The First Sixteen is Agriculture and Agri-Food Canada's podcast series that explores the freshest ideas in agriculture and food. Each episode explores a single topic in depth—digging deep into new practices, innovative ideas, and their impacts on the industry. Learn about Canada's agricultural sector from the people making the breakthroughs and knocking down the barriers! Farmers and foodies, scientists and leaders, and anyone with an eye on the future of the sector—this podcast is for you! A new episode is published each month.
Episode 024 - Modelling the future of water
To predict the future of water, we have to understand the present. That's exactly what AAFC's Dr. David Lapen and Dr. Steven Frey from Aquanty Inc., are endeavoring to do. Listen in as they discuss their work on a complex, country-wide hydrological modelling tool. It is designed to help researchers, producers and decision makers anticipate water resources of tomorrow and make better, more informed decisions today. This is the Canada 1 Water project.
Steven: I grew up on a farm in southern Ontario, so I’ve always had an appreciation of the challenges that farmers have faced with managing and trying to anticipate how water availability or lack thereof is going to impact their operations. Right now, a lot of people have kind of a gut feel as to how climate change may impact their water resources. But we’ll be providing the datasets and the tools and actually the outputs from the modeling to really put a quantitative spin on how things will be changing. And with that, I think is a great use for a project like this to develop end points that can be directly used by producers to help guide their planning for 10, 15, 20 years down the road or even a few generations down the road.
Kirk: Welcome to The First Sixteen. I’m Kirk Finken.
Sara: And I’m Sara Boivin-Chabot.
Kirk: You just heard from Dr. Steven Frey, a senior scientist at Aquanty Inc., and he’s also the hydrologic modelling lead for the Canada 1 Water project, which is the subject of our episode today.
Sara: The project is led by Natural Resources Canada, with a team-up with Aquanty and our own Agriculture and Agri-Food Canada. Dr. David Lapen, one of our research scientists, is also here to drive home the importance of this project for agriculture.
David: We’re generating these simulations using climate and weather information, future climate scenarios, things like that. So you can imagine that if we project into the future, what’s going to happen in 10 years, 15 years, 50 years? What might the water resources look like in Canada in the agricultural regions as well as beyond? And that is what Canada 1 Water is.
Sara: The objective is to create a single, large-scale model of all the available water in Canada. Surface water and ground water, from coast to coast to coast.
Kirk: It’s going to show us how water interacts with the environment right now. And then researchers and scientists can take that information and tweak it based on future climate forecasts. What happens if the temperature rises in this area, for example? What happens if there’s another drought out West? Using this tool, they’ll be able to predict possible futures for the state of our water.
Sara: And this is huge for agriculture. Climate change is on most people’s minds these days, but especially for people whose livelihoods depend on the climate. You can’t grow your crops if your fields are too dry. Or if they’re flooded.
Kirk: So without further ado, let’s dive into the future of water in Canada.
Sara: That was a cheap pun.
Kirk: Shamelessly cheap, yes. All right, welcome, Steven. Why don’t you take us back to where it all started. How did Canada 1 Water begin?
Steven: So Canada 1 Water at its core is a project funded by Defense Research and Development Canada under the Canadian Safety and Security Program to look at climate change impacts to water resources across the nation. And when we say water resources, we’re talking about ground water, soil moisture, and surface water. So we’re really looking at the entire terrestrial hydrologic cycle when we’re investigating how climate change is potentially going to alter or change the state of water and the volume of water across the country.
Sara: Hold on, that’s interesting. You said it all started with Defense?
Steven: Yeah. Defense, Research and Development Canada has a program where they’ve identified climate change as a potential, I guess, threat to Canadian safety and security. So there is a funding stream made available for groups to apply to in order to get funding from the Defense Department to support research into climate change impacts on Canada. And that’s where we really got the launch for Canada 1 Water. And since the core funding from Defense, Research and Development Canada – we’ll call them the DRDC for short – since that core funding came in, there’s also been funding provided through Natural Resources Canada in their Geological Survey of Canada Department, and Agriculture and Agri-Food Canada have provided funding into the program as well.
