding can no longer be eliminated with simple engineering solutions. We need a risk-based approach to mitigate flooding risks.

      2D modeling, I'll explain how 2D modeling can help us find better ways to mitigate flooding risks. Funding, the great news is you can apply for public funding to pay for part of your project. And Jacob will share how he and his colleagues are helping communities build a sustainable future with these funds. By the end of this session, we hope you're thinking about all the things you can do to help mitigate flooding risks with 2D modeling.

      We're going to share two stories. One is in Australia, a flooding map project for the island state of Tasmania. Another is a small community in the United States. The Tasmania Flood Mapping Project is a great story about how 1D/2D modeling can save lives in Australia. Tasmania is this island here.

      When it comes to flooding, they were very unlucky in the past few years. They were hit by extreme storms three times in just a few years, 2016, 2018 and 2022. However, with the help of a statewide 2D model, they were much better prepared when it hit in 2022.

      Let's get into the timeline here. Back in 2016 and 2018, Tasmania was hit by severe flood, causing massive damage. To tackle this, the Tasmania and Australian government launched the Tasmania Flood Mapping Project. The mission? To better understand flooding risks, strengthen communities and improve emergency responses.

      The project's real value was proven in October 2022, during record flooding. Within 48 hours, the team used observed and forecast rainfall data to create impact maps. These maps helped prioritize assessments and shape recovery plans. When more flooding was forecasted for the Meander River, they produced a predictive map 12 hours before the rain, guiding response strategies and public warnings.

      Thanks to this project, Tasmania has improved their response time significantly. They are now working on automating weather data integration to further enhance their flooding forecast capabilities. This project shows that extreme storms can happen a lot more often as climate changes, but we can be better prepared to protect our communities, saving lives, using the latest generation of modeling tools.

      Now I'd like to hand it over to Jacob to share a story that is much closer to us.

      JACOB RISCHMILLER: And I'll be talking about a more recent and local to the US event here. In late June, rainfall events in southern Minnesota were at a catastrophe. And as you can see on the screen here, in June 20th to the 23rd, the Blue Earth County area and [INAUDIBLE] County area had almost eight inches of rain in three days. This led to a massive amount of rain and rainfall in the streams and in the banks.

      As for their total rainfall for the month, that was about half of the rainfall for the entire month saw in three days, so quite a bit of rain coming through in this area, in a three-day time period. Part of that is the climate change and figuring out what happened. Average rainfall for this area is three times less than what they saw back in June here.

      So with all this rain came substantial flooding for multiple cities. This one, in particular, is in Waterville. This city experienced water, especially their downtown, for three to four weeks, and some locations along the river itself for about two months. So quite a bit happening that aren't just happening outside the US, but also within the US as well.

      MEL MENG: OK. So those two stories might sound extreme, but the truth is devastating floods are becoming more frequent and more costly worldwide. To understand the gravity of this situation, I turn to the NOAA website. It lists $1 billion disasters over the years as measured by insurance claims. Let's look at the 1980s first. So that's this first row. Over that entire decade, there were only 33 disasters, each causing at least $1 billion in damage. The total cost is $218 billion.

      Now, fast forward to last year. So this is 2023. In a single year, we experienced 28 events, disasters, with a total damage approaching $100 billion. If you examine the frequency of the events, that's this column. And you just look at these numbers. The trend is unmistakable. Costly disasters are becoming far more common in recent years. This is not just a series of isolated incidents. It's a clear, alarming pattern that demands our attention and action.

      So what is driving this dramatic change? Let's dive into some of the factors. According to the FAQ page from the same website, climate change is increasing the frequency of certain types of extreme events. But there is more to the story. The high costs are largely due to the fact that much of our growth has taken place along coasts and river floodplains.

      They are inherently vulnerable areas. And unfortunately, the insufficient building codes allowed them to be built. In this presentation, we're going to share how 2D modeling and citywide models can help addressing these issues.

      As the two stories we just shared, managing flooding, in many communities, has evolved far beyond a straightforward engineering task. For many, flooding isn't a question of if, but when. The challenge lies in mitigating the risks through strategic trade-offs to determine what's best for the community. The shift requires a fundamental change in our thinking, a paradigm shift towards a risk-based approach. In the next few slides, I'll dive deeper into what this entails and how we can implement it effectively.

      In this slide, let's take a quick journey through the past 30 to 40 years of stormwater and flood management in the United States. The modern era began in the 1970s, with the creation of the EPA. And the 1980s saw the establishment of FEMA. Take a look at this figure from an EPA report. It shows annual water budget for a hypothetical watershed.

