Decarbonize: The Clean Energy Podcast

Where does the water go? Stormwater management in the solar energy future

September 28, 2022 Season 3 Episode 20
Decarbonize: The Clean Energy Podcast
Where does the water go? Stormwater management in the solar energy future
Show Notes Transcript

Are solar farms a threat to water quality or a community asset? How can we create a solar-friendly permitting process that also enhances water and ecosystem services for the host community?

Thanks to the PV-SMaRT project funded by the U.S. Department of Energy’s (DOE) Solar Energy Technology Office, we are excited to debut the first solar-specific national study on stormwater dynamics and modeling. Project members include Great Plains Institute (GPI), DOE’s National Renewable Energy Laboratory (NREL), Fresh Energy, and the University of Minnesota.

The team used field research on five existing ground-mounted photovoltaic (PV) solar sites across the United States, three-dimensional hydrologic modeling, and feedback from solar developers, site managers, state and local regulators, and other stakeholders to assess the opportunities. And results are flooding in!

Based on the project’s findings, researchers have now developed a stormwater runoff calculator tool and best practices recommendations for local and state permit officials and solar industry practitioners. Tune in to this webinar, recorded on September 28, 2022, for more details from hosts Fresh Energy, GPI, and NREL and special guests for the inside scoop on how the tool has worked so far.

Meet the speakers:
Brian Ross, GPI
Dr. David Mulla, University of Minnesota
James McCall, NREL
Todd Smith, Minnesota Pollution Control Agency
Robert L. Goo, U.S. Environmental Protection Agency, Office of Water
Lee Strait, EOR
Moderator: Briana Kerber, Fresh Energy

Briana Kerber, Fresh Energy:

Hello and welcome to Decarbonize: the Clean Fresh Energy is a Minnesota nonprofit working to speed our state's transition to a clean energy economy. My name is Briana Kerber. I am Fresh Energy's policy communications associate. And today I'm here with you to share a recording of the webinar that we hosted alongside GPI and NREL called "Where Does the Water Go? Stormwater Management in the Solar Energy Future." In this recording, you'll hear from several special guests, including Brian Ross with GPI, James McCall with NREL, Dr. David Mulla with the University of Minnesota, Lee Strait with EOR, Todd Smith with Minnesota Pollution Control Agency, and Robert Goo with the US Environmental Protection Agency. And with that, let's jump into the recording. [recording starts ...] I would love to give the floor now to James, who is going to talk about how we got here with with the project at hand. James, take it away.

James McCall, NREL:

Absolutely. Yeah. Provide some introduction to the project. So the PV Smart Project or the Photovoltaic Stormwater Management Research and Testing project is funded by the US Department of Energy and through their solar energy technology office. And I think we're seeing the wrong or we're seeing the presenter view if we want to switch that over.

Brian Ross, GPI:

Oh, okay. Well, we'll have to pause for a second, while I...

James McCall, NREL:

I can keep talking.

Brian Ross, GPI:

...get things on the right screen.

James McCall, NREL:

Yeah. So yeah. So this, this project is, was funded, as I said, by the Solar Energy Technology Office. It's been going on for three years. And really this kind of webinar is the culmination of kind of the, the three years of research done by this fine team. And so really the the impetus for the project that we're seeing is that solar development has been taking off across the US. There we go.

Brian Ross, GPI:

Okay, there we go.

James McCall, NREL:

And so we're seeing that the over we're that are in the interconnection queue or basically kind of just about to come online. And this is basically a huge order of magnitude higher than kind of what is currently existing in terms of large scale solar. And that's kind of what's projects that are planned. So basically, if this is actually developed, this would use roughly 5.4 million acres of land, most of it that kind of exists in these rural or kind of non-urban watersheds. And basically the Solar Future study found that 10 million acres of land would be needed to meet the highest level of solar deployment, which is going to be a fairly significant change in land use across this. So coupled with this land use, we are seeing some both local, state and kind of federal concerns about kind of water runoff from these sites. And so really this project is trying to provide some basic science on kind of, the what are these, what is the stormwater runoff at these sites and kind of the, what are some of the best practices? And so we've been seeing that jurisdictions were treating these PV facilities as predominantly impervious surface, basically being treated the same as a parking lot. And we know that kind of the, our hypothesis was that in particularly with projects that have different types of vegetation, that this is probably not accurately capturing that and they're really the local land codes didn't actually capture the intricacies of a solar project. And so really we, the, a lot of this effort that will be discussed is creating a storm water model based on kind of real world observations and then kind of discussing what are some of the best practices on this. And so really our intent is to basically, as these sites are being treated as basically parking lots and impervious surface, there could be higher costs for stormwater mitigation. It could slow down solar deployment and particularly if there is some inconsistency between regulating entities and then even kind of poor water quality outcomes if you go to the next slide. So basically we want to see kind of like we know that there's going to be a different stormwater impact going from the left, which is just kind of gravel to the right, which is actually kind of a prairie established underneath solar panels. And so right now, particularly in some jurisdictions, these projects should be treated the same from a stormwater perspective, but we know that that is probably not accurate. And so we tried to kind of assess this. So I think the next slide, so our kind of goals of the PV-SMaRT project is to reduce the balance of system of cost. So if there's less water runoff, then we have to have kind of less retention ponds or smaller retention ponds to kind of manage stormwater when improved water quality outcomes. And then we want to really kind of establish science based guidelines for survey and the stormwater runoff based on real world observations. So if you want to go to the next slide. So to do this, we did five things. We established a water quality task force of of professionals, many of whom are on this call right now that are kind of working in this area to make sure that their kind of input is kind of provided into this process. We then conducted field research at five different sites kind of across the US geographically to kind of make sure that we are representing different ground cover soil types and also climates. We then, in particular the University of Minnesota, did some field research to validate a 3D hydrologic model to make sure that these runoff runoff coefficients are actually accurate and kind of can represent the differences of solar sites. GPI has done a lot of work on developing stormwater management, water quality, best practices. So basically so what are some of these things that we found, and what are the key parameters that need to be addressed as we're kind of doing stormwater permitting? And then kind of this last one is really why we're doing this webinar. We want to engage with local jurisdictions and other stakeholders to kind of get the word out and basically make sure that this science is available to people who need to use it. So if you want to go to the next slide. So as I mentioned before, our partners are University of Minnesota, Great Plains Institute, Fresh Energy and NREL, and these are all represented on this webinar. Coupled with our Water Quality Task Force, which is a combination of regulators, industry members, some kind of engineers, and then also some academics. So it's making sure that we're getting a wide variety of kind of input. And as you can see, both Robert, Todd, and Lee are all on this Water Quality Task Force. So next slide. And now I'm going to hand it off to Brian, who's going to go a lot more into some of our kind of initial findings and best practices.