Sara: How are they contributing to the project beyond the funding? How does this fit together with what you’re doing at Aquanty?
Steven: So if you can imagine, you know, we’re trying to simulate water movement across the land’s surface through the soil profile and through the groundwater system. So if we start at the groundwater system, we’re working with the Geological Survey of Canada to assemble datasets that represent the extent and, kind of, efficiency of the regional aquifer system. So the major groundwater flow systems, we’re trying to resolve those in the subsurface component of the model, and we work with NRCan for that. And then in the soil, we obviously work with the experts at Agriculture Canada to use their best available soils data in combination with additional data we’re getting from the Geological Survey of Canada and Natural Resources Canada to define peatland extent and permafrost extents to put together kind of a digital representation of the soil layers and the near-surface layers within this model. And then on the land surface itself, we’re assembling topography data from the best available regional datasets to come up with a homogenized digital elevation model or topography model for all of Canada.
Sara: So in order to make a model for Canada’s water, you kind of have to make a model for all of Canada? Mountains, valleys, different types of soil that might absorb and transmit water differently? How do you, you know, put a rope around an idea that huge?
Steven: So I like to use the analogy of Lego bricks. And by the time we’re done building these models, it looks like a small watershed assembled with Lego bricks. And each one of these Lego bricks carries a certain set of properties that governs how water moves through it or over it. And in the case of the Canada 1 Water models, we’re dealing with millions of Lego bricks.
Kirk: So you’re like the older sibling who follows all the complicated instructions to build the Lego set so the younger kids can play with it after.
Steven: Yeah, I mean, it’s absolutely fantastic. This is like, you know, getting to play in a sandbox as a kid, right? But it’s your day job. And yeah, it’s spectacular. We use, you know, the best available technology. We’re working with experts across the country in a myriad of different departments and universities to do a project that really has national significance. And it’s the type of project, like, there’s no one person behind it. You know, there may be some figureheads who are the principal investigators and some of the lead scientists, but it’s a massive collaboration of multidisciplinary talent in order to put all the pieces of the puzzle together.
Sara: And who’s going to see this puzzle, or play with this Lego set when it’s done?
Steven: So one of the objectives of the project is to make all of the data that’s being assembled and vetted for use in the project and use in model construction, that’s all going to be publicly available, so it’s all going to become open data. All the models that are being constructed are going to be public domain as well. So they’ll all be published through the open data archives at the Geological Survey of Canada, as well as the climatology data. And beyond just putting the climatology data that we develop into, like, open data archives for Canada, it’s also going into the CORTEX database to be used as a regional, kind of, state of the art regional climate projection information for Canada. But it’s kind of a national, or actually a global archive for regional climate projections. So we’re doing as much as possible to make sure all the components of the project become open source and available for future resources for researchers down the road.
Kirk: How would that change the research landscape as it is now?
Steven: A lot of the challenges right now with conducting research as a graduate student or as a postdoc is you spend a massive amount of time trying to assemble your data. So before you can do any science with the data, you have to try and assemble it and understand it and make sure it’s vetted. Well, by making these national scale data products available to researchers and students, you know, they don’t have to spend as much time on the data assembly and the data vetting. Hopefully they can get right into the science. And by having models pre-built for them, then they can take advantage of all the expertise around the science table on the Canada 1 Water project.
Sara: I want to know, what was it like when you saw the first regional model?
Steven: It’s really cool, actually. Like, in our minds, we already knew what it was supposed to look like. But when you actually see it kind of emerge on the screen, and we work with, you know, people who are really experts on manipulating and visualizing these model datasets. So it’s impressive from an outsider’s perspective. It’s just, it’s quite cool.
Sara: You know, I’m not a scientific modeler at all, but now I want to play around with this program.
Kirk: Me too! I can’t imagine how cool it’d be to see a full 3D model of all of Canada, right down to the types of soil in the ground, and then like, the movement of water through it.
Sara: Well, the project’s still ongoing, so the rest of us won’t be able to see it quite yet. But I think we know someone who has.
Kirk: Yep, sure do. Dr. David Lapen, the Agriculture and Agri-Food Canada lead on this project has seen these models in action.
