Data-Driven Response to Flooding, Erosion, and other Natural Hazards

[00:00:00] Laura Rankin: Welcome to the July edition of Water Data Forum. My name is Laura Rankin. I'm on the communications team at Cleveland Water Alliance. If you haven't joined us for one of these sessions previously, Water Data Forum is a virtual series presented by us at the Cleveland Water Alliance alongside the Water Environment Federation and the Midwest Big Data Innovation Hub.

[00:00:22] The goal of this series is to demystify the complexities of water data for both seasoned professionals as well as the general public by engaging experts in an exploration of utility, private sector, and research approaches to collecting, managing and measuring water data for impact. We're super excited for today's conversation on stormwater data in the context of natural hazards.

[00:00:48] We are going to begin with a curated panel discussion followed by a Q&A at the end. So please do feel free to pose your questions throughout today's conversation using that Q&A function in your navigation bar. We will also be recording today's session. So all registrants will receive the link to that recording in your inbox.

[00:01:09] And it's also going to be accessible on the Cleveland Water Alliance website, as well as our YouTube channel. So if you have any colleagues that are interested in today's topic and couldn't join for whatever reason,  please feel free to share that with them as well. So with that, it is my pleasure to introduce today's moderator, John Billotta, and John will be facilitating today's discussion and introducing our fabulous panelists. So take it away, John.

[00:01:37] John Bilotta: Great. Well, thank you, Laura. And thank you everyone for joining,  this afternoon. We're pleased to have all of you. A little bit about myself. So I am the senior research extension coordinator here at the Water Resources Center at the University of Minnesota on the St. Paul campus.

[00:01:53] And I lead our urban stormwater research program. And we have a huge portfolio of stormwater research projects that we're doing. To help us tackle some of the issues that we have with controlling minimizing the impact of urban stormwater across the Minnesota landscape.  And so I'm pleased to be talking about this topic today and how technology and data can help us both prevent impacts.

[00:02:25] But help us mitigate and minimize some of those impacts as well. And so,  I'm pleased to be joined by a great group of colleagues today that I would like to introduce.  1st, we have Donna Friedman with us. She is the watershed team leader. From the Northeast Ohio regional sewer district. Welcome Donna.

[00:02:45]  2nd, I don't think he's with us right now. I think I saw an email. He's having some technical difficulties, but Joseph Wartman hopes to be with us. He's the director.  the Natural Hazard and Disaster Reconnaissance Facility located  at the University of Washington. And then, we also have with us,  Lilith Yegahiazarian, I hope I got that right, Lilith Professor in Environmental Engineering and Science at the University of Cincinnati.

[00:03:19] So welcome, Donna, Lilith, and we hope Joseph can join us here in a couple minutes. Thanks.  I just want to remind everyone if you have questions or comments to put those in the Q&A panel,  as we proceed with our conversation this afternoon, and I do hope it's a conversation as well. So oh, there he is Joseph Joe. Welcome.

[00:03:43] Joseph Wartman: Oh, thank you.  It's good to join you on zoom. For some reason I had a, sorry about that. I had another link and I'm much better with zoom because Skype just doesn't work on a Macintosh. Oh, great. Well, I'm sorry, but I'm happy to be with you.

[00:03:59] John Bilotta: Great. Well, I was just going to kick us off here with a little bit of framing and then we'll come to some conversation with our panelists.

[00:04:06] And so I just want to step back a little bit and reflect on our title and smart stormwater. And, you know, we should probably know we're not talking about smart stormwater. We're talking about smart stormwater professionals and smart stormwater management and perhaps before we have a conversation about smart stormwater management.

[00:04:32]  Maybe we should take a step back and reflect about why this is an issue. And as the title alludes to in our description today, uncontrolled stormwater, I'd like to say excessive, or maybe mismanaged stormwater can pose a hazard to us, more importantly, the public. And the community that we play, work and thrive in.

[00:05:00] And so maybe we should just take a pause here about a hazard to who and hazard to what. And so we start thinking about what excessive stormwater plays a hazard in. It includes our residents. And not just our homeowners, but our renters alike, our businesses, and how they function and whether they're able to function.

[00:05:26] Schools, of course, and our transportation system, everything from light rail to,  underground trains and of course, roadways, excessive stormwater, uncontrolled stormwater also prevents,  presents a hazard in terms of other public infrastructure such as sanitary sewers, drinking water treatment systems, and our other utility systems, Such as electrical and that's largely driven by a quantity aspect, but there's also a quality aspect that comes with excessive stormwater and how it impacts our drinking water systems.

[00:06:08]  It also could impact our food production system, agricultural lands, our fisheries, aquaculture, all of this is impacted by excessive amounts of uncontrolled stormwater. I think we could probably all agree about that, but it's not just those hazards and the uncontrolled stormwater of today. It's also the uncontrolled stormwater for tomorrow.