Brian Ross, GPI:

Thanks, James. So really what it comes down trying to help particularly host communities, but also kind of water quality professionals across the nation understand what turns this scenario [on screen], which is not very welcoming, into this scenario. And how do we, how do we measure that and how is that incorporated into development practices and best practices? And what kind of considerations do permit officials need to make in order to make sure they're accounting for the different variety of projects? The interesting thing about these pictures that you see in front of you are that they're actually at the same place. We had a solar a development that was not working very well on the left. And they then after some discussion with with regulators, came up with a solution, which is on the right. So it is something that can be done either one way or the other. And we wanted to kind of document and verify what that, what the impacts of that were and what the opportunities were both for water quality for host communities as well as for the solar industry. So again, this is just GPI, where we're the nonprofit organization. We've been working a lot on the co-benefits of solar and wind energy development, including a fair amount of water quality research and best practices in various ways, as our role in the project was to kind of focus on the best practices after the research had been done. About a year ago, we actually published what we called our interim best practices, which is a document that you can get on the on the website, the project website, which took the spot we were at in the research and we started taking it out to stakeholders across the nation and getting their feedback on both best practices as well as on the status of the research to find out, make sure that we were going in the right direction, to make sure we were going to get something that was useful in the end, too, to the audiences that would be using this and that are concerned about how solar occurs at the local level and at the national scale in terms of getting them out of deployment that we want to see. So what we have done with these interim best practices and I'm going to run fairly quickly through this, we are really redesigning them now to reflect the final findings of our study. And Dr. Mulla is going to go into this in a lot more detail. But we basically came up with four different major findings on what we need, what needs to be considered from the standpoint of water quality and solar deployment. And the first and most prominent one was addressing the issue of compacted soils or bulk density of the soil. What are the priority best practices that kind of came out of these four solar projects? Or is it to really focus on low impact development (LID) construction practices in the selection of construction equipment, staging plans for how you move equipment across during the construction phase, limiting the amount of grading and certainly not not removing soils, etc.? There's a whole series of low impact development construction practices that would result in maintaining low bulk densities. And if you, if indeed you needed to, post-construction, to plow, chisel or scarify in order to de-compact soils to a threshold standard so that the developer, the host community and everyone else can be sure that in fact you're going to have infiltration on site rather than runoff. Things like seeding the site between clearing and construction and also looking beyond the actual construction phase in terms of compaction issues to make sure that Post-construction O&M plans are maintaining the targeted bulk densities of the soil over time so that we don't end up with compacted soils after the auction is ended. The second finding we had was on soil depth and this was a very interesting finding that this was a critical component because it's something that from the standpoint of stormwater, hardly anybody in the nation was looking at. So we kind of identified some best practices here to recognize that the soil depth of the rooting depth of the soil is actually the infiltration capacity of the site and is very critical to identifying stormwater. So just measuring and identifying soil depth within your, within the construction process and the permitting process, making sure that there are some understanding about how to avoid shallow soil sites or sections of sites or if you can't avoid them, providing for additional mitigation so that there's not any surprises and that the water quality impacts are addressed appropriately, entailing those mitigation steps for different kinds of soil depths and bulk density as the two biggest things that need to be addressed in, from a standpoint of stormwater management on the site. The third finding we had was that ground cover was very important and that different types of ground cover ended up with different kinds of infiltration ability, different kinds of water retention on site, different kinds of runoff. So some of the things, particularly at the local level where we saw a lot of variation at the local permitting level, is to recognizing that infiltration of water quality benefits does change with different kinds of ground cover choices and making sure that that's addressed when you're looking at the kind of mitigation steps that a particular object might want to use, looking again at encouraging the use of deep rooted or native vegetation for the long term water quality benefits that go beyond post construction or get into post construction, go beyond the construction. It's encouraging a greater diversity and sustainability of the native groundcover and recognizing some of the co-benefits that come with different ground cover choices, whether that be habitat creation or visual co-benefits, not necessarily affecting water quality, but something that most water quality entities and host communities would like to see happen anyway. And then the final finding was on disconnection, which is the amount of space that is between the panels with the panels which are impervious, but the ground which is underneath the panels as well as between the panels is pervious, particularly when you do the bulk density, soil depth and ground cover in a manner to maximize that. So looking at the kind of things for solar sites to consider about a, a disconnection distance that appropriately allows for infiltration of the water, focusing on disconnection distance, particularly when you're looking at dense or shallow soils, some of those more difficult sites and allowing for disconnection at the local level as a BNP when your modelling shows that it actually mitigates runoff rather than a baseline condition. Disconnection can actually be considered as it is in some regulatory environments already. As a BNP for mitigating stormwater, we are developing a series of tables that kind of reflect this. This is the compaction and bulk density set of tables with the current practice for permitting considerations and what the PV-SMaRT implications are for the current practices. We also have a series of recommendations here for solar projects in terms of the best practice that we would recommend that solar sites incorporate in their practice in order to create water quality benefits and to create ultimately a transparent and predictable permitting process in the development process. So this is, I ran through this kind of quickly, and I'm going to leave it next to let Dr. Mulla go in and do a description of the actual PV-SMaRT solar runoff calculator, which was developed out of all the field research really to develop to enable developers, engineers, local decision makers and state regulators, as the case may be, to work from a common foundation of knowledge and science in order to improve water quality outcomes for host communities and make for a predictable and transparent permitting process for the industry. So that we can get to accelerated goals and the expectations that we're seeing from the Solar Future study and from the current market need that James identified earlier. So at this I'm going to hand it off to Dr. Mulla to go into the details of the field research. What was the background behind this, what the findings were and what the ramifications of that is, as well as a tutorial on the calculator. So I will stop sharing, David, and let you take over.

Dr. David Mulla, University of Minnesota:

