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Refining FEMA Flood-Risk Maps Using Appropriate Technology: A Case Study of Brookings, South Dakota

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Description

In updating the Master Drainage Plan for Brookings, South Dakota, ISG faced challenges reconciling flood risk maps with community experiences. Despite a doubling of the flood-risk area, doubts arose due to discrepancies with historical records and incomplete evaluations of existing flood-reduction efforts. Using InfoWorks ICM software, ISG employed advanced modeling techniques to generate a more accurate flood map, enabling prioritization of mitigation projects. Stakeholder engagement ensured realistic modeling, leading to actionable results and strategies for water quality improvement. This approach underscores the importance of informed modeling in building resilient communities amid climate change uncertainties.

Key Learnings

  • Learn about how InfoWorks ICM software's advanced modeling capabilities can provide an advantage to master drainage plan studies.
  • Learn about engaging FEMA and communities early to foster active involvement and communication, addressing climate change uncertainty.
  • Learn how to use data tracking, visual flood mapping, and enhanced efficiency when modeling flood scenarios.

Speaker

  • Jacob Rischmiller
    Jacob holds a Bachelor of Science in Civil Engineering from Minnesota State University, Mankato, and has been with ISG, a nationally recognized architecture, engineering, environmental, and planning firm since 2015. As the Water Resources Practice Group Leader, he brings extensive expertise in watershed modeling, planning, and policy discussions. Guiding a team of skilled engineers, he fosters an environment of critical thinking and project rationale, resulting in thoughtful and tailored solutions to public and private clients. Specializing in surface water design and implementation, he identifies opportunities to maximize water quality and ecological diversity to mitigate impact on natural resources. Jacob's proficiency in hydraulic and hydrology modeling, using Autodesk InfoWorks ICM/XPSWMM software, is a key component of his work, encompassing projects from stormwater mitigation to wetland restoration. He will present ISG's advanced InfoWorks ICM modeling and discuss how his team reconciled flood risk maps with community experiences to create a Master Drainage Plan for Brookings, South Dakota.
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Transcript

JACOB RISCHMILLER: Welcome to my presentation today. I'll be talking about refining the FEMA flood-risk maps using the appropriate technology. I want to first acknowledge and thank the entire project team for this effort, especially the city of Brookings and their staff that contributed to this product as well as their master drainage plan. I am Jacob Rischmiller. I lead our water resource group here at ISG. I've been in the industry for nine years and worked over 300 projects, all from a planning stage, concept level, all the way through design and implementation within those projects.

ISG is a full-service firm based out of the Midwest with clients that are nationwide. We have 14 offices in total with 12 business units that break up the company. We do everything in the A&E world except for the geotechnical services and specialty services as well. Within the water resource world, I primarily interact with our water business unit, public works business unit, as well as the sports and rec business unit. ISG, like I said, is a multi-service firm. In the water resource, we use Infoworks ICM on a daily basis.

So we have 12 total licenses to an additional two XPSWMM licenses that utilize this modeling capabilities in both the rural setting on the left hand side here, left hand screen, as well as the urban setting on the right hand side. The rural setting and modeling, we really focus on the inundation times and how long that flooding takes on the surface within the Midwest, especially the upper Midwest, to where crop production is very prominent and that duration of inundation is a key factor to how much yields all of the crop products and crop production will handle.

On the other hand, we do dabble and do a lot of work in the urban setting as well. As you can see on the right, here is a screenshot of an urban model, that I'll be talking about a little bit later today, on all the buildings that are interacting with the flooding events that are happening, as well as the main ditches and culverts and how does that all interact, all in one view, to get a full picture and holistic approach on how we model. I do want to point out I do have another presentation with Mel Meng on climate resiliency and urban sustainability. So if you've got additional time, please go check that out.

Today my objective is to show these three lessons learned throughout my presentation. The first lesson is how ICM advanced modeling capabilities can provide advantages to massive drainage plans and massive studies. The second lesson is how to engage FEMA in the community to foster an active dialogue between both the modeling as well as the results of that modeling. And lastly, the third objective here is how visuals and data tracking can really enhance the efficiency within these models and how we really develop the models as we progress through the modeling.