      So as you can see here, it shows a different component, as an annual basis, on how much water ended up to where. So one thing I really want to highlight is the surface runoff. So the water ended up in your rivers and streams. Before development, it's only 0.3%. But after the development, it was close to 30%. So there's a huge increase of the amount of water ending up in your streams after development.

      So probably in the 1980s, FEMA did a study and established a 100-year flood elevation to be here. And following that, developers started to build buildings. And obviously, the buildings are built on the high ground. And it's high and dry. And when you are building on a high ground, the most important thing for you is to get rid of the stormwater as soon as possible. And you just need to put a big pipe. And if the flow is too high and causing flooding in the channels, you put a detention pond. And problem solved.

      But as you can see, in reality, when you start developing, the runoff will increase and the water level will increase. There will be more flooding risk in those areas. However, at those times, nobody are building here, so nobody noticed the problem. Then, maybe in 2000s, when people keep developing and all the high ground are already built out-- but if you want to build in the lower ground, you need to go to the FEMA map. And most likely, the insurance map haven't been updated. So the line is still here.

      So you say, OK. It's OK. I can build here. It looks nice. So you put a building somewhere here, so right above the 100 year. But in reality, maybe for a 10-year storm, the building can be underwater. So, in essence, this is why we're seeing more flood damage today. We're building more in flood-prone areas than we did 10 or 20 years ago. Even if the current climate remains constant, we're destined to face more flooding issues.

      Before delving into the new approach, it's essential to understand the limitations of our current methods. The primary limitation is largely a technical one. It makes perfect sense to require developers to apply for a storm permit to ensure no harm is done. The intent is clear and easy to understand. However, the challenge lies in proving that no harm will actually occur.

      In practice, regulatory agencies prescribe design manuals that outline the best practices for sizing some pipes and ponds. Developers are required to follow these guidelines. But here's the problem, as I have shown in my previous slide. Most of the design manuals operates under the assumption that we're building on high ground that won't experience flooding. And by referring to a outdated FEMA flood map, we're building in low areas that are likely to get flooded.

      Let me show you an example of how technology can significantly impact how we address flooding issues. This slide shows a flooding situation for a river with three-road crossings. So if you look at it here, this is a profile view. This is a river bed. I can see this is just river. And they cross this three road. So we are showing here that these are different colors.

      As you can see, there's a flooding at this road. So the solution is just you make the pipe bigger. But not that simple. We want to make it bigger. It will increase the water level downstream. It might cause flooding downstream. So the criteria is make sure, after you increase the size of the culvert, the elevation stay the same as before. You want 122. 122.

      So problem solved, right? Maybe not because you gave these assumptions based on the technology or the method you used. So for this, we used steady state flow. So the steady state flow was a method developed back in the '60s. So you can imagine, at that time, the iPhone in your pocket probably is more powerful than the most advanced computer at that time. So at that time, the key is to simplify everything, so that the computer can handle it. So that's why we use a steady state flow.

      But for the steady flow, instead of looking at storm for the whole duration, we just say, OK, let's take a look at peak flow, the 134 cfs. And we assume the river will flow day in and day out with that flow forever. It doesn't change. So the level will stay the same on the reserve. Time doesn't matter. So that's the conclusion we got.

      And so let's move to the next slide. The next slide is-- so this is the unsteady flow. So this unsteady flow for the software [INAUDIBLE] was introduced in 1997. And this is a more realistic view of the reality. It assumes there's no water in the river-- or very low level in the river before the rain starts. And then it ramps up to this peak flow. And when the storm stops, you can see it ramps down. So that's a lot more realistic view of what really happens.

      And then you can see, with the same peak flow, it just changed to the estimated steady flow. We don't even have flooding in the first place. The reason is simple. Because your river is mostly empty before the peak of the flow. So we have a lot of room to store that water, so that won't overflow. And you might say, OK, you're probably safer. You just prepare for the worst. So let's take a look.

      So if you run the model on your unsteady state with the proposal already in place, fixed, you will see the downstream level increase from 118 to 121. So remember, our idea is no harm is done. So when you increase the flood level by three feet downstream, the risk increase quite a bit.

      So in this, you can see, well, old technology represents our best understanding at the time it was developed. It doesn't account for the complexity of the real-world scenarios. With more powerful computing and new models, we can now model the events more accurately and find more effective solutions. I'll turn it over to Jacob. He will show how 1D/2D modeling and [INAUDIBLE] grid can improve a FEMA insurance map for the city of Brookings.