Thank you, Brian. And. I'm following along with the Q&A and see that there's a lot of questions about the modeling. And that's what I will answer in this presentation is how we developed the PV-SMaRT Solar runoff calculator. And I want to acknowledge Jake Galski, who's also here, and he is a researcher that is actually doing the modeling and collecting a lot of the experimental data. So as was mentioned earlier, we want to develop this runoff calculator to estimate stormwater runoff at ground mounted solar photovoltaic sites and the tool accounts for soil and topographic characteristics, surface cover, disconnected impervious surfaces that are associated with the panel design and climatic factors. We started by actually studying the four or five sites that are listed on this slide. So they're representative of different areas of the country, different climates, different soils, different management practices and different amounts of rainfall. So there's a wide diversity of sites - Minnesota, Oregon, New York, Georgia, and Colorado. I do want to point out that, you know, these are all 18 megawatts or less, as someone on the Q&A mentioned, but the results that we're developing are not dependent on the area that is being installed, because what we're doing is we're estimating runoff coefficients for individual soils within sites. And then those individual runoff coefficients can be used with other modeling systems like TR-55, SWMM, Hydro-Cad, to estimate the total amount of runoff from a site. So what we're generating here primarily would be runoff curve numbers, which don't depend on the area of a site. They instead depend on the characteristics of the site that are reflected by this diversity that we're talking about. So at each of the sites we did monitoring of the precipitation, as well as the soil moisture beneath the arrays, beneath the drip edge and in the area of full sun between the arrays. We also monitored the drip coming off of the edges of the panels. And in general, what we found is that about ten times the precipitation falling on the panel was dripping off the edges. So there's a concentrated flow at that site on the drip edge. And our approach takes into account what that concentrated flow does in terms of infiltration and runoff. For each of the sites, we did extensive characterization of the vegetation and the slope and the characteristics of the site, including infiltration and runoff and measurements of soil moisture. And these data were used to calibrate our model. The specific model that we used for the initial modeling is called Hydrous 3D. It simulates two or three dimensional, variably saturated flow in the unsaturated zone. The model inputs are soil depth, soil texture, soil, bulk density, saturated moisture, content, soil, hydraulic conductivity and slope. And the data from our five experimental sites were used to calibrate the model and then determine its accuracy against measured data. So we did some calibration of parameters like gas saturated hydraulic conductivity, which we also measured experimentally at each of the sites. So we didn't do a large amount of calibration. Our measured values were pretty close to what the final calibrated value should be. An example showing the agreement between our measured data, the green lines and the model data, which is the brown lines, shows a very good agreement between the measured and the model results. For different precipitation events, which are the vertical blue lines and for the five different soil textures that we had are root mean square errors. Where we compare the measure to the predicted values are actually all very good. Our best results were obtained in the sandy soils where we had the highest infiltration rates and the results were less satisfactory in one of the clay sites, but still very acceptable. So the idea here is we're trying to use our knowledge of the three dimensional nature of hydrology at these ground mounted solar PV sites to get a better estimate of runoff. In the past, people some people have modeled PV sites as if they're totally impervious, which is not really correct. And other people have tried modeling them as a mixture of pervious and impervious sites, which is more consistent with the approach we're using where accounting for the disconnection between the areas that are impervious, where the arrays are, where the precipitation runs off at the drip edge, but beneath. The arrays were also allowing infiltration of water that runs off from upslope. And so it's not a completely pervious surface is not a completely impervious surface. There's a kind of a mixture in that area. Then when water runs off into or rain falls on the full sun area between arrays, it can run off, it can be transpired. It can infiltrate downslope. And the screen capture on the bottom shows our actual modeling runs where we show the ability to handle drip edge runoff incident, precipitation in the full sun area, along with the infiltration, their routing of runoff under the next panel array down slope and then continuing that for a number of different array systems as you go down slope. Ultimately, we're predicting the amount of runoff that happens down slope. So the conclusions from our experimental studies at these five sites show that the model was accurate at estimating runoff, that there were different factors that seem to play a role here. And I've ranked these factors from more important to less important. Runoff was more strongly controlled by the design storms that we use than any other factor. So using a large design storm created a lot larger runoff than a smaller design storm. Compaction and bulk density of the soil was the second most important factor. Soil depth was the third most important factor. There's more runoff from shallower soils and deeper soils. The type of vegetation or ground cover or surface condition at the site was the fourth most important factor. And then the least important factors were whether you had a raise or not compared to a baseline pre-construction condition and the spacing of the array's run off. Tended to increase as we narrowed the spacing. We also compared our estimates of runoff at these five sites with the NRC runoff curve number method for 100 year storm and other design storms as well, and found that our modeling approach reduces the runoff relative to a more simplified approach that involves just applying a runoff curve number and assuming that the entire site is pervious. Now we know that for the normal users in the industry, using our complicated model is not really practical. So what we did was we used our calibrated and validated Hydrous model, ran it about 1,000 different times with different soil textures, different soil depths, different bulk densities, and different design storms. To develop a set of nomagraphs that were incorporated into a user friendly Excel spreadsheet that predicts the runoff curve number and runoff for a design storm of your choosing. So these graphics here show the actual run off calculator that is an Excel spreadsheet based tool and the results are based on your input for vegetative cover presence or absence of arrays, the slope steepness, the rooting zone depth, the soil texture, the bulk density, and what kind of ground cover you have at the site. And so I'm just showing here the difference between silty clay and a loamy sand with a moderate bulk density and early established pollinator habitat. These are solar panels spaced at 25 feet on a 10% slope, and you can see the runoff curve number for the first situation with the finer textured soil is larger than the runoff curve number for the second situation. And if you had a ten inch design storm, the first situation would result in almost five inches of runoff, whereas the second would be about an inch and a half. So it's a big difference. Now the assumptions for our runoff calculator are listed here. We assume that the arrays are parallel to the contours of the slope. The soils are uniform. The vegetation is also uniform. The runoff is routed off the panel and allowed to infiltrate in the area between the panels. Any runoff that continues down slope can then be infiltrated under the subsequent panel, panels are assumed to be tilted down slope maximizing runoff coming off the drip adds. So this is a more or less worst case scenario. The soil is not frozen and does not have snow. And our intended uses are, for preconstruction versus post construction. And so in pre construction, you could run the calculator to assess runoff without any arrays. So you have select no arrays. You can have pre-construction vegetation, which might be row crops, for example, and you can evaluate the site suitability based on soil, soil texture and soil depth, which are critically important factors. So in this first scenario without a raise, the runoff curve number is about 74 for a loamy soil that's pretty shallow. And in a ten inch design storm, you get about 6.7 inches of runoff. For post-construction, you could alter those to consider what might happen if you had post-construction management practices that created lower bulk density, like ripping or management of wheel traffic so that you don't have compaction. There could be pollinators established. You'd have panels with a 25 foot spacing. What this combination would do is show you that your curve number goes down to about 57, and that reduces the runoff from about 6.7 to 4.4 inches. Now, to use this tool, there are two ways to gather the input data. You can measure the data at the site and then put it in, or you can use national databases from the NRCS. These are the soil databases called SSURGO. And you can look up all the input data for your site from the SSURGO databases as a second alternative. I just want to highlight a few things that Brian mentioned. Soil depth is very important and if you have deeper soils, you'll get less runoff than shallower soils. That's shown here in the calculator. And again, you can get the soil depth from the NRCS SSURGO database. Vegetation is very important and there's a dropdown menu on our tool which allows you to choose from all these options. So you can have bare soil, gravel row crops, turf grass, you can have pollinators, forests, mature prairie, you choose what kind of vegetation you want and that will affect the bulk density. So if you're exploring post-construction effects of bulk density, I mean a vegetation, you just enter from this dropdown menu. What kind of ground cover you want? You don't change the bulk density because that can be independently changed to reflect ripping of the soil or management of wheel traffic. They're independent of each other. So you select the vegetative cover during the pre-construction period that you want to evaluate, and then you can look at how that affects your runoff. So in this example for a loamy soil, you're looking at the difference between newly established pollinator versus turf grass. There is an increase in runoff with turf grass relative to the pollinator, and that gives additional runoff from the site. So to conclude, we developed a user friendly run off curve number calculator and you, the user inputs, soil texture, soil depth, soil, bulk density, vegetative cover, presence or absence of arrays, panel spacing if arrays are present and slope, and then the calculator immediately gives you an estimate of the run off curve number, which you can, Then you can enter your design storm of interest and it will tell you how much runoff to expect. If you have different soils at the site, you can run this calculator for each soil and then you can use the area weighted inputs of the different soil runoff curve numbers and put those results into other models that can calculate the total runoff from the site. And we'll have some examples of that later on in this webinar. So the runoff calculator allows for accurate consideration of runoff generated by the disconnected pervious surfaces as affected by a wide range of site specific conditions. And now I will conclude my prepared presentation, and I thank you for your attention.