[00:06:37] In many ways, we have more of it than we did decades ago. And why is that? We simply have more of it in different times of the year, in different geography and places than we had before. And so that is largely driven by precipitation patterns. Dare I say climate change, but I like to say precipitation patterns have changed.

[00:07:00] And that results in different amounts of precipitation, whether that be rainfall and snowfall coming at different times of the year at different rates and quantities that we've seen before. And that changes our urban storm water runoff. And the patterns that we've seen, so our design storms have changed.

[00:07:24] And we continue to develop and redevelop our communities, which is a good thing. And even with our pushes for green infrastructure and our pushes for bio infiltration and infiltration into the groundwater, we simply are, in many cases, creating more impervious cover, which results in more storm, storm water runoff.

[00:07:50] Our population is growing, our communities are changing. Ag and rural lands continue to disappear.  All of this resulting in more impervious cover in many cases, despite our energy into green infrastructure, can result and is often resulting in more urban stormwater runoff. So what does this mean for hazards? And the work that we do with urban stormwater.

[00:08:17] And so I want to turn to our panelists here and have a little discussion about this. And so the 1st question that I'm going to pose to all of our panelists members is, you know, this uncontrolled, excessive, mismanaged stormwater can cause these natural hazards that I've talked about, such as flooding, We didn't even talk about erosion, a little bit about water quality.

[00:08:44] What does this mean in context to your work and the organizations that you represent? So, in no particular order. Okay. Alphabetically, Donna.

[00:08:55] Donna Friedman: Thanks, John. Thanks for that introduction. That was great.  so,  my name is Donna Friedman. I am in Cleveland, Ohio. I know there might be some of you from other places.

[00:09:05] So I wanted to throw that out there.  I work for the Northeast Ohio Regional Sewer District and we have Sort of two sides of the house, we have our wastewater treatment where we have three treatment plants, and then we also have a stormwater program, which is mostly what I'm going to focus on today.

[00:09:20] Although stormwater does affect our wastewater treatment plants as well, due to inflow and infiltration of stormwater getting into sanitary systems, as well in Cleveland and in some of our entering suburbs, we also have combined sewers. Which leads to combined sewer overflow, and we are under a consent decree with the EPA to control that 25 year plan,  and we are making great progress on that program, so that's good, but for our regional stormwater management program, these hazards are worsening, erosion, flooding the struggles we have with water quality. And the program really was initiated based on a lot of field data that was collected, as well as anecdotal data from our communities.

[00:10:08]  We knew that these problems were very large, we have 62 communities that we serve, and the problems are so bad that we realized that they needed to be solved on a regional level, right, we need to be looking at this from a watershed perspective, not from a community to community perspective.

[00:10:26] Water does not follow community lines and so the solutions shouldn't either.  We do focus on flooding, erosion, and water quality. Those are the three peers of our program. And it typically, as John said, it is to protect buildings, roads, utilities, but also to protect our natural ecosystem, right?

[00:10:47] One of our major focuses is rebuilding the riparian corridor that we've lost through urbanization.  We complete those, or we try to meet those three peers of our program through projects, through water chemistry and ecological sampling.  We have a field team, the stormwater inspection and maintenance team, which we lovingly called SWIM.

[00:11:11]  And they really know the streams, right? They are there day in, day out inspecting the streams, analyzing erosion, trying to find where the worst log jams are so that if a storm comes through, we can get that log jam out of the way so the water can be conveyed downstream.  And we also lean very heavily on our geographic information systems team.

[00:11:31] They help us to visualize all of our, all of our streams they help us to mark all of the areas of risk. They take all the data from our large watershed studies, and they put it on a map so that we can all look at it. We all know what's going on. And then they use analysis to really help us narrow in on where the problems are and where we need to be focusing.

[00:11:54]  Through those large watershed studies, we have found that we have over a billion dollars of work, that needs to be done in our 62 communities. So, yeah, we're very aware of the worsening natural hazards and we're doing our best to take a whack at it.

[00:12:13] John Bilotta: Great. Thanks Donna. And I think we'll come back and certainly boots on the ground right where flooding can impact our communities, especially with these large utilities.

[00:12:24] So let's skip over to Joseph. And in context of this uncontrolled stormwater, what this means for you and your work and perhaps some of the research and projects that you're involved with.

[00:12:36] Joseph Wartman: Yeah, well, thank you, John. First off for having me, you can call me Joe. And, you know, more directly to your question of what does it mean for our work?

[00:12:47] It means that we're really busy and I'll just step back for a moment and tell you that I direct the natural hazards and disaster reconnaissance facility. So we help support the collection of perishable data after major natural hazard events and after disasters. And so we are the kind of groups that are on the ground collecting this data very quickly, often in the immediate aftermath of these kind of events.

