Season 2, Episode 12: The Water Cycle and Modelling
with Dr. Tricia Stadnyk
In this episode, Episode 12 of Season 2, Dr. Trisha Stadnyk, a hydrologic modelling expert, discusses the intricacies of water modelling and its implications for future water availability and quality. The conversation highlights the challenges of integrating various models, such as climate, hydrology, and water resource management, to address local and global water issues. Dr. Stadnyk emphasizes the importance of adaptive risk-based management over traditional standards-based approaches, advocating for a shift towards resilience in water policy: a water first philosophy. The discussion also touches on the need for improved data collection and monitoring, particularly for groundwater and small streams, to enhance model accuracy and inform decision-making. The episode concludes with a call to action for individuals to become more aware of their water usage and for policymakers to prioritize water conservation and sustainable management practices. The podcast invites listeners to engage with these pressing issues and consider the broader implications of water management on future generations.
Introductions to Dr. Tricia Stadnyk
Welcome to The Gravity Well Podcast. I am your host, Jenny Yeremiy. Here you break down heavy ideas with me to understand their complexities and connections. Our mission is to work through dilemmas together in conversation and process. I acknowledge that I live on the traditional territory of Treaty seven and Metis districts five and six. The treaties and self-governance agreements established by indigenous peoples were created to honour the laws of the land, maintain balance with nature by giving back and uphold reciprocal relationships. This knowledge and intention are what guide The Gravity Well conversation. I ask for genuine dialogue, real hearts, and openness to different perspectives. This is your invitation to find common ground with me.
Jenny:
This podcast is dedicated to the natural world, our children, nieces, nephews, grandchildren, and all future generations. The Gravity Well is on YouTube and streaming wherever you get your podcasts. Join us@thegravitywall.net. Good morning everyone. It’s a sunny day in Calgary. It is lovely to have Dr. Trisha Stadnyk with us today to talk about the water cycle as well as some modelling. This is in the context of conversations we’ve been holding around Water in Southern Alberta. This is also, if you follow the show, episode 12 of season two, but it’s episode four of this series, this miniseries on water that Bob Morrison has been co-hosting with me. Why are we talking about water? Again, just that’s for the general public. We want people who are involved in water to feel empowered to have conversations about the future of water and where we’re headed. And also concerned citizens like myself, geoscientists, that are now very focused on water in our province.
We’ve had a few conversations so far, as I mentioned, the first was on the history of irrigation with Shannon Stunden Bower and Jordan Christianson. Then we’ve had a couple conversations so far on the environment. First on the impacts of resource extraction and then on the water laws and licence system. That’s where we’re at. And today, as I said, we’re going to talk about water modelling and the future of water availability and quality and quantity. And then after that we’re going to go into some stewardship conversations. And then in the fall we’re going to reconvene with some conversations around the future. I know Tricia, you just had a wonderful conversation with the Council of Canadians and in it you mentioned some recommendations which I’d love for you to touch on here, but obviously we want to potentially get deeper in the fall. Okay. I’m going to stop there and let Bob reintroduce himself for us and a little bit for this conversation and then we’ll get into it with you.
Bob:
Okay. My name is Bob Morrison and I’m a retired planner. My career was mainly in water management and since retirement I’ve been involved in municipal issues here in Calgary. And for this podcast I’m particularly interested in where water modelling can take us for the future because it is one of those key tools that’s going to help us understand and predict where we’re going in terms of our water use, our water management, and our water protection. Thanks, Jenny.
Jenny:
Wonderful. Okay, Trish, I have you down as a professor at the University of Calgary in Civil Engineering, with a crossover in the Geography department within the Faculty of Arts. This interesting Social Science dynamic of water, as well, which I’m excited to hear about. You combine engineering, environmental and earth and planetary sciences with social sciences to understand large scale continental water resource supply. Yeah, please tell us a little bit more about your background before we get into this. Trish, thank you.