First, I would to set the stage of where in the world we are. Brookings is located in the Midwest, as outlined in the black, and the yellow is the city of Brookings' approximate location. It is 20 miles to the west of the Minnesota South Dakota border. The city has a population of 23,000 people and is home of the largest secondary school and University of South Dakota State University. The city is located in a unique position that's surrounded by two creeks, Six Mile Creek to the northwest, Deer Creek to the east, as well as the Big Sioux River.

So flooding is a critical aspect to understand for the city, and how that flooding will impact their city storm sewer, as well as the residents and flood insurance. So this project really started as a flood map update. On the left here is the original flood maps for FEMA, FEMA flood maps and insurance maps, that the city and residents would have to obtain by. The proposed map on the right is the updated proposed draft map, with the yellow and blue really encroaching in the city limits, and showed additional flooding and additional insurance requirements gonna be met by all of the residents.

So that's where this project really started from and adapted into a master drainage plan study to really understand the entire city scope and how does the city interact with both rivers and creeks as well as flooding locally within the city limits. So you may be asking, why is there a big difference between the original map, back in the FEMA maps, and the proposed FEMA maps? Well, really, it has to do with the modeling differences.

The original maps were developed based on a one-dimensional steady-state model. That is really just taking the channel and cross-sections of the creek and the rivers, and sending flow down it and developing a flow regime and flood extents from there, versus the updated FEMA maps are actually taking the LiDAR data and topography data that is current as of the modeling that was completed.

So this is a good example here is on the left is more of the results that you would see out of the original HEC-RAS model versus the right is really utilizing that topo, that LiDAR data, to convey the flow down the channel as well as any backwater channels, or conveyance areas, that would be occurring based on the rain event here.

So the city saw those big differences, like I showed earlier, and really wanted to make sure that flood extents was correct. They invested their own money based on their stormwater fees and distribution, that I'll go into later, to develop a full, in-depth, one-dimensional and two-dimensional model for the entire city. Here are the results. The one on the left, the images on the left here, that I'll be going through a couple of different models, are the draft FEMA maps versus the image on the right is actually the ICM map.

As you can see, there's a pretty substantial difference between where the flooding was occurring, how much flooding had happened, as well as that encountered how much insurance would actually have to be within the city, and updated flood insurance for residents within the city. So really that conveyance of the stormwater infrastructure on the ICM model of the 1D, 2D model really made that difference from a 2D only model to a fully one-dimensional and two-dimensional model, and where that water is going first versus just spilling over land.

This next example here is a unique one to where it's a strip mall and a bigger building area on the left hand side of both of these maps to where the flooding that was occurring would have encompassed an entire building, or a couple buildings here, versus the technical and actual data in our ICM map show the flooding around the building and not encompassing the entire building. Because that is not actually representing what is truly happening out there with the HEC-RAS model.

And the last one that I want to present here is really of that university campus and how much difference is the modeling actually showed within the regular parking lot of the city or of the infrastructure. So understanding how does that stormwater drain, how does that function, and how quickly that functions is a pretty key aspect to understand, especially the student and the student population that would increase, where that goes through and how does that interact with each other.

If this modeling effort wasn't obtained or the city didn't invest their resources into it, there'd have been a lot more residents having to purchase flood insurance for their own properties, which would have increased costs for residents within the entire city. So like I said, the original plan was that just the FEMA stuff, just looking at their FEMA map updates. But the city saw a bigger perspective and opportunity to look at their entire master drainage plan within the entire city limits and show how can we utilize this 1D, 2D model to the best of its ability.

Part of that plan was to develop and reduce flooding in key areas and strategic areas for the entire city. So that was part of our goal. Another goal, sub goal, was to enhance the water quality and recreation and aesthetics within the city limits. Those were some of those key concept plans that we developed. As well as within developing those, really focused on updating their modeling platform that was done in 2008 via EPA SWMM model and conditioned our new model to rain events that have actually been occurring.

Part of our recommendations at the end of this entire plan was recommended concepts for each of these projects that we looked at, revising the city's stormwater fees. I'll get into more details towards the end of the presentation about what their stormwater fees entailed, as well as developing new standards and inspection protocols for all of the stormwater ponds and infrastructure throughout the entire city.