Brian Ross, GPI:

Yeah, we David there's a couple of, I think, answer now. We will have some questions and answers later, especially after we finish the rest of our panelists. But there was a question, on getting the model calibrated to large storms or all storms?

Dr. David Mulla, University of Minnesota:

We calibrated the model based on our measured range of storm events. So all the way from one year return frequency storms to about 200 or 250 year return frequency storms. So a very wide range of storm events. Is the model applicable to sites where you have cut and fill? Yes, of course, because the cut and fill will change the soil depth and it will change the bulk density. So if you know how the cut and fill has changed the bulk density or the soil depth, you can enter that in the model. Are there recommendations for the drainage area limitations to which the calculator can be applied? Those are really based on our our assumptions. We make a big deal out of like specifying that the arrays are parallel to the contours. The soils and the vegetation are uniform. There's no frost or snow. We have run simulations for situations where the arrays are up and down the slopes. That does increase the runoff by about 40%. We probably will put that into the calculator for a updated version. And then how did the curb numbers compare to those in other models? Those will be the subject of the next two presentations that we're going to have. So we are getting some evaluations to answer that question. Thank you for your questions.

Brian Ross, GPI:

All right. Thank you, David and Lee, I Is that the order we have? So we have Lee Strait from Emmons and Olivier Resources (EOR), who has, as he introduced himself, has a great deal of experience, both in water quality broadly as well as kind of looking at solar sites. And we did ask, EOR was on our task force, and we asked if they could with some of the communities they're working with and some of the solar developers are working with, if they would be able to run some case studies using our beta model. And he is going to present that to us. So go ahead, Lee.

Lee Strait, EOR:

Great. Can you confirm you're seeing the

Brian Ross, GPI:

Yes, you are.

Lee Strait, EOR:

All right. First, I guess I'd like to thank Dr. Mulla and the Fresh Energy team for having me here to present on this topic. I was asked to complete a case study comparing PV-SMaRT outputs to standard industry practices in relation in relation to stormwater management. There we go. First, a little bit about my team. I am with Emmons and Olivier Resources, EOR for short. We are engineers, biologists, ecologists, hydrologists and land use specialists. In general, we work to make the world more environmentally sustainable, natural and beautiful by restoring water bodies, waterways, reducing development impact through smart stormwater management, and bringing ecological features back to their natural state of being. We also happen to do a large amount of site assessment permitting and civil design for solar developments throughout the Midwest and beyond. There are mainly works in the upper Midwest, but we are expanding as opportunities present themselves. The Yellow Stars in the Slide show all the solar sites we have worked on and the red Stars show all the electric utility substations we have sited and designed. So what is smart Stormwater management? Detention ponds and basins are always going to be a thing, but the best way to manage stormwater and minimize your development's impact on water quality is to reduce the amount of runoff from your site. EOR emphasizes low impact solar site development by establishing cover crops before construction to effectively reduce runoff during construction. We build our designs to minimize grading and soil compaction, and we mitigate soil compaction that does occur. Obviously, solar sites also provide an excellent opportunity to reestablish native prairie grasses and pollinator habitats, and we provide comprehensive vegetation management plans to make sure the plantings thrive. We also make sure to build in vegetation buffers around every site to capture runoff that does occur. Smart Stormwater management requires smart and realistic modeling as well. To do that, you need accurate representation of soil conditions, characteristics, ground cover and land use. PV-SMaRT happens to be a great tool to account for the different soil variabilities. The bulk density root zone, land use, vegetative cover and of course all of these have a significant effect on the infiltration capacities. This is a neat study that was done by Jay Riggs when he was the Dakota County Minnesota Conservation District. It was shared with me by Jay Michaels, who is EOR's stormwater guru or godfather. We haven't settled on his official title yet, but we're working on it. Chances are, if you have read a stormwater ordinance in the Midwest, one of these two Jays had a hand in it. This study documented all rain events on a 25 acre site for a full year and the effects the development had on the runoff volume. The charts a little busy, but essentially the precipitation amounts above the color curve number lines is runoff and precipitation below the line is infiltrated. In this case, changing the site from the partially vegetated and wooded site to residential with compacted soils that you would typically see resulted in an additional 12 million gallons of runoff per year. And that's a pretty big pond. The key study I was asked to complete for today's webinar focuses on comparing a stormwater management report from a 300 plus acre industrial scale solar development that use industry standard practices to run off volume using PV-SMaRT and NRCS soil data in the report and comparing to all curve numbers were chosen based on soil borings taken at low land areas of the site that are not really representative of the full soil profile, and they were all assumed to be compacted hydrologic soil with very high curve numbers, which is basically a worst case scenario for pre-development runoff. This slide shows the breakdown of the soils on the site and the associated curve numbers in the comp report, which is the report I'm comparing to curve number 89 was used throughout the site. When you take into account all the soil characteristics using P V-SMaRT, you get curve numbers from 33 to 42 accounting for root zone depth of 60. Actual density measurements, things like that. Significant difference 89 down to 42 proposed conditions in the comp report. Assume metal conditions and solar panels is pervious surfaces with some new impervious surfaces added first service roads and the curve numbers drop from 78 to 84. Using PV-SMaRT and assuming the panels as disconnected impervious with newly established metal conditions along with the same new impervious services, the curve numbers were 39 up to 65. This next slide shows the modeled runoff curves for the ten year, 24 hour storm using hydroCAD from the four different reaches in the development. The grey curve is existing conditions from the comp report. The red curve is existing conditions, if the lookup table from hydroCAD is used. The purple curve is a proposed conditions from the comp report. The green curve is the existing conditions using PV-SMaRT curve numbers and fully accounting for soil conditions. And the blue curve is proposed conditions using PV-SMaRT. Pretty obviously these curves show the stark difference in stormwater runoff when you fully account for soil conditions using PV-SMaRT and all reaches the difference between the comp report, proposed conditions and the PV-SMaRT proposed conditions. Runoff volumes using PV-SMaRT are approximately 10% or less of the comp report. Here is another illustration of the differences between the comp report, the lookup table and PV-SMaRT run off volumes for the ten year storm. As you can see, all breaches have merely negligible runoff using PV-SMaRT numbers and significantly less runoff than the comp report. In summary, the proper accounting of the complete soil picture and profile leads to significantly reduced stormwater management burden and PV-SMaRT is a great tool for accounting for that variability. While there may be some minimal upfront costs associated with documenting the actual soil characteristics and maybe a few extra field visits, the long term management costs will be significantly reduced. I'd be happy to talk offline about the results. The case study and how to be smart might be a good choice for your next project. Feel free to reach out and thank you for your time.