Tricia:
Yeah, for sure. Thank you very much for having me. First of all, it’s my pleasure to be here and something that’s very near and dear to my heart, which is having a broader based conversation about water and just for people that are interested and want to learn more. I’m very happy to be here. I’m a Canada research chair in hydrologic modelling. I guess my core area is to develop models that simulate water supply, typically speaking on large scales. Looking at how climate change is impacting the overall amount of water and distribution of water on the entire earth, but particularly on continental scales. But I also zoomed down to the community level and take a look at what the impacts of that could be for the ecosystem for people living on farms, for indigenous communities, and just generally people in urban areas. What does drought mean and what can we do to help contribute to all of that? All of that is my area of interest. I’m an environmental engineer by trade and training. I’ve worked in civil engineering my entire career, but it’s only been since 2019 that I joined the faculty of arts to better understand human behaviour around water and response to climate change.
Jenny:
Fascinating stuff. Okay, Bob, why don’t you lead off the first question please.
Bob:
Many people in organizations are involved in water modelling here in Southern Alberta in terms of understanding the system. What roles do each type of modelling play and what have we learned from the different models that we’ve got out there and what are the strengths and weaknesses of the kind of modelling that’s being done?
Tricia:
Oh my goodness, I could talk for a whole hour on that. That’s a loaded question. First of all, I want to say I never really get a chance to talk about the different types of models. That’s something that’s really important to know is that it’s not one size fits all. Typically speaking, the information that the general public gets about the water is after a downstream of maybe five or six different types of models or modelling type analysis. With each one there’s strengths and weaknesses, but there’s also intent in terms of different purposes. It starts with climate models. We can’t do anything without weather and some information on temperature and precipitation. And if you’re like me and you live in Calgary, then you know you don’t really trust the weather forecast that much. And ultimately that’s why it’s difficult to predict water is because we’re at the mercy of the weather forecast and it’s only as accurate as the weather forecast.
If it says it’s going to rain and it doesn’t, then we’ve got too much water in the stream and that water never actually fell. That’s really why it’s such a difficult process with so much uncertainty, particularly as we go forward into futures unknown with the climate system. But from there, typically what we do is we feed that into a land surface model, otherwise known as a hydrology model. Hydrology models simulate how much water supply is generated from rain and snow processes, plain and simple, how much water is there? This is before we as humans have any kind of interaction with the water. It’s like the bulk supply if you want to think of it like that. From there, we might simulate groundwater or groundwater surface water interactions. How much water from the surface disappears subsurface, and that’s a different type of model as well.
Some models in unique situations can combine those two, but typically only very small scale processes because they’re very computationally heavy, meaning it takes a lot of computer power to run those models. We typically can’t do that over large areas. If we’re interested in peak flow for flood prediction or low flow prediction, then we have to run what’s called a hydraulic model. And a hydraulic model literally simulates how much of that water supply ends up in the river, at what point in time and at what time are you going to hit the peak or the low flow as a result of different processes that are happening. Those are also the same type of models that we use to do floodplain mapping. All of your insurance rates, if you happen to live in a city, are determined based on hydraulic models that are taking the information from hydrology models and distributing the water across the land.
As I said, we might want to have focused groundwater studies and look at how much water is long-term. That’s a process that acts on hundreds if not thousands of years. A very different timescale than all of the other types of models that I’ve talked about. And there could be very detailed modelling of that. And the last one is actually what we call water resource management models or worms affectionately. I have many international students who can’t remember the acronyms that I’m like, just call them worms. It works, right? Worms rain, but water resource management models are the ones that actually determine how much water supply there is after we as humans have interfered with the water cycle. Once we’ve taken out the water due to water licences, used the water for irrigation, stored it in reservoirs and released it, those are the models that add all those kinds of human interventions and then look at the water supply.
Bob:
Do these all happen separately or are they happening together?