      JACOB RISCHMILLER: And I'll be talking a little bit more on this project, on refining the FEMA flood risk maps, as a case study as well, during Autodesk University here. And this would be a beneficial model to look through. As highlighted in the red areas there, on the left-hand side is the proposed FEMA map that was being developed. And the city came and asked, what about our stormwater infrastructure? How is that being impacted?

      And then we came in and enhanced that modeling procedure from a surface 2D-flow-only model to a full 1D/2D model which incorporates that stormwater infrastructure into the modeling parameters, Then I will show a good case study on it later, on how significant just adding that stormwater component can be to our modeling softwares here.

      MEL MENG: OK, great. Yeah, so in summary, flooding, in many communities, is no longer a localized problem that can be easily eliminated with bigger pipes and ponds. It requires a fundamental shift in our strategy. Comparing with the old, localized, frequency-based approach, building a simple site model, now we have a citywide-based model.

      When a new development is proposed, instead of assuming no impact will be done downstream, we let the model to show the more realistic impacts. Instead of only checking the peak flow of the proposed site, we'll look at the changes in the whole city to make sure no harm will be done.

      OK. So in the following slides, I'm going to talk about the 2D model, the state-of-the-art method for modeling flooding for whole city is 2D modeling. When done right, it not only gives you more accurate street-level flooding, but also requires dramatically less time and effort to build than the traditional approach.

      Yeah, we already know how to deal with flood. FEMA has a whole program for it. The challenge we're facing at the moment is the FEMA map probably is outdated for your community, as we discussed, because it was done using a rather simple model and hasn't been updated in recent years. So the first thing we need to do is to develop a flood risk map. And today, the best way to create a map is using 2D modeling, as shown here.

      The model will directly simulate the flooding on the surface with detailed velocity and depth. It is not only a better way to model, but a cheaper and faster way to model a whole watershed at the city level. Building a 2D model is mostly collecting these data sets and loading them into the model. The days that you need to digitize each stream, each building manually is gone. I'll let Jacob do an animation of what 2D model is.

      JACOB RISCHMILLER: Here's a simulation of that modeling that Mel was talking about, is the green lines are all the stormwater network. And the blue is a rainfall event, a 5.7-inch rainfall coming on to-- this is the city of Brookings model here. As you can see, the darker blue is deeper rain and deeper flooding occurring. And how that interacts with the landscape is truly run off of the LiDAR surface, versus trying to digitize, like Mel was talking about, all the curbs and gutters and utilizing all of that information.

      It's really utilizing the surface to the best of its ability and show where the localized flooding comes through, so that residents in the actual community understand the duration of flooding as well. This is a key aspect when you're going into community and landowner meetings to where that flooding, we know, is going to happen. We just need to understand and give that visual to the residents, that it's 5 minutes, it's 10 minutes, on this ideal storm, versus them coming up after the project or after the event happens and say, I have flooding. And we don't know why.

      Well, we do know why. We have the data to back it and showing, OK, did we calibrate this right, then? Now it's a modeling calibration effort to where they're saying it's 10 minutes. We showed it for five. OK. We can do a little bit of manipulation and get that to be calibrated correctly, like Mel was talking about in that Tasmanian project earlier, as well.

      MEL MENG: OK. Thank you very much for sharing. OK. So In this slide, I'm just talking a little bit about why the 2D model is more-- takes less time to develop. As you can see, when simulating water on the surface, all you need are two things-- Topographical data, the contour lines, and land use information such as whether the area is paved or it is grass.

      Collecting this data has become significantly more accessible and affordable, unlike 10 or 15 years ago, when only government agencies could afford to fly large areas. Today, anyone can use a drone equipped with a LiDAR sensor to conduct their own survey at a reasonable cost.

      Traditional 1D modeling requires manually drawing flow paths and cross-sections, which is a subjective and time-consuming process. Even with high-resolution data, you end up with a rough model because you're only sampling at specific points and making broad assumptions. In contrast, 2D modeling automates the entire process. Once you lay out the 2D cells or mesh, the software automatically extracts topographical and land use data. And this approach eliminates guesswork and ensures consistency, regardless of who performed the task.