Sara: Exactly. Let’s go to him, and hear what he has to say about it. David, we’ve heard from Steven what it was like when he first saw the Canada 1 Water models. What was it like for you?
David: The data assembly aspect of this initiative is a Herculean big data effort. I’d say it’s one of the biggest ones in the department that we’ve been involved in. And getting all these layers together that are influencing the hydrological and climate balance, so to speak, you can imagine, right? It’s huge. And stitching together different kinds of data sources, that’s something that is, I want to say a science in itself. Remarkable technical capabilities are required for that. That to me is “Wow.” When they’re able to stitch these datasets together, that alone is a big deal.
Kirk: So you’ve been leading our department’s work on providing information on the soil for Aquanty. We know what led to the development of Canada 1 Water, but where are you at now?
David: This project is a few years in. It’s on schedule to build this Canada-wide platform for insight into hydrological processes. And it’ll evolve to estimate benefits to the sector that are directly or indirectly hinged on these water resources at a greater temporal and spatial fidelity. And that’s ultimately I think what would be the ultimate next steps, taking this coarser scale modelling approach and putting it into something that has a higher fidelity with respect to farm-scale decision-making.
Sara: So is this something producers will be able to make use of as well? Not just scientists? Let’s say I’m a producer in Gaspésie, which has seen a lot of pattern change in the last few years. Too much water, a few years without any water, hay production issues related to climate. So say I’m a producer from that region. What will Canada 1 Water provide to me and my neighbor as a tool?
David: It would provide a sense of what is going to occur in the future in the context of viable commodities, for example. If there are conditions that are going to be predicted in the context of, say, too wet or too dry, it provides a decision support within yearly windows to give you some sense of what commodities would be viable in that area. And so, you know, we may see areas that just are not going to be viable anymore for agriculture because it’s, you know, the groundwater has disappeared and they have recurrent droughts and whatnot. And it’s just not cost-benefit to do agriculture in those areas. And, likewise, viable areas in the future, or in the north, for example, as the climate’s warming and higher value crops are being grown in more northerly areas, you know, what kind of areas are going to be viable in the future from a water side, climate side? And certainly these kinds of tools are going to give us that information.
Kirk: Right now it sounds like a very large-scale project. Are there plans in the future to bring it down to a scale of individual regions, or even individual farms?
David: The Canada 1 Water starts coarse. So it’s the thin edge of the wedge for a national scale uniform modeling platform. From that we could nest in, and I’d call it nesting, hydrological nesting, where we can kind of look and focus on particular areas or sub-watersheds and be able to then understand more of the hydrological or soil resource nuances with respect to how water is used by agriculture or impacted by agriculture. So, yes, being able to say something about the practices on a farm is something embedded in the Canada 1 Water from almost a subregional scale. And that’s something that we are doing in a more refined scale in other areas in Canada is we were able to then look at how field management practices impact, say, watershed, sub-watershed scale processes that impact downstream receptors like municipalities and fields and etc.
Sara: Do you see this kind of data and analysis influencing policies in the future?
David: That’s probably, I think, one of the big dogs in this, absolutely. It will put on the map we hope for Canadians and the sector the importance of groundwater in particular. It’s going to be able to provide kind of a finger on the pulse of water resources in the sector. What can we expect and how should we start preparing for it? And again, we’ve seen this at the municipality level, as an example, where they’re asking us, “Hey, look, you know, how big should I make my culverts based on what’s going to happen in the future in terms of land management, drainage, climate and what’s being grown on the land, and what’s being conserved on the land from the context of natural capital.” There’s great concern about that. So, yes, if we can put on the map the relative impacts and vice versa of these water resources on agriculture in a very, very holistic and national scale way, it will have a firm impact on policy in Agriculture, in Natural Resources Canada, from the mining sector, the forestry sector, and of course Environment Canada and the environmental sector as well. And human health as well.
Kirk: So we know how Canada 1 Water is helping researchers, producers, and policy makers. But what about you personally? What do you want to see with the future of this project?