Tricia:
That’s a fantastic question. Bob, very, very few times does this happen together in what we call coupled modelling. Most times this actually happens separately. It’s often what we describe as a modelling chain and literally think of it as that a chain with different links and one model feeds into the next model which feeds into the next model, and you build that information or dataset as you go depending on what the actual problem is, you’ll keep going in that modelling chain until you’re able to answer your questions.
Jenny:
You mentioned that you think globally and then locally as well. I just think about this, is it a result of this understanding of the impacts of water from various activities that we’re doing that’s causing this? Because what it sounds like is we need potentially an upscaling of the way we approach modelling and you’re linking things together because of that potential. We’ve talked about in this room, the compartmentalization of the work we do. I’m assuming it’s a combination of this compartmentalization and then also the problem growing in our understanding. Is that true?
Tricia:
There’s a couple of reasons for it, but you’re very perceptive there in describing it the way that you did. In my work, I look at water supply as affected by climate change. Climate change is a global scale process. It’s something that happens globally, not locally, but it’s experienced locally in terms of its impact on the overall water supply and how much water there is. Really what we need is this global, down to continental, down to regional, down to local scaling through that modelling chain in order to answer the local questions about what climate change means to a community, to a city, to a water supply at the provincial or even river basin and scale level like looking at the South Saskatchewan River. But that modelling chain has to start global because if it doesn’t, then we’re not getting the right, what we call forcing data. These changes are happening and being forced by processes that actually start in the Arctic and feed the entire globe in terms of changing global circulation patterns. That is necessary to use as input to the more local models.
Jenny:
And just to follow up to that, I can’t remember where I heard this, but that you were saying the local, it’s felt locally, are the global models quite sensitive to the local changes? Meaning I understood that the global models are potentially looking at too large of a scale and not being able to sum those local changes which amount to much more than what can be realized in those models. Is that
Tricia:
Absolutely, absolutely the case, which is why I would never use runoff from a global model to make a prediction for what the impact on the water supply at a local community level is. But by going from a global climate model down to a hydrology model that describes how water’s distributed on the land surface, then I take the global scale inputs of precipitation temperature and I use that to feed into the next model, which is a much finer resolution of what the land surface looks like and how the water moves or behaves on that land surface, how much evaporation is lost, those kinds of things. From there, if I need an even more detailed picture, not just what the overall volume of water is, but what is the water level in said community at said time in response to a large storm event, then I have to go to the next level or modelling chain, which would be a hydraulic model and so on. This is where the modelling chain comes in as each model has an increasingly high resolution because we can’t just downscale or use the global model scale information at the local scale. It wouldn’t be accurate enough.
Jenny:
Yeah, I think of that as a geophysicist. I think of it as a large scale versus seismic scale, right? You just don’t have the resolution to be able to see those things locally, like globally, but you certainly can if you look at it locally. Okay, Bob, I’ve taken over. Go ahead. Your turn please.
What contributes to water supply: Precipitation, Groundwater, and Glaciers
Bob:
No, you’re asking excellent questions. You mentioned precipitation, you mentioned groundwater.
Jenny:
Yes.
Bob:
You didn’t mention glaciers in the South Saskatchewan system or just say the bow basin. What’s the contribution from each of those to the water supply that we see in terms of precipitation, glacier melting or groundwater itself?
Tricia:
That’s a complicated question and I wish I could give an actual number, but I can’t. This is really at the forefront of where we’re investigating right now, and these are processes that largely haven’t been studied in detail until the last decade or so because they’re complicated. And the reason why it’s complicated is because there’s a feedback between how the glacier is changing and the climate system and those feedbacks aren’t well represented within the climate models and they’re not as well represented historically within the hydrologic models. We’re working on that and trying to bridge that gap so that we get that feedback back. Correct, because it’s important to give a very specific example, the previous generation of climate models really underestimated the impact of temperature increases on the loss of glaciers and the original projections. If you go up to the Columbia ice fields, you’ll see a museum on the bottom floor and it says the glacier could be gone as soon as 2050.