      The model is driven by data and not assumptions, leading to more precise and reliable results. So as I have shown here, you can see these lines, if you do it manually, with the 1D approach, you have to draw these lines. You have to extract all these cross-sections for each line. And when you assemble the whole model with the 2D, you don't need to do any of this. So software automates the whole process and understand what the land use and the topo looks like.

      So the next one I want to show is the rain on mesh because that's another important, new technology that can improve the accuracy and reduce the manual work. So let's imagine it is raining. A parking lot sees a lot of water rushing into a catch basin, while a adjacent field barely showed any water on the surface. So this highlights a fundamental question in hydrology. How much water will run off when it rains?

      So let's explore the evolution of hydrology calculations in the 1960s, constrained by the limitations of available land use, topo data and computer power. Simple methods, such as the rational method, was proposed. As a widely used method today, it hasn't changed too much over the years. Rational method is a good example. So it simplifies the process by focusing on a few key parameters. You simply delineate a flow path and calculate the time of concentration and then put it into a simple formula. So you don't have to deal with all of the complexity of the catchment.

      But today, with advanced computer programs and better data, we have moved to a distributed hydrology approach called "rain on grid" or "rain on mesh." Instead of broad assumptions, we now let each cell's data determine the flow, offering a more accurate and detailed model. This modern approach not only more sound, in theory, but also eliminates the tedious and error-prone steps of delineating subcatchments and flow path, making citywide models more efficient and reliable.

      As shown here, the rational method and similar method are like this. You had to manually draw this. You needed the path. If you want to add more details, you have to break it down into smaller ones and spend more time digitizing. But for the rain on grid, rain on mesh, you just lay the mesh or grid here. And the software automatically extract all the information needed to run the simulation.

      I would like to share a fascinating study conducted by a research group from MIT that recommended 2D modeling as a best flood risk assessment tool. Their goal was to develop a tool to help developing countries assessing flooding risks, as extreme events become more frequent. After reviewing existing tools and approaches, the MIT team recommended building comprehensive citywide 1D/2D models with street-level details.

      Here, we have a case study model for the city of Cambridge, where the MIT campus is located. The study simulates the flooding event for a 24-hour, 100-year designed storm in 2070, accounting for climate change. So you can see here are three different models. So the first model is just a 1D model with the [INAUDIBLE] hydrology just discussed and connected to a 2D surface to show the flooding extent. As you can see, comparing with others, it shows a lot less flooding within the city.

      And this one is just a 2D-only model. So this is relevant for developing countries. They might not have good records for their underground pipes. So this is a quick and easy way for them to get some rough idea of what that looks like. However, for cities like Cambridge, they do have a very good idea of where these underground pipes are. You can see, once you incorporated the underground pipes, they can show quite some benefits to reducing the flooding extent.

      So that's similar to what Jacob shared with us on the project he will present. [INAUDIBLE] the pipe in 1D/2D definitely helps. So this is a great study to demonstrate the different approaches and their impacts on results.

      So another thing I want to show is this bottom chart. So as Jacob showed, it's an animation. It's not just a static map. So in reality, the water goes up and down. So this chart shows that change. So this is the duration of the storm, 24 hours. And this is a percentage of the city having flooding issues.

      One thing I really want to show is you can see here, after the peak of the storm, a lot of the city were underwater for a while. And one stop is still underwater. So these detailed information, how long a building were underwater, is critical when we're estimating the risks. And here is a website I really wanted to share with you. So this site hosts all technical reports related to the Tasmania flooding project we shared at the beginning of the presentation.

      I'd like to emphasize that 2D modeling is not a new or experimental approach. It has been successfully utilized by many cities worldwide, to address flooding issues. It's a proven method backed by advanced technology, ready for adoption today. Next, Jacob will discuss the funding resources available for flooding projects.

      JACOB RISCHMILLER: Thanks, Mel. Like Mel said, I'll be talking about the funding sources. There's multiple different funding sources available for each community, as well as different levels of grants available. So there's federal-level grants. There's state/local grants. There is the local grants and municipalities that may fund sustainable future/climate change modeling.

      One thing to point out from the get-go is the Environmental Protection Agency. The EPA has established a finance center with four goals in mind. The first one is research, identifying those solutions to make communities meet climate resiliency. Giving advice on how to support our technical people, the engineers and modelers that are available.

      Three is a innovate, finding best solutions, developing those solutions, working with stakeholders in that portion. And then four is network, creating those relationships with our partners, with engineers, with other firms, government partners to find better solutions, talk about other ways to get funded.