Brian Ross, GPI:

All right, thanks, Lee. Next up is going to be Todd, why don't you go ahead and get your slides up and we will, I think, hold off on questions for now until after all three panelists have gone. And then we have some time set aside for some Q&A to dive more deeply. There's a lot of very good and interesting questions I think that people obviously want to ask. So Todd is our state regulator on the panel, has a great deal of experience with solar in a number of different kinds of sites in Minnesota, as well as, of course, long experience on the stormwater management, construction, general permit and other water quality issues. So go ahead, Todd.

Todd Smith, MPCA:

Great. Thank you. Good afternoon, everyone. So I was going to take just a minute and talk about what we're doing with solar projects in Minnesota. We've got a calculator of our own and we can just talk about the two calculators side by side here as we get going. So. In Minnesota, like in all the states, you've got to get an NPDS permit for your stormwater management. And we do have treatment requirements in there, and it's all based on impervious surfaces. Sure many of you already know this, and it's been somewhat like this for a good 20 years now. In the base requirements always been if you're going to create a net increase of impervious surfaces more than one acre, you're going to be required to have some type of stormwater treatment system on the project. And that is the rule that we've been running with. And it's a pretty simple calculation. The volume of the water that you need to capture on your site is just one inch times that net increase of impervious surface. So you get a volume of water with that basic calculation. And we have run with that for quite a few years. It wasn't till just recently that the solar industry started applying for a lot of permits and it quickly became evident that solar panels are not exactly your typical type of impervious surface, since we have always assumed that creating impervious surface means you're eliminating some type of pervious surface. And that's not true here. Or at least you have the opportunity for it to not be true because you have the area under the panels. So we did recognize that it was going to be fair and reasonable and to have a different standard for solar panels. So we did work on a calculator for that. One of the things our permit focuses on is infiltration. It is the goal of our permit to try and mimic the natural hydrology of the landscape out there. And we need to promote infiltration since we're covering so much of the planet with these impervious surfaces. So on these solar panels, we developed our own calculator and we resurrected an old BMP called Disconnected Impervious Surfaces, which you can model in a number of different programs like SWMM. And we had actually done all of this work prior to us creating this calculator as far as creating these performance curves that I'll show you and associating it with that standard the one inch times the impervious surface. So here's how it works. This credit basically comes back and gives you a credit, assuming you've maintained that vegetation under the panel. The credit is based on SWMM modeling. And it's really has the, the inputs are the pervious surface versus the impervious surface, the ratio between those two. And the picture here you can see the panels, the panels being the impervious surface and the pervious area being the area between the panels and also the area under the panels. That's the Y plus Z there, which I believe is the equivalent to the panel spacing input on the calculator Dr. Mulla's been talking about. So with those dimensions you can create that ratio, the pervious to impervious ratio. And this is what our calculator looks like. User inputs are here. There's your pervious and impervious area. The runoff. The runoff depth is based on the vegetated conditions of an undeveloped site, and it's dependent on the soil types A, B, C, and D. The average runoff is what you look up on these performance curves that I'll show you and the runoff depth is a somewhat fixed number for the state of Minnesota based on rainfall records. And that performance goal there is straight from our permit one inch times the impervious surface. So what we developed here and we use 35 years of continuous simulation modeling to estimate all of the runoff events for all the storm events for 35 years in three different locations throughout the state of Minnesota. And based on the soil types and it's just broken down as to A, B, C, and D, and that ratio between the pervious and impervious areas, you can look up the average annual runoff depth with these charts. And that is the gist of our calculator. We have a bunch of assumptions. Two of these are two unlike the ones you just heard about. We expect the Earth disturbance be minimized during construction and that you have vegetation under those panels. We do expect that the vegetation as well established all the other impervious surfaces on the site, need to follow the regular construction stormwater permit rules. The panels should be ten feet or less in height and we do assume that there's some pervious covered down slope, if you will, from those those last few rows. So let's take a look at the two calculators together. And this is a very unscientific slide here. I hesitated to even put this slide together. It was very difficult to compare the results of the two calculators since everything we have done with our permit and the standards we have in it is based on an average annual basis, which is different than the PV-SMaRT calculator, which is looking at specific storm events. So in order to put this slide together, I did a lot of runs, many, many runs looking at all the different soil types in the in the PV calculator versus our own. And I think and I'm going to say, I think that the results look something like this, at least on the soils. It looks like the calculators tend to diverge a bit. Whereas the PV-SMaRT calculator is giving you nearly a 100% credit on those soils, our calculator never gets much above 75% at least with your typical panel spacing anyways. When you get down into the C and D soils, it seemed like they were lining up a little bit better. But as you kind of seen here, there's quite a bit more variables that are available to you in the PV-SMaRT calculator that we simply have not incorporated. As I said, our calculator was based on SWMM and it has a lot of limitations to it. I think the biggest one is the vegetation type. We have assumed turf grass for all of those numbers that I showed you. We're typically not planting turf grass under our solar panels. We're at least doing prairie type vegetation and hopefully pollinators and things like that. Everything that I have read and best professional judgment would tell you that you're going to get better infiltration from these deep rooted plants. And our calculator simply does not take that into account. The other thing that's missing from our calculator is the condition of those soils. Are they compacted? What is the bulk density? We don't have those inputs. And I think that we, I think you can you could vary the results of this quite a bit by taking those things into account. So that is our calculator that we have here in the state of Minnesota. We're using it. We're going to continue to use it. I do think we'll have a second version of the calculator at some point in time, and I think we're going to base it on some of these other results that you're seeing from the work that Dr. Mulla and everybody is doing. And that is our approach.

Brian Ross, GPI:

All right. Thank you, Todd. And we have I know some people want to ask questions. We're going to have one more presenter. Robert, do you have slides you're putting up?

Robert Goo, U.S. EPA:

No, I'm just going to talk. Sorry.

Brian Ross, GPI:

Okay. So Robert Goo is, he was I will say, entire duration of this project. He's been, you know, been at the EPA in the ... I was going to say the bowels of the stormwater work for a very long time and and brings a tremendous knowledge. And he asked some of the toughest questions that we had as we went through the process. So we wanted him to kind of have an opportunity to talk about those here. So go ahead, Robert.