[00:13:10] And we really didn't work on stormwater or flood related events until just several years ago. And it's really now a large portion of the portfolio of what we're engaged with. And just as an example. We're doing a large training workshop this week and a lot of our staff are wrapped up with that, but over the weekend we're, heading back to Yellowstone Park for the second time, this summer to not necessarily directly related to storm water per se, but to look at some of the effects of the flooding that have impacted the park.

[00:13:42] And that's estimated to be close to a billion dollars of damage right now as the kind of assessment. So we're really quite busy. I think what it means for our work, we collect all kinds of data related to engineering to the natural sciences and social sciences. And I think for our work, we're learning that that we have, we're beginning to exceed a threshold, not only in terms of the frequency of such events to which we're responding, but also.

[00:14:09] The events are becoming intense enough that they're starting to have these secondary nonlinear follow on impacts that we never really quite anticipated. So, for example, there's really a massive movement of sediment both through erosion and then re-deposition in these events at a scale at which I don't think we saw very frequently  a decade ago.

[00:14:34] And so we're really starting to see secondary issues related just to this dynamic of how flooding and sediment dynamics and infrastructure and communities interact. And just as a simple example, we're finding scenarios where scour is occurring at bridge foundations. In some cases.

[00:14:53] Bridges that have stood for 100 years through obviously,  you know,  through many decades of severe storms, but are now being undermined and then soft materials are being deposited in those scour holes and part of the sediment dynamics. And that's quite deceiving because we go back and look at those.

[00:15:10] It looks like there hasn't been too much. That's changed at the mud line, essentially the interface between the water and the subsurface. But then what we're finding is subsequent failures of some of these bridges because they have been infilled. And so there's some really tricky,  secondary and tertiary problems that we haven't seen before.

[00:15:28] So I'd say what it means for our work is that we're learning a lot very quickly about some of these kind of effects that we weren't before aware of. And It really is going to require us to think carefully about taking the kind of knowledge we've developed in this field for over many decades and try to think about how to apply that moving forward.

[00:15:47] Probably not only to an environment where the situation is much different, but where this, where these coupled effects of flooding and urbanization and land use are more intertangled. And so I think that's what it means for us right now.

[00:16:03] John Bilotta: Well, thanks, Joe. And as you talk there, I write down some good tough questions for the whole panel as we go.

[00:16:11] Certainly one to think about is how we continue to have more and more data to work with, which is a good thing, but it can be daunting as well. Joe, just for a follow up question, I don't want to assume everybody knows all the terms, but can you define for our audience perishable data? I think you refer to.  

[00:16:31] Joseph Wartman: Yeah thank you for asking that because that's always a point of confusion.

[00:16:35] Perishable data is essentially data that changes very quickly with time and in particularly after a major natural hazard event. This is typically related to the normal kind of cleanup and sometimes rescue or recovery operations that occur after such an event. But there's a lot of really important clues about what happened and what are the effects of such an event that will get lost if we don't collect that very quickly afterwards.

[00:17:00] So, you know, at the extreme, sometimes we deploy to places within a day. Other times we. For example, in Yellowstone Park, because of the access issues for the park,  we probably deployed within about a week or so it's data that if we don't get it now, it will be lost forever. And that data is incredibly valuable for us for validating models, for kind of making new fundamental discoveries about some of the things I've just mentioned and so forth.

[00:17:27] So that's why we spend so much effort in trying to collect this and then, we ultimately make this available to everyone in the community. It becomes open data.

[00:17:39] John Bilotta: Thanks, Joe. And next, I'd like to turn to Lilit. So we're talking about uncontrolled stormwater data and what this might mean for your work.

[00:17:48] We'd all love to hear from you. And in our remarks before we started, you mentioned students. I'd like to hear how some of this relates to maybe work that you do with your students, too, and how you incorporate that with your work with them. So, Lilit.

[00:18:03] Lilit Yeghiazarian: Yes, thank you, John. I lead an NSF funded center called the urban flooding open knowledge network and it is based on the premise that cities are highly complex systems. You have the power grid, you have the transportation network, you have the water network and the water, as Donna mentioned, does not stop anywhere. It's not confined to built environments or national environments. It has no borders, so it floats. All of this is intertwined with the, with the communities and public health and socioeconomic factors that really all of that forms the fabric of modern cities.

[00:18:48] So, if you look at it from this angle, you realize that stormwater is part of a highly complex system. And this is how we approach it is critical to have data that Joe collects that Donna collects that typically have been really accumulated and models have been developed in different sectors that have been siloed up until now.

[00:19:15] So our mission is to integrate and harmonize data. That have been sitting in different silos, and now we can ask cross cutting questions that if you have a stress on the,  an external stress on a highly complex system, like a city. And that stress can come from intense storms. So how do failures reverberate through the entire system of systems?