We now know that that’s more accurately 2035 approximately so much, much faster. And the reason for that is that the previous climate models did not take into account the temperatures increasing the rate of wildfire and the wildfire depositing ash on top of the glacier, which is dark and absorbs more heat. There’s what we call a positive feedback process of climate change that actually works to accelerate the loss of the glacier. These are things that we’re learning as we go through experience unfortunately, but each generation of climate models and models in general gets better as a result of that knowledge. The glaciers and the loss of glaciers are typically simulated within the hydrology models or separately using the information from the hydrology models. They’re extremely important in setting the water supply at the headwaters of a basin. If we look at the South Saskatchewan river basin, we would be wrong for the entire river estimate, river flow estimate or level estimate.
If we didn’t take into account glacier melt, which is the very headwater, the Bow Glacier on the Bow River, and of course the Columbia ice fields for the North Saskatchewan River, these are very important processes. They are included in many of our model simulations. And the loss of the glaciers is now being included in many of the simulations that are being generated today, which is great news. What is poorly known unfortunately, is the impact that this has on groundwater supply. We know the glaciers feed the groundwater system, and in fact, there’s an age old debate between hydrologists and hydrogeologists depending on what side you stand on to say is it groundwater or is it glacial melt? In fact, it’s both. We know that a large proportion of the glacial melt goes directly subsurface and ends up reappearing within the bow river and the South Saskatchewan river further downstream closer to Calgary.
As those glaciers disappear, that groundwater system is going to change and the contribution that we get to the base flow in a river, the flow that comes from the subsurface and leeches into the river is also going to change. And that’s concerning for two reasons. Number one, the quantity of water, particularly at times of the year where the glaciers are the highest and our rainfall is the lowest, which is late summer, early fall, and the temperature of the water, which is extremely important for eco hydrology or fish and aquatic species that live in that river.
Bob:
There’s eco modelling then as well, someplace in the system.
Tricia:
Yes, we haven’t gotten to that, but we were talking about water supply up until now. But yes, taking the output from this very large modelling chain that I’ve already described to you and actually determining, okay, what is the impact to X, Y, z fish health, aquatic species, water temperature, water supply intake is just one piece of this very large puzzle. And the cumulative effects modelling happens with whatever results the modelling chain that I produce or my teams produce outputs. And unfortunately these processes aren’t very well integrated, but it is still that kind of feed forward, keep building that chain, keep adding links as we go to try to answer the questions that different communities have and that includes water quality as well.
Bob:
Okay. Jenny, you may want to ask based on what we heard about logging practices, forestry practices.
Jenny:
Yeah, well sure I can lead into that, but I wanted to touch on, as I do talking about the potentially double counting of water is what I might be hearing,
Tricia:
Not really double counting, it’s more how we describe it. The volume is the volume, we’re not adding it twice, it’s just whether it’s described as glacial melt or whether it’s described as groundwater, really depends on your perspective and your training. I think from observations, we know approximately what the overall volume is. It’s just a question of whether that water goes immediately into the subsurface and becomes groundwater or whether it goes overland and into the rivers, like the bow river from the glacier headwater. And of course we know that there’s both. Some goes into the subsurface, some goes into the surface, we monitor for that and we do have an idea of what that split is, but it’s mostly semantics in the community.
Jenny:
Yeah, I heard you discussing in your conversation with the Council of Canadians that we really just have one system that is separated into three systems. I just noticed that when we’re doing things compartmentalized, I wonder if, again, not a criticism of the work, but a criticism or just a consequence of the way that those stuff is calculated. I wonder if there’s double counting. Yeah, I hope that was understood. I think what Bob was hoping to bring into this is processes like logging. Let’s use it as an example. We just met with Dr. Uni Alila who walked us through his work in terms of understanding extreme weather events related to logging and how it actually accelerates drought long-term being that it takes out those, the highs will remove more sediment, which closes off cements, et cetera. How does a process like that get incorporated? And then we brought in other things like oil and gas, removing water from the system or so we get how complicated it is, but how do these things, this cumulative impact get layered into your work? Thank you.