Robert Goo, U.S. EPA:

I'm going to continue in that vein, Brian. And it was my talk from EPA's perspective. We are very supportive. of models such as this, and tools and approaches that help communities develop and implement stormwater programs that are protective of water quality and reduce changes to watershed hydrology from the development process. As we all know, this PV-SMaRT tool is an evolving tool and it's one of many approaches that can be used to determine the appropriate stormwater control measures for l arge scale PV arrays and other such similar development types. And I want to say we don't have all the answers yet and this is part of a process and we're all in it together. And I think this effort is a really good start in terms of creating a dialogue, engaging partners, engaging the industry and state and local governments have the discussions about how to treat these systems and what really is appropriate. And I think one of the things that was mentioned earlier was that. There are a lot of assumptions that we're u sing and we need to figure out whether our assumptions are the correct ones for both the development construction process and post development behavior or performance of these systems. From our perspective, many communities do lack the requisite expertise to model these systems and select the best management practices necessary to assure that the water resources will be protected. And so that's I think that's the value of this tool, is that those jurisdictions that don't have the wherewithal, they don't have the expertise, the engineering, expertise, the staff. They can maybe, they can perhaps, use this tool both as a screening level tool and as a permitting tool. Obviously, we haven't applied it yet, so we don't really know how it's going to be used at the community level, but we will get that data in time. And I have a lot of questions to pose. How comfortable jurisdictions be with the tool and how much confidence will they have in this tool, given that there are other competing tools that they could perhaps use, as we had our other speakers discuss. What kind of jurisdictions will really best utilize this tool? The ones that don't have the expertise. The ones that don't have the time. How would they use it? Many, many factors influence how stormwater control measures are required through the permitting process. And it's unclear to me how this tool will be used to inform that process, that process of selecting formal control measures is making the assumptions that you have specific factors on the site, whether it's bulk density or infiltration of capacity or vegetative cover. Another question I have is how does this comport with existing stormwater requirements where you have stormwater performance standards at the state or local level? And how can the PV-SMaRT tool be used to meet those requirements? And what I suspect is that this process will yield exemptions in that process or modifications based on performance of these systems in a given jurisdiction. So over time it will affect local requirements. We haven't really talked about what research needs, sort of touched on it from various perspectives. We only had a handful of sites for this effort. Most of them were on fairly flat surface sites, sites maybe with perhaps some shallow slopes. We haven't fully looked at all vegetative cover issues, force conversion to PV, solar array, deep rooted plants versus shallow rooted plants. Todd mentioned turf versus meadow. Those all are considerations. We tried to address that in the model, but we still have a long way to go in terms of w here we are, whether we'll have some nationally applicable utility for the model. We don't have good data on pre development, post development, runoff conditions and what affects both design, construction and overall long term maintenance have on runoff conditions. And I'd like to see more modeling on that front. And then I'd like to see, as Todd and Lee both mentioned, more comparisons between continuous simulation models or more complex models such as SWMM or hydroCAD and the PV-SMaRT model to validate its utility and make jurisdictions more comfortable that it represents the behavior of this system that they may permit or allow to be built in their jurisdictions. Couple more things. How does, do we have a use it right infiltration method? Is this sprinkle infiltrometer the right way to look at infiltration? Things like that. I'd like to see some comparisons. Is bulk density the right surrogate for looking at a larger set of site specific conditions? And will communities, jurisdictions be comfortable with using that overall, that surrogate for a lot of site specific factors where whether you have d ifferential compaction on the site, other impervious surfaces like geologic features that may affect runoff patterns and behaviors on the site. And then sort of the long term life cycle issues with, can we assume that the system will perform over time? And we need to ascertain that over time. And I would like to say that a lot of these thoughts I hashed over with an engineer named Steve Trinkaus in Connecticut, and he has developed a set of questions and a checklist for New York State with Pace University t hat walk you through this process, and it may be useful to the attendees to take a look at. Thank you very much.

Briana Kerber, Fresh Energy:

Awesome. Thank you so much, Robert. And thank you to all of our panelists for sharing your insight into this project and your evaluations and your questions and feedback on the calculator tool in particular that I know was borne from extensive research that we all got an inside look into today. I know that our panelists have been answering questions in the Q&A box, via typing them out as we've talked. So thank you so much to everybody who submitted a question and had their question answered that way. But I would love to now give our audience members a chance to ask some of our panelists questions live. So I'm going to transition to that at this time. And I'm just going to start from the top of what I see. I've got a question from Janine. How was the recommendation to install deep rooted native vegetation vetted from a fire risk perspective? Maybe somebody can tackle that question for Janine today.

Brian Ross, GPI:

James, I didn't know if that was something of the Inspire work, I think that maybe you might have addressed that question directly. And I'll just say in PV-SMaRT, the insurance requirements are varied. And it's a little hard to, to have made some assumptions across the national basis because we certainly see vegetation standards at different sites being applied in a lot different ways. But James, I didn't know if you had something on the Inspire research on that fire question.

James McCall, NREL:

Yeah, No, I don't think that we have a seen from like a regulatory perspective a change in that. I mean, I know that some of our sites that we're looking at, the recommendation is, you know, a lot of these prairies need a prescriptive burn every 3 to 5 years, but that is definitely not going to ever occur underneath a solar array. So the thoughts were to kind of replicate that by doing kind of like a mowing and then kind of like removal of thatch every so often. And so I know that that's kind of one way that we're looking at. But I have not seen any requirements or at least any kind of national requirements or state requirements on that level. And from the insurance perspective, I think that's going to vary by site. So I can't really answer that. But I know that that's kind of one way that some of some of our partners have been addressing that concern.

Brian Ross, GPI:

Yeah. I mean, the question notes that servers maximum height of 6 to 10 inches and that may very well be true, but that is not uniform at all across across the nation and so or across insurers. But it is something obviously, that would have an impact on the selection of best practices on a given site. And I just want to emphasize that the best practices and the recommendations for kind of the site and development level are to understand and to make the designs consistent with the science that we've kind of laid out here. It is not to be a prescriptive pathway to a particular set of best practices. And so there are certainly going to be some site specific conditions that will make some variation. And we just, the ask here on best practice is just to make sure that you're accounting for changes and and site conditions in a way that is consistent with the science. Okay.

Briana Kerber, Fresh Energy:

Awesome. Well, I'm going to go to our next I apologize if I mispronounced your name. Is there an opportunity for the same type of calculator to be used for urban lawns and landscapes, which can also benefit from decompaction, increased organic matter and establishing permanent vegetation with optimal rooting depth? Who wants to tackle that one?