[00:19:41] You can say, well, you have excessive storm water and because of that roads are impossible. Sediments are depositing in the structures of the bridge and the bridge start failing more rapidly. Well, what does it mean in terms of impact on the communities? People cannot get to work, right? People cannot get to see their parents.

[00:20:03] They cannot help them. So work stops. So what is really the total impact of an external stressor on highly complex systems? And when you start thinking about it. And integrating data, only then you can answer questions to this complex to this complex queries. So this is the angle that we come from.

[00:20:26] And I do love the perishable data aspect of what Joe does, because another thing that we work on is water quality. And there are very tricky contaminants like microbes that if you don't, you're not there at the right time at the right place that they, that sample is done, and all the information that those samples would carry with them about the sources of those data would disappear.So, yes, data is critical to everything  that we do.

[00:20:55] John Bilotta: Well, thank you. And so let's turn a little bit to data compilation and data use. And so 1st, we'll talk a little bit about data use and Joe, I'm going to go to you 1st. I think you started to touch on this a little bit with your Yellowstone example.

[00:21:15]  But how do you envision us using big stormwater data, or, you know, this robust data set that we have, or, you know, data collection and monitoring. To help us prevent or minimize or mitigate impacts of hazards in communities.

[00:21:36] Joseph Wartman: I think there's a lot of ways, but I'm going to focus on 1  drawing on the discussion we just had, because I think that we've talked a lot about the connection between different fields, different disciplines and I really like this idea of presenting water as a, as a kind of a system problem.

[00:21:57] And so, I'm going to offer just 1 example of some work that we were doing recently, not necessarily directly related to stormwater per se, but to a related and sometimes a secondary phenomena of debris flows or debris floods. So heavily sediment and trains  volumes of water that are impacting communities, like, for example, Montecito near Santa Barbara.

[00:22:22] And we have done some work in collecting reconnaissance data. Related to the reconnaissance data and making the field reconnaissance to collect this personal data very soon after to understand what the effects have been on the population in terms of structures. But we've also done collect some social sciences data to understand how people perceived early warnings and how they reacted to those.

[00:22:48] And then we have been able to look at the connection between the physical intensity of what they experienced, where they were and what actions they took and ultimately close to 40 people perished in that event. So, what were some of the decisions that people made that. In some cases, preserve their life and other cases tragically resulted in the loss of life.

[00:23:11] So once we understand that what we have found that actually human behavior  is more of a driver of whether 1 survives and events such as that. As opposed to just the physical driver itself. And so there's a number of measures you can take of moving to a 2nd floor of the way that you interpret and understand early warnings of simply being aware that you're in a flood zone will affect how seriously you take that because it's I think it's some subconscious level in the back of your mind. So I'm just offering 1 example of the way that we can take this data and combine it in ways that enable us to develop mitigation strategies that might not just focus on this sort of hard infrastructure, but also on the way communities perceive that information and in the ways people decide whether they're going to build and rebuild and whether it's going to come back to a facility in the same configuration and so forth. So I think that really articulating the connection.  between, you know, the various connections and dependencies in this complex system are really critical for us for developing this mitigation strategies.

[00:24:25] John Bilotta: Well, thanks, Joe.Donna, I'd like to talk a little bit about your work at the sewer district. I mean, the local regional entity. I assume you're both collecting data and using data.  I think the question we have here is perhaps how  do you envision using more and more of this big stormwater data? Lots of data sets to help you manage and make decisions at the sewer district level.

[00:24:52] Donna Friedman: Sure, so kind of going off of what Joe was talking about, you know 1 field of data, I would say that we're starting to lean into starting to move more towards is some of the predictive rainfall rain radar modeling and so the forecasting right?  As Joe said, you know, it's very hard to predict how your communities might respond and how certain residents might respond when you tell them that they need to evacuate or when you tell them that there's a big storm coming and that they need to stay away from the stream areas.

[00:25:26] So we are yeah. We have good relationships with our communities and with our service directors, and now we're starting to use some of that data. To install, you know, stream gauge stream gauges that then have alerts for for different flood stages, not just the really big streams, but even some of the little bit smaller streams.

[00:25:48] We have live rain gauges that give us live feed on how you know we have 30 of them so we know how much rain is falling and where it's falling. And then we also. Using that predictive rainfall radar, we can alert our staff, our field staff say, Hey, there's probably going to be a storm here. So if you guys can go check the hot spots, if you can go check, you know, bridge XYZ this culvert over here, make sure that they're clear of debris so that the water can actually convey through rather than flooding out those neighborhoods.

[00:26:21] That's really helpful to us. And if we're able to say we think that there's going to be a big storm, then we can alert our communities. And they can alert their safety forces to shut down those roads that flood continually in those large storm events. So, that's one of the areas of bigger data that we're starting to move more towards rather than our very  other data that we lean heavily on all the time, like our engineering models for our stream designs and our basin designs, things like that. 