Tricia:
Yeah, no, those are great questions. And just to kind of roll that all into the double counting part, of course, the ideal would be to have what we call in the community a digital earth twin where all of these processes are modelled at the exact same time simultaneously in one model framework. This is being developed within the modelling community at local skills and then scaling up to global. It is very difficult because we’re really pushing the limits of computational power that’s available to us. And I know that sounds crazy because to most people we have unlimited computational power. We think of things like ai, but really what we’re talking about here is a whole linkage. The way the earth functions is absolutely incredible and amazing. And also a mystery, just like the human body is in many of these linkages, we need mathematical equations, complex mathematical equations to describe every single transfer of a water molecule through the earth system.
And to be able to do that all in one model requires a massive amount of supercomputing to the point that there’s really only one earth system computer that could handle this. And there is clearly a lineup to be able to access that computer and also oftentimes to get the predictions from it, they’re not in time to be able to make decisions on the ground such as do we open the dam gate or not? We need to kind of dumb down the science a bit, put them into smaller compartmentalized models and then run them one at a time. And that’s essentially what we’ve done is just fragment the mathematics in terms of looking at cumulative effects. That’s a great question and I would describe that as FITFIR purpose in my community. We set up a model to answer questions. Those questions have to be defined at the beginning because the choices that I make as a modeller are going to be determined based on what those questions that I’m trying to answer are.
And if I’m looking at the effects of logging, then I know that I’m looking at the effects of land cover change and land cover, how much forest was there, how much forest is there now, and what did that area become? Is it just a bare open area or is it turned to grassland? All of those kinds of things I need to know and I can numerically code the model to actually describe those changes over time with the advent of space-based technology. Land cover that’s dynamic that really we get imagery on a daily basis or every few days, we can update that information in terms of what the land surface looks like, the land cover effect, and then the hydrology model can respond to that land cover, meaning within the model itself, how much water is generated from a storm on a forested area will be significantly different than how much water is generated.
Runoff is generated from a bare soil area and the model can respond to those dynamic changes over time. And that’s essentially how we do it is by changing the land cover and having the model be linked with those changes. Land cover, that’s an example of something we can do within the hydrology model. There are other cumulative effects like fish health that we can’t do within a hydrology model, but the fish biologists would take the water temperature and the stream flow and the water levels that our models would produce, and then they have their own series of models that they would run to look at the impact on the fish health.
Jenny:
Yeah, I can see how the timeframe to be able to make decisions on that would be challenging based on the amount of steps in the process to be able, and then the dependency of these models that are based on inputs that you have no control over, you can only monitor and measure.
Bob:
I was going to talk about the same thing, timing. Because you’re saying you’ve got to get the models all at the same time and then you’ve got to be able to do it in a timely fashion.
Tricia:
Correct.
Bob:
How are we doing on that? Are we being successful? Are we making progress?
Tricia:
This would come down to the type of problem that I have been asked to address. If I’ve been asked to address flood forecasting to look at peak flows, I know that if I’m working with the city of Calgary, I need an answer in a few hours, not a few days, but I have to be able to run that model, update that model, and give them a new answer. All of that process can only take a couple of hours. At best. If I’m working on long-term response to climate change, then I could have a longer timeframe or a longer time window to update the model and run it, which makes sense because I’m also running not a single event or a couple of days worth of flows, but I’m actually running a 100 to 200 year time series for climate change simulation. I need that extra modelling time and I could plan for that simulation to take two months, four months, six months, whatever it takes.