As you can see on the right is the precipitation trends in Brookings, South Dakota. In the 1900s, we're about 17 inches of rain versus now in 2020, we're above 25 inches. So an increase of over 25% in the last 100, 120 years have been occurring. So flooding is being more and more critical with climate change and with other resources changing and adapting. The city saw this and wanted to invest their money and to understand what can they do within the city limits, and what projects can they do, and develop a capital improvement plan for reducing flooding for their residents.

First, I want to take you through some of the modeling updates and how we develop the new model converting EPA SWMM into ICM and how that function, some of the data analytics behind it as well, and really show you the complexity of these models and how much data is truly in the model itself. So first, the EPA SWMM model here, as you can see, it's laid out pretty simplistic. You have catchments laying out throughout the watershed. You do have some pipe networks, and some routing of these pipe networks, and some very small, little storage basins and culverts to utilize that infrastructure.

But that's about all of the EPA SWMM model. There is parameters in each of these areas to calibrate rainfall and conveyance of the system, but it doesn't take into account that LiDAR and 2D surface just like ICM would. So here's that same area of the EPA model into InfoWorks ICM here. So as you can tell, there's a lot more layers, a lot more conditions within this modeling software then that basic EPA SWMM model is.

Luckily for us, each of these layers can be turned on and off. And we can create more themes to really validate and compare different models, different results, making sure we have all of those data to accurate as the best we can. In developing those, we developed some standards working with the city of how do we calibrate, how much time do we put in investing into spatial data referencing, and how does that all work? Impervious areas was a key aspect within the entire city. I'll go into more detail about the impervious areas and land use in the future in a couple slides here.

The subwatersheds were delineated throughout the entire city. These are your basic delineations based on just the elevation data that's available and what's going to what storm sewer network. Land use is also being developed or was utilized. The building footprints were all utilized as well. As you can see it pointed out here, that is all identified and carved out using spatial data. The storm sewer network was utilized in our modeling.

Throughout the model, there was some manipulation and assumptions made as the city did not have all of their stormwater networks laid out appropriately. And then we used some concept designs and level zones, mesh level zones, within the modeling software to really show future scenarios, future plans of what can be done to help out flooding and reduce flooding throughout the entire watershed. So like I mentioned, their storm sewer network was decently or pretty well developed, but didn't have all of the information.

So the blue here on the chart is their missing data versus the orange is the available data that they had available, or they had with already in their GIS system. So really that missing data, we work with the city, hand-in-hand, to either go and find that data and actually go take shots, understand what's happening on it, or made some assumptions on pipe condition or the year and based on other values and other networks around that area.

So it was a hand-in-hand and then wrote a memo on what links and what nodes were assumed and what is not assumed, so that we can really enhance that in the future. And when the city does inspections, they can go off and check off and make sure that the data that was used for our modeling was assumed for our modeling or is the actual data out there.

The Autodesk team and engineers that we work with to vet some of this stuff really played a key factor in this, as they have wrote scripts for ICM to really showcase what areas you're missing data, what areas are offset. Some assumptions can be made throughout that scripting process to fill in missing parts of the data as well as using data flags within the ICM software.

So we understand now, and in the future when we have to go back and we look at it, that this data link or this pipe was assumed to be an 18 inch or assumed to be a 6 inch or whatever size that might be, versus seeing the data and not having any of that context when it's passed on three or four different engineers. Another key aspect, like I mentioned earlier, is the LiDAR data and that land use data that we developed or that we utilized.

An example here is the city invested back in 2019, a very heavy amount into a full 8 centimeters vertical accuracy LiDAR data for the entire city aspect. As you can see, it captures all of the runways, walking paths, all the trees and shadows of the trees, so it's very detailed and very thorough throughout the entire city. That really utilized in two aspects, one, for this modeling procedure, and two, impact their stormwater fees. So the process of their stormwater fees I'll talk about later.

But utilizing this data compared to the publicly available land use was another key aspect of enhancing the modeling capabilities. So the right is more of that publicly available data on land use, as you can see on the left is that LiDAR, really defined and precise data. Here it's more of an assumed on highly intense versus the low intensity and doesn't give you that context of no, this is actually grass, this is pervious, versus we're just assuming it's this and not really very accurate detail.