[00:26:50] John Bilotta: Well, thank you, Donna.  Lilith, do you have some comments, some knowledge and expertise experience to share about how you're using big data sets to help us either predict or avoid community hazards?

[00:27:06] Lilit Yeghiazarian: Yes.  I like to think of data is the foundation of everything that we do. So we have data, then we have models, as Donna mentioned, and based on models, we can generate knowledge, and we can act upon that knowledge.

[00:27:24] So data, analytics, knowledge, action is kind of the pyramid. So in our center, we have developed a real time flood forecasting capability across the continental U. S. And if you have that capability, then you can actually start modeling how people would behave in the event of a flood. So, if you give that information and you, let's say, can model if there are certain directives from the local authorities to do X, Y, or Z, we start thinking about what are the best evacuation strategies for a community.

[00:28:09] So which roads are predicted to be flooded and when? How do emergency responders should react to the situations? And for them the decision is basically do I send a truck, do I send a boat, or do I send a helicopter? And we can make these recommendations based on known behaviors. So it's a sociologic analysis coupled with hydrologic forecasting kind of thing.

[00:28:37] And based on that, we do develop recommendations for best evacuation strategies and routing really during the flood. So that's one example of how we use data.

[00:28:47] John Bilotta: Thank you. And so for our participants, if you have any questions for our panel, please go ahead and put those in the Q& A panel of Zoom, and we will get to those in just a few minutes whether that be about data or Excessive stormwater hazards.

[00:29:07]  But we'll take a few questions that I'm developing on my own and I'll invite any of the panelists to respond to these. So we've been talking about a lot of data and I, and I'm really intrigued by a couple of different things. Innovative ways of data collection. But also the challenges of more and more data.

[00:29:30] Oh, we don't need a gigabyte drive. I need 10 terabytes of a drive. So for any of our panelists that would care to respond, how are you managing the challenges of all this data collection and management? Anyone care to take a stab at that?

[00:29:51] Lilit Yeghiazarian: I would start,  we don't collect data on the ground. We use existing data, awesome data that Joe and Donna are collecting.

[00:30:02]  So the way you can handle it, number one, cloud storage is cheap, so you can do that. Number two is how do you analyze massive amounts of information and what resolution does it make sense to analyze it? Do you need information on the scale of a building footprint or do you need information on the scale of a neighborhood or a community or a county?

[00:30:29] So I think I would reverse it and say, what are the questions that we're trying to ask? And what, where are these actions going to take place and you can take a step back and decide what is the required compute power and what kind of data you want to aggregate or desegregate. So there it is, you were talking smart, so smart ways about optimizing the compute time and data storage.

[00:30:58] Joseph Wartman: Yeah, so we have collected. I think in the last several years, we did a count a few months ago, and we had collected close to about 250 terabytes of data in the immediate aftermath of I think we've started responding to close to 80 events. So that's a lot of data. It's not as large as the kind of data streams that satellites and many other,  Consistently monitoring sensors are collecting, but, it's a lot.

[00:31:26] And the way that we manage that is as Lillian has suggested, cloud storage is relatively inexpensive. We work with a partner. We're a National Science Foundation Center. So we have an NSF partner called Design Safe. That's based at the University of Texas, which is our cyber infrastructure partner, which is where we archive and make all of our data openly available.

[00:31:46] I think what's particularly important about that is that design safe has an in-house data curator that looks at that data, make sure that it's in a standardized format and that it is accessible. And we don't always know the purpose, like how that data is going to be used. But if it's well organized, you can do something as Lilith suggested, get a question and see what kind of data is available to help answer that rather than let the data drive the work.

[00:32:14] Really, you know, form some compelling questions and say, okay, we have,  you know, we have some, a lot of flood data from location A, we have it from location B and location C. What commonalities are there? What can we learn from that?  yeah. But I do think having it organized by a professional librarian or curator is really critical.

[00:32:34]  so it doesn't simply become a mess of hundreds of terabytes of data that we've really have just lost control of what's in there.

[00:32:43] Donna Friedman: Yeah, Joe, I just going off of that, I was going to say anyone can create data, right? But not anyone can just put together good usable data. I know that at the sewer district we have very high standards for the data that we receive from our consultants, whether they're stormwater or sanitary sewer consultants.

[00:33:00]  You know, we don't want the data until it's exactly right so that when we put it into our system it flows with the rest of everything else that we've collected. So I know our staff works really hard on the QAQC of that data before we really take it on.

[00:33:18] John Bilotta:  Thank you Donna, for approaching that topic, because I was going to ask a question about Q. A. Q. C. Certainly, as we combine, you know, lots and lots of data and we collected you know, so how do we get that data? I'm going to go 1 more of my questions. We got a couple of questions from audience here, but, um.