David: Yeah, I think the first step is a finger on the pulse of what we can expect in the future. Start with that. What are the main water resources used for agriculture? What’s going to happen to them under a changing climate? And be able to say something about that for the country. And we can focus on the areas that are currently under agricultural productivity. But in this case, we can focus on areas that could potentially be under agricultural productivity or taken out of agricultural productivity due to other stressors, water-related, climate-related included. And so we hope that again, you know, these kinds of very robust engines to predict water resources throughout the country will be used to help develop sustainability metrics more reliably, carbon sequestration more reliably, greenhouse gas emissions more reliability, these kinds of things. Because all those things are dependent upon, you know, water and temperature and, you know, kind of core drivers. And when you can predict them responsibly and more robust and accurately, then that gives us better insight into what we might expect in terms of meeting different goals, meeting the 2050 goals, 2030 goals, biodiversity, whatever it is. It’s a variety of targets that the department wants to achieve. These tools can help there.
Sara: How does it feel to be modelling information for 2050? Or even, like, the year 2100? You’re looking so far into the future to times that, you know, you and your team and Kirk and I, none of us will be around to see. How does it feel to be working on a project where the timeline is longer than the average human lifespan?
David: I think it’s terrific. You do have to kind of jump into a different perspective bucket with it. You know, you have to kind of understand that there are a massive amount of intrinsic uncertainties associated with that. And given those uncertainties, as we all know, you know, you’re projecting the future. How do you know what’s going to happen? You know, and we’ve seen it here. You know, we’ve seen the war in Ukraine. Bang! All of a sudden that changes things, it creates new pressures or bang! There’s more hurricane pressures a particular year, and that changes things. And I would say that, you know, being able to do that and recognizing uncertainties, but being able to say, here’s our general feeling of what the state of the art predictive engines can generate on the state of water for this country is a big deal. It’s a huge deal, in fact. I mean, nothing grows without water and everything alive needs water. And where does it come from? Right? And also balancing being able to say something from these generalized projections about how to balance water use by humans, the environment, you know, in tandem. All the agricultural decisions, all the commodity and, you know, the energy sector, etc., they all have to be considerate of the environmental component of this. You know, the environment needs water to support services, ecosystem services and so on. And that is something that this kind of approach can help us get there. So I think it’s just a terrific place to be.
Kirk: “Nothing grows without water.” It’s simple, and it’s true. And it shows just how important this project is for all Canadians.
Sara: We heard some pretty high-level science in these interviews. But projects like this bring the science down to everyone. It’s not just about these big concepts and ideas. It’s all about real problems we’re dealing with, and concrete solutions.
Kirk: Yeah. And Steven actually had a great last word on that subject.
Steven: It’s always good for us to, you know, try and communicate to the people who can ultimately benefit from the science. We don’t necessarily just want to do science in a silo for the sake of, you know, our own interests. It’s really beneficial to try and push it out into the real world. I think we all want to do our part. I think everyone has to recognize we’re not going to be the solution in ourselves. But as part of a team, we can hopefully make a difference and we can hopefully create tools and data products that other people will be able to come along after us and use to keep working on these problems and challenges. And, you know, if this is just the first milestone in a long road towards improving Canada’s resiliency to climate change, then I’m personally quite happy to be part of it.
Kirk: So Sara, what did you think of these interviews?
Sara: Well, obviously these are not weather predictions, they’re climate predictions. It won’t tell us what the year will look like or if we should irrigate next Thursday, but it helps to make general decisions regarding land and water management. Like, producers right now are at a place where they can’t really look how their grandparents did the things. They need those tools to predict in which zone they are now, or in which zone they will be later.
Kirk: Yeah. You know what, I just feel like we’re in this whole new era where there’s these new tools that are evolving and they’re becoming available on the market, and, like this one is a huge, huge project. But these tools are based on data and algorithms, and I just feel like we’re going to be able to make better decisions, you know, with this information, and not decisions based on intuition so much.
Sara: Yeah. Talking about tools, if you want to hear about more tools, subscribe to The First Sixteen! We’ve got a lot of fascinating topics lined up dealing with both the present, and future, of food and agriculture.
Kirk: And until then, you know what to do.
Sara: Try something new.
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