So the city is broken up into five watersheds, five unique subwatersheds, that drain around all the areas into either Deer Creek, the Big Sioux River, or Six Mile Creek. So really, the center point of the city is almost the high point within this area of the landscape. The watersheds that we really focus our efforts on was the South Dakota State University or SDSU watershed, the Central watershed, and the Medary watershed here.

One interesting aspect that I want to point out is the SDSU watershed flows into Six Mile Creek to the north, and that actually flows to the southwest through the edge of the Central watershed, and impacts the stormwater within the Central watershed. So the key aspect that we really had to understand was that central water impact of stormwater that came from that SDSU watershed. We did break these up into two subwatersheds versus one because of the sheer size of the Six Mile Creek watershed coming throughout that landscape.

Each of these subwatersheds had very unique characteristics to it that I'll be talking through and talking into more complexities of each of the modeling. So the SDSU watershed, the one very to the north, is approximately 2,200 acres in size, has 66,000 feet of pipe, 20 stormwater ponds throughout the area, and pretty even distributed of land use from residential to green spaces.

The map on the right here shows the blue is the inundation based on a major storm event of 5.7 inch rain in 24 hours, while the green is actually the city storm sewer pipes, and these yellow arrows is really where the conveyance of the flow goes. So you can see back in the upper portion of the watershed, there's not a lot of flow or a lot of flooding within the residence areas. But once you get into the main conveyance system and into the channels, you can really see the flow regime and flow inundation expand out and get wider as you bring in more watershed.

This watershed, like I said, is a little unique as it's pretty large. It's the smallest of the three watersheds, but it is also has the most impactful to the university. The modeling dynamics and complexity of the model has 906 nodes, 776 pipes, and 265,000 elements. So that terrain meshing, as you can see in the actual mesh zone itself of ICM, plays a key aspect of how many elements we have and really shows where that flooding can occur and where it can really be a hillside.

The central area is also a relatively small watershed at just around 2000 acres in footprint, 75,000 feet of pipe, has four stormwater ponds throughout it. And the land use of this watershed is mixed between residential and airport. So on this watershed, a pretty key aspect was to understand the flooding that occurs around the airport, as well as what comes through Six Mile Creek and how does that impact what would happen in the airport. This watershed also has some industrial sites next to airport as well so that it could-- that understanding was key as well.

This watershed has 912 nodes, 822 pipes, and just over 260,000 elements throughout the watershed. As you can see, there's more dynamics of the elements, which is every triangulation throughout that 2D zone. But the watershed isn't as large, so it really lessens the amount of elements that are there. The Medary watershed has a key, a unique factor as well. This watershed is 3410 acres in size, 101,000 feet of pipe, 52 stormwater ponds, and is predominantly residential land use.

The key aspect of this Medary watershed is the wetland complex to the southern portion of the watershed, and how's that complex really inundate the flooding that is happening upstream, as well as how does the city storm sewer interact with that flooding? Now, the tricky part when we were evaluating proposed options in this watershed, was to not starve the wetland of water, but also providing enough water and enough storage to enhance that wetland complex for the best of its use and best of its ability.

The 52 stormwater ponds that are in this watershed, which is the largest amount of ponds that are there, are really based on the development. Every development had their own stormwater pond to really capture what was happening throughout that area. As you can imagine, this one is a very complex model as it's 1065 nodes, 987 pipes, and just over 290,000 elements. So quite a bit of elements and quite a bit of topography changes throughout the entire watershed as you really got to understand the roads and the characteristics of each house for that 2D modeling and 2D landscape.

Another key aspect that we utilized within the entire scope of this drainage plan was the pipe capacity analysis within ICM. The stormwater pipe capacity really gave us a nice visual to really to forecast where can we actually implement and increase conveyance within the system or where is it OK to where it will handle it for now, but they know in the future they're going to have to do something. So here on the map is the color gradients. This green is adequate capacity. This is a five year storm event.

The orange is potentially inadequate, it was on the edge of if it would be adequate or not. And the red is not adequate at all. So you can see here that there's some areas that are green, then we hit some orange, and then a red. That pipe itself is the restricting factor within that pipe channel and the pipe network. As you can see over here on the eastern side, this entire area is potentially inadequate for the current capacities that they need in themselves.

Another key aspect within ICM and the visuals that can be presented are the modeling videos. This here, the green is their stormwater sewer network. The blue is your rainfall depth. And really what we're playing here is the duration and inundation times throughout the landscape. It's a short video, but it really forecasts and shows you what residents could get flooded and what residents do not have to worry about the flooding.