[00:33:39] So, the question I have, Lilla talked about real time data collection. Donna, I think you talked about a network of monitoring things for all three of you or any of you. What innovative ways have you come across or you're employing for data collection, some new things, some new technologies or new methods?

[00:34:04] What's innovative about data collection in regards to stormwater and hazards? Anything

[00:34:18] Joseph Wartman: I'll take a first shot at that because we collect data a lot of different ways. Our center has over 100 unique instruments and we have duplicates of many of those. So we have over 300 instruments in our portfolio. And that includes drones with sensors and light our equipment and a hydrographic survey vessel for capturing bathymetry.

[00:34:38]  Which has been used quite a bit for a lot of the flood investigations we've been working on. I think that what I have found to be really exciting is that there's a whole new family and range of sensors that really enable us to see things that are otherwise blind in a sense to the naked eye.

[00:34:59] And those are multispectral and hyperspectral imaging that really has a lot of application to stormwater management and to flooding. In particular, we're able to do some work in mapping flood lines through hyperspectral and multispectral signatures. And so it enabled us to go back and really get a sense of what the various flood heights were after the floodwaters have retreated.

[00:35:25] It's one of the applications I've been particularly excited about, but it's been used in a lot of other ways to look at soil moisture contents, to look at sediment dynamics, you know, again, as it pertains directly to flooding. So I think that's the, the Some of the instrumentation that I'm most excited about right now, and I think really holds a lot of promise for helping us better understand by being able to see things in ways we couldn't before of really being able to understand a lot more about what has happened in these events when we haven't don't have a lot of precedent for them.

[00:36:02] Lilit Yeghiazarian: Oh thank you. Sorry, Donna, if I jumped ahead.  Here's another question. Where do you collect? Because ideally you collect at every single point, every one foot, you can put the sensor, but that's going to become prohibitively expensive very quickly. So you have to be very strategic about where you collect and when you collect. I was wondering if Donna or Joe would have answers to that or have thought about it.

[00:36:34] Donna Friedman: As far as where and when, we do a lot of pre and post construction monitoring on our stormwater projects. And so that helps us a little bit with understanding the impact of the work that we're doing. But you're right.

[00:36:49] You know, like I wish we could have a rain gauge everywhere. But we have 30 and that's pretty good. And, you know, we have all this new technology that helps us a little bit with identifying where that rain is falling and how hard and things like that. But it is definitely, definitely a struggle that there's only so many resources.

[00:37:07] So you do have to be Pretty picky and we like to lean a lot on our engineers for some of that data.

[00:37:12] Joseph Wartman: And we've set up our center to really work in the service and support of the research community. So to the degree possible, we try to let our partners who were supporting us answer that question as to where they want to collect data and they want to collect data everywhere.

[00:37:31]  Just as Donna's mentioned, we try to bring them down as to what is achievable in the time and space available.  So we really try to let them drive that question and we try to work more in a supporting role of finding the best strategies to collect that data. But increasingly those groups have been  trying to specifically collect data to understand.

[00:37:57] I think, John, you opened this session with a great description of the kind of challenges we face and if there's One thing I kind of see is that that's all happening against the backdrop of infrastructure systems that have been in place for many decades or more. And I think that adds a whole nother challenge.

[00:38:14] So, in terms of where to collect data, a lot of the research focus recently has been collecting that data to understand how these extreme events are impacting infrastructure systems. That have not necessarily been designed to accommodate anything as large as the, as the kind of four scenes that they're seeing today.

[00:38:34] So that strategically, there's been also a lot of emphasis on collecting data in places where we traditionally have not collected data as a research community with an eye towards equity. So oftentimes we've looked at locations with some of the most spectacular property damage. Forgetting that there are large swaths of communities that are highly vulnerable to flooding, for example, and who have a much tougher time recovering from those because of a number of structural factors.

[00:39:03] And so I think that we've employed a strategy of trying to collect data across the whole range of socioeconomic groups. So we can begin to identify. How these events affect different communities, business communities, residential communities,  government communities and so forth. Again, across the whole spectrum of the population,

[00:39:26] John Bilotta: You think I would have paid you to prompt this next question, but it's actually from 1 of our participants.

[00:39:31] I'm glad Joseph or Joe that you mentioned that. But Lilith, I think you talked about some predictive, you know, Uses of your data in communities. And one of our participants is asking how you did or any of you are using sociological data combined with this scientific data to inform your analysis and prediction and modeling.

[00:39:54] Lilit Yeghiazarian: In our case, we have. As I said, we can forecast flooding. Well, when you say forecast, it is tied to a place. And that information is linked directly to the census. So within one click, we can pull out information, massive amounts of information as to who is being impacted, what is their status.