Dr. David Mulla, University of Minnesota:

I guess I can give it a shot. Thank you for your question, Kateri. The PV-SMaRT Calculator was really kind of designed for disconnected pervious surfaces like ground mounted solar sites where you have, you know, the arrays that intercept rainfall yet allow for infiltration underneath the panels. And then you have this area in between panels where you have sort of the situation that you're describing, which is the urban lawn or landscape. So in our calculator wasn't really designed for use in urban lawns and landscapes, but obviously if you run it without a raise present, it should represent the situation that you're describing. However, other tools already exist that can be used for that kind of scenario that you described. And I wouldn't claim that our tool would represent a big breakthrough for doing that kind of modeling in areas where you're only dealing with pervious pervious areas.

Briana Kerber, Fresh Energy:

Awesome. Thanks. Thanks, Dr. Mulla. I have another question from Ross. Ross is saying it's interesting to hear the soil depth or depth to bedrock is a significant factor. Is that data (field soil depth) something that is available from the NRCS soil survey? And if not, what's the best way to determine or measure that depth for a given site?

Dr. David Mulla, University of Minnesota:

Yes, I can take that as well. Yes. The SSURGO database allows you to estimate the soil depth, soil profile depth, and you can also measure it by doing a soil boring. This depth that we're talking about is the depth to a restrictive layer like bedrock, a fragile open and impermeable layer or shallow water table. And so it's a very important factor in the model and something that I haven't seen a lot of other people trying to account for. Basically, as your soil depth becomes shallower, you get more runoff because the soil has less capacity to infiltrate water and it saturates more quickly, leading to run off. So our thought was that this might be an important factor for developers in particular who are trying to select a site that, you know, if you look at the soil depth for various sites you're considering as a developer, you could run those through the PV Smart calculator and quickly really kind of try to quantify what the effect of that single factor is on runoff. And it may be that, you know, if you have one site that's really shallow soil and another site that's more deep soils, you might want to prefer building the ground on a PV site at the deeper soil site so that you could mitigate more of the runoff and and and install fewer engineering practices that would capture the runoff and store them. So if you want to if you want to measure, you can do that by just doing a soil boring and going down to the restricting layer and measuring that depth. Or you can go to the SSURGO database from NRCS.

Brian Ross, GPI:

Yeah. And I'll just add to that, that we did existing practices that were done at least at the state level and some extent in local. And we did not find anybody who from a stormwater standpoint, was looking at soil depth or that kind of infiltrative capacity question that David was just just talking about. So it is actually, that that is one of our big surprise findings here, is that there's a major component here that kind of comes into play in terms of water quality impacts or water quality opportunity. When you have actually a deep soil depth and you have, for instance, an impaired water that maybe could be benefited by by solar.

Briana Kerber, Fresh Energy:

Awesome. Well, Todd, I think we have a you. Someone in the Q&A box said that they have checked your Excel file that you shared during during your presentation, and they're just wondering which cell would give them the total generated runoff. I don't know if you can confirm that for us quickly or you can type in the answer in the box too.

Todd Smith, MPCA:

Yeah, I think I know the answer to that I saw the, I saw it there. Are you guys seeing the screen right now?

Brian Ross, GPI:

No.

Todd Smith, MPCA:

Oh.

Brian Ross, GPI:

Okay, We got it now.

Todd Smith, MPCA:

Yeah. I showed you the results box down here to know for your permitting and things like that. But these central boxes here, if I'm understanding the question correctly, I believe the total runoff for the year would be represented by this 188 cubic feet in this particular example. That's what these middle boxes are. It's the average annual numbers. I believe that's true. If you want to get into that discussion a little bit further, I'd be happy to talk to you sometime afterwards. For those of you that are familiar with our MIDS calculator, which you can use to calculate the output of a bunch of different best management practices like ponds and infiltration systems, the output is quite a bit different for that and a little bit more inclusive than what we had here. I think that is the answer to that.

Briana Kerber, Fresh Energy:

Awesome. Thanks, Todd. I've got a question from Greg. And Greg is asking, which model do you follow for compliance when the state and consultant models differ? Who'd like to tackle that one?

Todd Smith, MPCA:

Well, I can talk about that. As far as compliance with the state permit, of course, you need to follow the state regulations and we have adopted this, the calculator that I showed you. If you want to take a reduction on that one inch requirement that we have, that is the calculator that you would need to use for compliance with the state requirements.

Briana Kerber, Fresh Energy:

Okay. Thanks, Todd. I'm going to go next to a question from Ethan. Ethan is asking, are these sites being mechanically managed for vegetation control or grazed by sheep? I know we talked a bit about this. Or some combination. Did the data show any meaningful difference in runoff with mechanical mowing versus grazing?

Dr. David Mulla, University of Minnesota:

Okay. That's a great question, Ethan. In our five experimental sites, we did have some variations in management. Some were grazed, some were mowed, some were left to grow. And we haven't fully, you know, evaluated the differences yet for those conditions. But that is a question that we are looking to answer sometime in the near future.

Briana Kerber, Fresh Energy:

Thanks, Dr. Mulla. I've got a question from Amy, and I think this one might be best to go to James. Amy's asking, how do you balance establishment of prairie with need to mow to avoid shading?

James McCall, NREL:

So I think that there's there's a couple of So basically, even during the establishment or prairie process, during the first couple of years, there is going to need to be mowing events just to kind of prevent kind of weed and other type of kind of competition. So that's just kind of a natural part of just establishing the prairie in terms of actual shading on the panels there. We've seen a lot of different responses to that type of question. We have seen some developers who will just kind of establish prairie and then basically, once it reaches a certain heights of their panels, they will just kind of come in and do a mowing event. We've seen some developers make the decision to kind of increase cost and actually raise the panels to then allow for that kind of height. And then we've also seen some kind of seed mixes that are basically rely on native species that only grow to a certain height. And there's there's a lot of different factors that kind of go into that. And so the claim is, is that the establishment of prairie will reduce mowing events. And I think that we are seeing that that hypothesis is true, but it doesn't really kind of come into effect until 3 to 5 years after establishment. And it's really a much more long term kind of process, whereas the upfront establishment process can actually require some more maintenance than just kind of turf, grass and clover or something else. I think that there's a lot of different factors that kind of go into that, and we are really seeing different responses from industry members on that, on that area.

Briana Kerber, Fresh Energy:

Thanks, James. I'm going to go now to a question from Hannah. Hannah is asking, was vegetation diversity the only factor considered in the panel height recommendation? Hannah's saying that they've heard AHJs say they prefer lower panel height. So there's a reduction in water scour. That's a new term for me. Who would like to tackle that question from Hannah?

Brian Ross, GPI:

I think scour is something for you, isn't it, Mulla?