The interaction with the community was a key aspect to show this so that they understood that some of the flooding is going to happen, but not all of it's going to be in one spot. It's spread throughout the watershed. As well as residents up in the upper portion of the watershed, they should experience some as maybe their pipe capacity is too small. But it's for a limited time, limited duration. Maybe it's 10 minutes, maybe it's 30 minutes, but it's not there for weeks, so that they get that visual as well.

So you may be wondering, how do we quality assurance and quality control these models and really validate what kind of flooding aspects occur throughout the watershed and throughout the city? This is where we utilize drone services. The city of Brookings, after one of their rain events, went out and flew a drone in some strategic areas that we wanted to validate modeling. On the lower left, we were concerned about this flooding area and how close it was getting to these residents that were around this development.

So getting this picture, and then showing the modeling results that are right next to it, and comparing them side-by-side was a key aspect to the project, versus the upper right is really that we knew it flooded and we knew how long it would flood there as well. The community, we brought the community in from the initial start of the meetings and an initial start of the project. They did set up a subcommittee.

That committee involved city staff, the university stakeholders, their municipal utility officials, community representatives as well. The municipal utilities officials were really focusing on that stormwater revision fee that I'll go into at the very end. We did have three town hall meetings throughout this planning process that really opened it up to the public and provided additional feedback. The online survey that we had enhanced those town hall meetings to allow residents that weren't actively there to be able to participate as well.

So that was a lot of the modeling portion. Now, I'm going to briefly talk about their priority project matrix and how do we utilize that to the best of its ability. During our project plan, they wanted to revise how do they look at each individual projects on a very non-biased weighting scale. So we ended up looking at their previous categories and how they weighted them and recommended some changes and added a column to identify multi-use.

So if a project was benefiting not just flooding, but also benefiting water quality and the aesthetics, it got a higher ranking and higher score than a project that would just benefit flooding that wasn't previously being captured in their previous categories. The weighting system also played a factor into it, of how much weight do we want each of these categories to hold. So when you score the project, it gets compounded.

So let's take an example here of citizen safety as an example. Each category, for example, has a weight of 5. Well, one project, if we're doing a pond or a storage that reduces flooding over land and reduces a road for overtopping, gets a score of 5. Well, you multiply those two and get a total ranking score for citizen safety of 25. You do this for each of those categories, like I mentioned earlier, and you really get a non-biased score system of that project.

So then you're capturing that project and not on a non-biased setting, and not unintentionally ranking it higher because you want that project to go. When we looked at these plans and looked at our concept plans, we really strategically planned on three areas. One, to provide storage upstream of any flooding location. Two, to increase the conveyance of that flooding area. And three, to provide storage downstream of where we can increase conveyance. So really put this into perspective is this concept plan here.

It is on the SDSU watershed, so the flow goes to the north. We really wanted to phase this from a construction aspect backwards. So you provide that storage downstream, provide that capacity for that system, increase your channel capacity in the middle portion, so it gets more conveyance downstream as well as take more of that overland flow into that channel. And then the last phase here on the very upper portion is increase the culvert capacity to reduce flooding in the resident area. So that really harnessed everything together and really put it all into perspective of yes, this is a better approach than what was previously done.

Funding was a big opportunity. As the city wanted to and had a previous method of their land use and zoning flooding, or zone funding source, to where the city is in a special area to that they can do special assessments and tax every property based on their land use and zoning, to a new methodology using that LiDAR data that I talked about earlier in accuracy to really capture the impervious surface contribution to the stormwater infrastructure. So on the right here is that percent impervious cover and on the left is really the land use zoning.

And you can see just in this one parcel in one area, how much difference the land use is. The LiDAR impervious cover is from the western part of the SDSU campus to the eastern part. And each of that really gives a bigger picture of how does that parcel utilize the thermal structure. So for a real in-depth example here, this property on the left hand side is more of an industrial property that encompasses 51 acres in size, 13 acres is impervious, so the ratio of that is 25% impervious.