      Another source is FEMA and their BRIC grant, so they're Building Resilient Infrastructure and Communities Grant. They do have funding out there that aims to support communities as they build capacity and capabilities. They have a greater knowledge of infrastructure that could be implemented and how is it impacted. One thing to note, in '23, that is a competitive project or grant process. But they did total $674.5 million of funding through this grant.

      The next federal funding and last federal funding I'll discuss today-- this is not the extensive list of federal funding. So these are just the top three that-- or the top two that I picked here is from the National Resources Conservation Services, the NRCS, and the Watershed and Flood Prevention Operations program. This grant aims at watershed-wide approaches and not just site approach. So really looking at the larger scale of the entire watershed that's coming to one particular location and not just that one location, how does that-- or one city and how does that impact.

      So if this community is along a river, they really want to look at the entire river watershed, from that point, and what's feeding it and not just what's the city infrastructure in it as well. The main purpose of the grant here is for flood prevention, watershed protection, public recreation, public fish and wildlife, agricultural water management, water supply industry, both municipal and industrial, as well as water quality management.

      One caveat to this funding of the WFPO is that the NRCS has to be actively working on projects and the public benefits, especially in the agricultural benefits market-- they have a whole ranking of matrix system-- has to be greater than 20% for the project to be eligible for this funding. So one thing just to look at and talk with your local representation of the NRCS department, to see if you can meet those benefits in order to go after funding.

      Off of the federal and going to state, there is a lot of state climate plans that are being developed as we are figuring out how climate change is impacting the bigger market. Back in 2006, the climate plan started to occur, but they really focused on greenhouse gases and not so much climate change or climate resiliency. This has been shifting as we progress through the age, the years here.

      And now, in 2022, they're really focusing on more of that climate resiliency and multi-facets, so looking at not just water, but how is the economy being affected to it. How is production being affected? How is industrial transportation-- each facet, they're kind of looking at, which I'll dive into, here, the Minnesota plan. Because that's where-- my company is more based out of the Midwest. In particular, I'm in Minnesota.

      Our plan is broken out into six different goal areas. First goal is clean transportation. Second is the climate-smart natural and working lands. Third goal, which I'll go into more detail here in a little bit, is the resilient community. Fourth is clean energy and efficient buildings. This is healthy living in communities, which ties back a little bit into goal three. And then sixth is that clean economy, looking at that bigger impact of how is the climate changing our economy as well.

      So like I mentioned, focusing on goal three, they did create subcategories within this goal to really make it a reframed goal work-- framework for them to build upon. Within that, it's climate-smart communities, healthy community and green spaces, especially in the water resource world, and then resilient buildings, infrastructure and businesses.

      I'll go into a case study. Here is an example of a Ford site in Saint Paul, Minnesota. This project is 120-acre development that was used by the manufacturer facility, Ford Motor Company, back in the day. They did start in development negotiations of wanting-- it was all impervious surfaces, that 120 acres. And worked with our local watershed district and the city council of how can they make a different impact, knowing that this site is going to be a rare opportunity within the community. And how can we bring the community back into the water resource components to it?

      So the first zone is that urban zone on the very top portion of the development. It is really more looking at water quality and green infrastructure reductions. And then the second zone is that transition zone. How can we bring the community back to the water resources, especially-- they made a pretty little pond, as you can see there in the right-hand image, to really bring that community into the water, into this pond area. All clean water coming into it from this 122-acre development.

      And then the third zone is the more natural component zone. It is how can we replicate the more natural setting in an urban landscape. So funding of this project came through the development. There was some local funding investments as well. But primarily, the developer saw an opportunity that they could localize and see a change within this entire 122 acres, to develop, as well as create, a better community area, green space and bring the community back into the residents.

      That was just one prime example of how climate resiliency can pair into a project development project. Also, Minnesota here, we have the Minnesota Pollution Control Agency. And a part of that is climate adaptation resources. They fund almost 3/4 of $1 million worth of funds on an annual basis to really look at planning and implementation of climate resiliency.

      So part of that, ISG has been involved in three municipalities that were all awarded grants through that program to look at today's flooding, as well as future flooding. How does that work? We work with both of those-- all three of those communities and really seeing the forecast of, OK, we know we need a 1D/2D model. As we believe and we've talked about today, that's the best modeling we can do.

      We're a big user of ICM and how integrated that is in-- for rain on grid, as well as the meshing system and triangulations that it uses throughout the surface. So those models are a current 2024 model, rainfall, as well as trying to do a predictive model at 2050 using all of the climate changes that are occurred.