Dr. David Mulla, University of Minnesota:

Well, we have observed scour at the drip edge we did some modeling on what might happen if you have scour and you have panels or oriented up and down the slopes. And I will say that this is kind of an important factor. It seems as if, you know that small area along the edge, if it's aligned up and down the slope, will create a lot of extra runoff. In fact, it increases the runoff relative to the arrays that are parallel to the contours by about 40%. So I would say from my perspective, it's the orientation of the arrays relative to the slopes. That's the important factor. And then a secondary factor would be how high the arrays are off the ground. There is some research that shows that increasing the height of the arrays to get better establishment of vegetation can have some benefits relating to increased infiltration in the area under the arrays and also can lower the temperatures underneath the arrays, which would lead to higher efficiencies of generating solar power. So there are a lot of trade offs perhaps in this particular area that you've asked a question about and so you could take my answer and dice it up and use it, I guess, any way you wanted to [laughs].

Brian Ross, GPI:

Yeah. And, Dr. Mulla, correct me if I'm wrong, but I believe that what we discovered was that the concerns at the drip edge, which when we talk to people were frequently fairly high, actually turned out not to be as important in the modeling except when the drip edge was parallel to the slope. Then it did make a difference. But otherwise, the drip edge kind of concerns, if you have established vegetation were a lot lower concern and the need for dissipation or things like that in order to ensure sheet flow, if you had established a vegetation was a lot less than what maybe at least some local governments were presuming.

Briana Kerber, Fresh Energy:

Awesome. Thank you both. I've got a few more technical questions from folks in the Q&A, and then I want to round us out with a kind of a catchall question, kind of based on some of the questions that Robert himself raised. So next question in the Q&A is, is from Harold. Harold's asking, is there data on runoff impact of PV from clear cutting of forest versus a cleared field? Could this calculator be used for a situation where he's saying in his case in Texas, 2000 acres of woods would be removed on rolling landscape?

Dr. David Mulla, University of Minnesota:

I'll try to give a quick answer to that. I think we need more more data from these kinds of sites. They haven't been very well studied. The calculator does include an option to consider runoff from a pre-construction condition where there is a forest, and that's just based on existing knowledge that's embodied in the runoff curve numbers that are disseminated by the narcs. So I think that you could get a rough idea of what the change would be in runoff as you go from a forest to another surface cover condition after construction. But I would say that this is an area that probably does still need a bit more research because. You know, there's questions about. Exactly how you deal with the stumps that are left behind after clear cutting. If you leave them, you might have one situation. If you try to pull them or mulch them or grind them, you might have another situation in terms of post construction infiltration. I don't think we have all the answers yet on dealing with those nuances.

Robert Goo, U.S. EPA:

I would agree with Dr. Mulla. TR-55 has some limitations. It does deal with vegetative cover, doesn't necessarily deal well with depressional storage. There are a lot of issues with TR-55 and as Dr. Mulla mentioned, you have differential compaction, you have the tree stumps, you have all sorts of influences, including slope, that may influence runoff patterns. So we do need more information on this, these types of scenarios.

Briana Kerber, Fresh Energy:

Awesome. Thank you both for answering that I've got a couple questions from Greg here. Are you seeing sites stabilized with turf grass in order to close out the NPDES permit quickly and then later those sites are improved with deep rooted plants or stabilize directly with deep rooted plants? Can anybody speak to that?

Todd Smith, MPCA:

Yeah, I can talk about NYPD's permit a little I haven't seen people try to do that with turf grass. It's been proposed by many people to put down something that's green, to get it up growing and to achieve that 75% cover so they can terminate the permit. That's not really allowed unless it is perennial vegetation. That is what the regulation says. So it's not some sort of cover crop. Maybe I will take just one minute to talk about the upcoming NPDS permit. We are going to try and put something in the permit on this subject to allow people to either terminate early or at least stop doing those weekly inspections. Once your site greens up with something, if you're trying to establish pollinators or a native prairie mix. And I think we'll just offer that to all construction projects just to give people a little bit of a breathing, some breathing room on those weekly inspections, which can be kind of brutal if you've got to carry that out for three years. So there is some relief coming on that front in the weeds permit.

Brian Ross, GPI:

And I'll add to that that there's actually, well some of the other states had been doing. And there are at least a couple of states that have tried to address this in their solar specific regulation. Actually, the state of Indiana, I think, put it into their new revised construction general permit. Broadly across any any site where they're using native vegetation that they provided some flexibility on the final stabilization standards. And it is something that we've talked about pretty extensively in our internal discussions about how you might change regulatory standards in order to achieve the improved water quality outcomes that this study suggests.

Robert Goo, U.S. EPA:

And my response is that in some states we you have to have final temporary stabilization, and that has to be and then you don't have post-construction requirements. So the question is how do you deal with that, especially in communities where they don't have well-developed stormwater programs? And they don't require necessarily long term stormwater control measures or have adequate performance standards. So how do you, how do you balance that, especially in states that are not up to par, so to speak? Yeah. And I think Robert, that's a great question that I think Micah in his comment is kind of getting at in the Q&A, and I think it would be great if, to close this out before I end our time today, some of our co-hosts and panelists could talk about what would need to happen for states and other regulators to adopt this PV-SMaRT model if maybe a few of you could speak to that. And then, and then we'll end our time after that.

Todd Smith, MPCA:

Well, as I alluded to earlier, we are looking we'll be taking a look at all of the stuff that Dr. Mulla and these fine folks have been doing.

Brian Ross, GPI:

And we have been. Oh, go ahead, Robert.

Robert Goo, U.S. EPA:

As I said earlier, we need more research. We need more applications of the model and to verify and validate it against other measures, other models and in a variety of sites. Go ahead.

Brian Ross, GPI:

Yeah, and I would just say we have been a number of different state water quality staff. And we have had a few that have already made some changes based upon this. We have not had, of course, the calculator itself in front of anybody except a very, very few cases. And we should probably note that the calculator will be actually posted on the website for everybody's use in somewhere around two weeks, I think is what we're looking at is, if I'm not mistaken.

Dr. David Mulla, University of Minnesota:

I just wanted to also mention that in our we found that not every state was taking the approach that Minnesota uses, which is to try to estimate annual runoff. And a lot of states are basing their decisions about run off on design storms. So that's why we chose to go with the direction we did. With regards to basing the calculator on design storms, we found a lot of states are more interested in using that approach than estimating annual runoff from long term weather records. So it's, but I mean, our tool could certainly be adapted to deal with annuals, annual, you know, precipitation patterns.

Briana Kerber, Fresh Energy:

Thanks, everyone for tuning in to the audio Thank you to our co-hosts, Great Plains Institute or GPI, and NREL, the National Renewable Energy Laboratory. If you would like to stay up to date on Fresh Energy's work, head to our website at fresh-energy.org or follow us on social media. As always, thank you to our subscribers and supporters. If you would like to support Fresh Energy's work, you can head to our website at fresh-energy.org and click donate in the upper right corner. Thanks again for tuning in, everyone.