[00:40:22] And based on that, you can start analyzing as to, you know, how vulnerable are these communities? As Joe mentioned, it's a matter of resilience and vulnerability. Are they expected to bounce back quickly or not? Is relocation an option or not? Where do they work? Median age, diseases, mobility, all of this is, you know, a fantastic area of exploration because we're just starting to dig into this.

[00:40:54] Again, it all comes down to data and how you can mine data across multiple sectors.

[00:41:04] John Bilotta: In this highly scientific field that we work and we have to always remember that, you know, behind the data or in front of the data, what we're trying to use it for is for people, people, plants and animals, you know, for us as a community. And so certainly sociological data, demographic data, all of this plays a role of how we use the data effectively for what we like to say to prevent, minimize or mitigate the impacts of all this urban stormwater, right? 

[00:41:38] Joseph Wartman: I'll just, you know, add 1 more take on that question, which is to just kind of offer a practical example. Since we work on the ground quite a bit and the way we have addressed that is we do have a science plan that talks about strategic approaches, cross scale data collection, cross geospatial scale.

[00:41:58] Cross temporal scales, but also across social scales and specifically to do that. We use data from the American Community Survey, and look at social vulnerability index and then typically divide that up into core tiles. And develop sampling schemes that sample equally across those quartiles.

[00:42:20] We do that particularly because we work in a lot of places that we don't know. We don't know when the next major natural hazard event will occur somewhere. And that's something we've been able to employ across the range of hazards, but it's a more objective and quantitative way of ensuring that we're equally sampling again across those quartiles.

[00:42:38] Across those communities and that's an index that's developed by CDC and there's some similar spin off index indices that can be used as well. But that's how we directly use that social data and to help guide our data collection in the field.

[00:42:53] John Bilotta: Great.  If any of our participants have any other questions, please go ahead and put those in the chat or the Q&A panel and we'll see those, but I want to wrap up with one last question for us. And I guess looking ahead, all 3 of you the future of stormwater data and natural hazard planning. How do I want to phrase this?  do you see,  I think Joe, you touched on this with multi spectral signature monitoring, but looking ahead do you see one technology or data application on the horizon that has great promise or excites you about collecting or using stormwater data in community hazard planning. Who would like to go first? Okay, hearing none, I'll offer mine. I was going to do this. One of the things that's most exciting for me on the horizon, actually, it's already here, is real time control of urban stormwater ponds and our ability to use predictive forecast.

[00:44:17] I think Donna was talking about that. To control stormwater pond levels in prediction of a huge upcoming storm. So we can store more floodwaters so we can avoid potential downstream impacts in advance. So real time control of one of our oldest best management practice as urban stormwater pond levels is exciting for me in the future.

[00:44:43] But how about from any of you three?

[00:44:49] Lilit Yeghiazarian: Well, I would say that there is not one technology. I think there is a number of technologies that are very exciting and what you mentioned real time control is absolutely critical to that. But what is it that enables real time control is integrated data. So I think we're going back to where we started john.

[00:45:13] This conversation is with smart. I think this is exactly what it is. It's not just about people, but making the system smart. And that means that you have real time monitoring. You have data analytics on timescales that are compatible with rapid decision making. And then you have these controls that are in real time that can make a change.

[00:45:39] At the right time at the right place. I think all of these three are what excites me. And in terms of data technology, one that we have been working on over the last three years is the knowledge network or the knowledge craft, which is a sophisticated way of storing data and identifying relationships between different entities.

[00:46:01] And if you think about it, it really reflects The interconnections of complex systems that we're dealing with because you can put all of this different data from multiple sectors from utilities, power grid, water infrastructure, socioeconomics, all of it in one place. And because it is in one place, it lives in harmony.

[00:46:22] You can ask penetrating questions across the entire complex system. And that I think is a critical part of smartness. Again, data, analytics, knowledge and action all in real time where it's needed.

[00:46:42] Donna Friedman: I can go next. I was thinking. So we live right. I'm right by Lake Erie, like my house is 10 minutes walk to Lake Erie. It's great. However, you know, as the climate getting warmer, we're having these erosion sediment loads coming into Lake Erie. We are at threat of harmful algal blooms and sampling of harmful algal blooms has been very difficult.

[00:47:07] And I know that there's a lot of work out there with floating monitors with all types of water chemistry sampling so that we can really Pin down what cyanobacteria is going to create this micro system that's toxic, toxic and harmful. And what is actually okay right now. Once you get that sample, you do have to wait a little while for those results.

[00:47:30] So I'm excited for that to start moving forward so that we Can really identify what is a threat and what is not a threat and what what climate situations increase the likelihood that that algal bloom is actually a harmful algal bloom.