      So those communities I mentioned are three of them. Those are the red dots on the screen here, that we're doing the active modeling on, for right now. The three blue dots that are on the screen are more master plan models. As you can see there, Brookings is on that screen, that I mentioned earlier. Those were just sitting at today's rainfall and today's storm events and weren't part of the scope to look at future rainfall. But still, a citywide model was developed for each of those cities.

      The ones in red, like I mentioned, are the community resiliency grants. Those are all small grants or-- not small grants, but small communities that didn't know where to start. So each of those communities came to ISG, knowing that there's flooding, based on what I talked about earlier, in the intro. Rainfall is getting wetter. We're getting more rain. They wanted to see what it was to do-- what is the impact going to be in 2050. How is that rain going to actually affect the community? And how does that work?

      So they came to us, asked, where do we go? How do we start? So we ended up researching, found the MPCA grant, typed up a memo-- a grant application for them, so that they could submit to the MPCA. And was eligible to get those fundings to implement this kind of modeling, with a small percent match. I believe it's a 10% match on each of the communities. So it's a very small investment, on them, but it's a 90% return that they get of matched funding for it.

      So the one modeling that I want to show you today is really the Eagle Lake, the 3,000-population city, and how their community is developing this. I'll go back one slide. As you can see, that does have two dots. The blue dot was a 2017 model that we developed, on the left-hand side here, to really understand stormwater impacts. They did have some rain events occur, that they just had a lot of flooding happening. And they didn't know the full impact of what was happening throughout the entire city.

      They hired us on that model, just to understand what was happening, versus the climate resiliency grant. Wanted to do that, which is on the model on the right, is the existing-- one caveat, this is all preliminary results. It's an active project that we're working on right now, so these results may change in the future. But they also wanted to see, if we do more development, what is the 2050 model going to look like? And how do we set the city up and this watershed up for success, to limit flooding within the landscape and not have additional flooding? We're not looking ahead. We're not in 2050 and looking backwards.

      One key area that I want to point out here is on the western side of each of these screens-- or each of these screenshots is a comparison between the older technology, in 2017, and the new technology, in ICM, of that rain on grid and meshing. In 2017, those two open ditch channels were modeled as a 1D link and 1D channel, which limited the flow into a channel and then capacity, versus the ICM model is all surface-defined model allowing that LiDAR surface and what we did for topographic survey to convey that water downstream.

      And you can see a lot more flooding in that particular instance than you can in 2017. And what that does is really impact that those are both rural farms, crop and soybeans-- or corn and soybeans, I mean, and how do they integrate within the city and how much water do they hold within their landscape and the city actually takes on.

      So another model here, a video, so you can see, really, the impact of this modeling. The simulation here is black is all the city storm sewer. This is the 100-year event. The blue dots are all the nodes. So where does water come in and out of the network and spill onto the 2D surface and really showcase that interaction between the 1D and 2D and the duration?

      These residents here were also part of that June storm event. So these are results that are being shown as we speak. And they're getting input of we had a similar event back in June. How did this line up with the residents and their actually, physically seeing this water? And how does it work?

      As you can see, there's a lot of flooding in their low grounds, in their ponds, some flooding in residences, but not as much as some of the previous videos I've shown. But still, that dynamic between the results and modeling versus the visuals is a huge aspect to bring to the communities, so that they can truly see and visually see it with their own eyes.

      MEL MENG: OK, great. Yeah, thank you very much, Jacob, for sharing those nice-looking animations and explaining the-- sharing with us the success stories you bring to these communities in your area. So I hope that, by this time, you already agree with us, to build resilient and sustainable communities with better technologies.

      So as we can see, extreme storm events are becoming more frequent and costly. And we need to adopt a paradigm shift to risk-based flooding management. And 2D modeling is the best available technology today, building citywide models with street-level resolution, evaluating impacts, on the city level, and taking a risk-based approach to evaluate the flooding impacts.

      So before I let you go, I just want to thank the people who helped us with this presentation. So Joe Kirby from Woodard & Curran, we used the [INAUDIBLE] comparison slides from one of his work. And Katerina Boukin from MIT, that's the Cambridge study we showed here. And also want to thank Alex Grist from Autodesk and a colleague who reviewed this presentation.

      OK. Thank you very much for joining us today. And I hope you're as excited as we are, ready to get started to help make a difference, to address the extreme storm events, storm events and the flooding it has caused. Thanks.

      ______
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