Well, their current bill, because of the size of that boundary, was $23,000, just over $23,000. But in comparison to the property on the right, it's 12.8 acres in size, has a similar impervious acres of 12.1, so it's 94% impervious by to the acres. Well, their current bill was almost $6,700. So how is it fair to have a majority of the land being impervious to have a smaller bill that contributes more stormwater than a larger property that contributes less stormwater?

The city was trying to figure out an equitable way to capture how do we do this on a parcel by parcel basis and be fair throughout the entire city? City partnered with a financial firm to really enhance this and make sure it was credible, and approachable, and consistent throughout the entire city. So that financial firm also helped analyze multiple different methods throughout the planning efforts here.

The city really used that impervious data and land use data that was captured in the 2019 LiDAR to enhance this aspect and really focus on what is green space? What is pervious versus non impervious or impervious? And what is contributing to the stormwater? So as you can see on the bottom of the blue text here is really more of that proposed even distribution based on the impervious acres for each of the parcels. So it's a lot more fair for an industrial site that's got a lot of green space versus a strip mall that's got the same amount of impervious areas.

City does have plans to update this on a regular and frequent basis based on either new permits that come in for the site or potentially updating LiDARs on an annual or regular basis. So lastly, I want to recap on all the three lessons that I've talked about today. As you can see in the picture on the right is the Infoworks ICM modeling of the SDSU area, and how that model really enhanced the abilities and capabilities of the master drainage plan and the studies that were provided for the city itself.

Secondly, engaging the FEMA and communities early on and often throughout the planning process addressed not only community concerns about the project, but also addressed their realities. So they made sure that flooding event was actually real, be like, OK, I can recall back in 2018, 2017, that water did get very close to what you're representing and showing that throughout your entire model. That really helps validate our concerns of are we overestimating flooding? Are we underestimating flooding? What is truly happening and how can we tweak modeling parameters to make sure we capture that entirely?

And lastly, I want to show the data tracking and visuals. These modeling videos have been a huge aspect of the work we do at ISG here and be able to show and validate all of the modeling and get residents to really visually see it. As engineers, we really understand it and need to know the numbers and the data behind it. But that data only goes so far. These visuals really enhance all of our capabilities and show the efficiencies of what our modeling softwares are doing, how powerful our modeling softwares are, and enhances us as engineers throughout the entire project.

So thank you, everyone, for watching my presentation. I hope you got some beneficial aspects of the takeaways from this as well.

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We use Tealium to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Tealium Privacy Policy
Upsellit
We use Upsellit to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Upsellit Privacy Policy
CJ Affiliates
We use CJ Affiliates to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. CJ Affiliates Privacy Policy
Commission Factory
We use Commission Factory to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Commission Factory Privacy Policy
Google Analytics (Strictly Necessary)
We use Google Analytics (Strictly Necessary) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Strictly Necessary) Privacy Policy
Typepad Stats
We use Typepad Stats to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. Typepad Stats Privacy Policy
Geo Targetly
We use Geo Targetly to direct website visitors to the most appropriate web page and/or serve tailored content based on their location. Geo Targetly uses the IP address of a website visitor to determine the approximate location of the visitor’s device. This helps ensure that the visitor views content in their (most likely) local language.Geo Targetly Privacy Policy
SpeedCurve
We use SpeedCurve to monitor and measure the performance of your website experience by measuring web page load times as well as the responsiveness of subsequent elements such as images, scripts, and text.SpeedCurve Privacy Policy
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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Improve your experience – allows us to show you what is relevant to you

Google Optimize
We use Google Optimize to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Google Optimize Privacy Policy
ClickTale
We use ClickTale to better understand where you may encounter difficulties with our sites. We use session recording to help us see how you interact with our sites, including any elements on our pages. Your Personally Identifiable Information is masked and is not collected. ClickTale Privacy Policy
OneSignal
We use OneSignal to deploy digital advertising on sites supported by OneSignal. Ads are based on both OneSignal data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that OneSignal has collected from you. We use the data that we provide to OneSignal to better customize your digital advertising experience and present you with more relevant ads. OneSignal Privacy Policy
Optimizely
We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
Amplitude
We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
Snowplow
We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
UserVoice
We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
Clearbit
Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID.Clearbit Privacy Policy
YouTube
YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

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Customize your advertising – permits us to offer targeted advertising to you

Adobe Analytics
We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
Google Analytics (Web Analytics)
We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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