[00:47:48] Joseph Wartman: I think that I'm most excited about the resolution that the improvements in the resolution of the data we're collecting, you know, in some sense, it's the ability to most like infinitely scroll into the scene and see that you know used to be community level data and then sometimes it was neighborhood level data.

[00:48:07] And now you can zoom into later data on your block. And I'm thinking, for example, of some of the work that the First Street Foundation has done with really ultra high resolution mapping. I think that the reason that that's so exciting is because if we can personalize the risk, we have a much better chance of someone taking a proactive measure to help mitigate.

[00:48:29] Some of those hazards, you know, it's the reason why those speed limit signs say you're going 25 you speed by that when it flashes that you're going 30 as personalized information that's coming directly to you that typically causes you to slow down in response to that. So I think that our ability to provide risk and hazard data at the parcel level can really begin to open up.

[00:48:55] A lot of opportunities for mitigation strategies involving communities involved in individual households and elsewhere. And in the past, we just simply didn't have the data resolution to permit that.

[00:49:07] Donna Friedman: Can I do one more? Just came to me while Joe was talking. Yeah.  it's along what he was saying, I was recently, or I was watching a presentation about, you know, climate change and flood waters elevated near, you know, sea level rise, things like that.

[00:49:26]  One of the technologies that they're talking about where VR experiences where you could put these VR glasses on be standing in like Boston, you know, in a popular area by the water, and you could turn and look around in your VR fancy glasses and see where the water elevation would be and you know X number of years.

[00:49:47] And I think that being able to really put people in that situation and say, and like they can see it they can, you know, it lets them feel it more, at this, like, neighborhood level,  that Joe was talking about, like, instead of, you know, oh, nationally, sea level is going to rise. Like, no, this neighborhood in Boston that you've been to before or that you live in now, this is what the water is going to look like, you know, and how does that affect you personally? I think people feel that.

[00:50:14] John Bilotta: Well, great. Well, thank you all for those contributions. I do want to get to one other question that we just received from a participant. It goes to Lilit, but it might apply to your work too, Joe. But at your center, Lilit, have you been able to get the buy-in of private,  privately owned utilities to share data? And how do you approach those collaborations for data sharing?

[00:50:38] Lilit Yeghiazarian: Oh, that's an excellent, excellent question.  In our work, we found that depending on the utility, depending on the city, you're going to have a completely different approach to data. In Cincinnati, they say, Oh, take it, everything, anything you want.

[00:50:55] In other places, you have to sign NDA. So I would say there is no one way to approach it. It's always on a case by case basis. And it's always about building trust. And having this specific use cases and having an understanding of how opening the data is going to benefit this community. So once that is articulated, I think paths open that may not have been prior to that. That's a great question. Thank you.

[00:51:28] Joseph Wartman: I applaud that question as well, because we do find this as well that it really varies community by community and also the nature of the utility. Generally, we found that electrical utilities are quite conservative about releasing data and water related utilities are typically more open about that. But it really, really does vary.

[00:51:49] I think there's always a concern when we're often investigating things where things have gone radically wrong. So, we kind of step into situations where people want to be careful about, you know, what would be the distribution potentially of blame for that. But I would say,  maybe if there's an answer to that sometimes, and we sometimes get that sometimes still.

[00:52:10] John Bilotta: Well, great, my own contribution to that might be, it doesn't necessarily apply to, our past experience with private data, but collecting publicly collected data from multiple local units of government, cities, watershed districts, state agencies we're just in the middle of a project of doing a metadata analysis, trying to pull all this stormwater monitoring data from all these different sources together, which presents a QA, QC problem.

[00:52:41] But we've gotten there, but the carrot on the other end is being able to provide that data to anyone for everyone. That is in a usable format that they can access for whatever evaluation assessments they might wanting to do. So it's having that collaborative approach and not take, but also give back.

[00:53:06] Well, I want to thank our great panelists and all of our participants. We could certainly have a long conversation about data and sensors and how we're using this to both monitor stormwater,  predictive analysis to avoid community hazards both presently in the future.  But hopefully experiences like this allow us first and foremost to share our experiences, whether we're failing at something or succeeding at something and how we're using big data and as well as say how we're going to use this data smartly today and in the future. 

[00:53:47] So thank you to Donna, Lillet, Joe for joining us today. And I'll turn it back to Laura for some concluding remarks of our webinar.

[00:53:57] Laura Rankin: Thank you so much, John, for your excellent facilitation skills and just echoing all the thanks to our experts for that engaging conversation and to all of you tuning in for your participation and attention today.

[00:54:10] We do want to let you know that our next water data forum session will be taking place in September, and you can head to the Cleveland Water Alliance website for more details there, as well as following all of us on social media for updates as the date and time are locked in. So, we hope to see all of you there, and also hope that you enjoy the rest of your day and the rest of your week.

[00:54:31] Thank you all.

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