It really depends on the purpose. How we’re doing on that is exactly why we have probably hundreds of models to choose from because the choice of the model will be dictated by the problem because you can’t have a one size fits all solution to be able to do that. If you take the most complex integrated surface water groundwater model out there to most accurately describe the glaciers and the runoff from it, it’s going to take six months to run on this basin and you’re not going to get an operational solution. Instead we take the most important parts of the problem that will give us the best guess of the peak flow, and we run a simpler framework to try to guess our best estimate of what that flow might be. And this sounds like it’s all guesstimate, but these models are ground truth and benchmarked and all this stuff over time and calibrated. That’s a very fancy way of saying that we check the model output to make sure that we’re making appropriate assumptions for the problem that we’re trying to address.
How is water continuously accounted for with rapid changes?
Bob:
But in many ways, in terms of calibration, the goalposts keep changing on you, whether it’s the way we’re using the land or what climate is doing to the hydrologic cycle, how do we somehow get, particularly from an operational point of view, how do we make this all come together in a timely fashion given that time is progressing far faster than we think it is in a way?
Tricia:
Absolutely. And this is one of the reasons why I personally love water resources so much because it is really complex. There’s no playbook for this. I used to live in Manitoba and I had a saying where no, one flood is ever the same. I lived through two 230 year floods out there, the 2011 and 2014 floods, and they were completely different. And you couldn’t use the same model to describe those because the cause effect relationship was different and calibration is really no different. The way in which you approach it is by best understanding the system that you’re working in and what’s really driving the change in the flow or the peak flow, finding the model that best and most accurately represents that, and then calibrating that model to an event that’s very similar to the event that you are interested in modelling. What is changing? Is it the rainfall that’s changing or is it the snow melt that’s changing or is it that you now have rain on snow happening at the same time and then you calibrate to an event on the record that is closest to that event?
Tricia:
And if it’s not as extreme, then you can actually make synthetic events to calibrate those models to do your best to push them further from what our historic record shows. But the key is that the models must be dynamic, they’re calibrated to historical storm sequences, but we’re not setting them to a solid response to the same storm all the time. Meaning if we change land cover over time, then the extreme runoff that’s going to come from that same event from the historic time series is going to get more severe in the future. And that’s the key is that we have to evolve those models over time and make sure that the system dynamics are well represented.
Bob (29:01):
But it sounds like the same kind of problem that the climate modellers have. You’re dealing with probabilities. Absolutely. There is no fixed answer. That’s correct. The poor guy at the end or the poor gal at the end doing the operational models, they need one solution, but they know very well that it’s a range of solutions in a sense.
Tricia:
Absolutely. And this is why we’re now as an engineering community evolving from what we call standards-based practice, which is really you have a storm event, this is the amount of flow to expect from that, and that’s your standard one in 100 year event is what we’ve often heard it called the Calgary 2013 flood is another way that the public has heard it referenced. We are evolving away from that and towards something called adaptive management practice or risk-based management practice. And that is a very simple way of saying instead of having a single one in 100 year flood event, you have a range that flood event will be within, and that’s called the uncertainty envelope or the risk envelope. And that it’s really far more complicated than a single hydrologist could answer to. Say, if you’re designing your pipe for a 1 in 100 year event, this is going to be your flow.
You have to take into account not only the environmental change or the climate change, which that envelope shows, but also your economic resiliency, your social and cultural resiliency. Where is the floodplain? How far are the houses from that? What is the consequence of me being under on that flood event versus what is the consequence of me overdesigning for that flood event? These days, decision making is far more complex for clients and they have to really understand how much economic risk, how much environmental risk, and how much social cultural risk are they willing to accept on being wrong? Because the reality is we know there’s a much higher chance of us being wrong now.
Bob:
In a sense, we have a social cultural economic model someplace in somebody’s head or in the spreadsheets or in the actual computers.
Tricia:
These are things that are probably the future right now we don’t unfortunately have one single model that takes that into account, but what we’re really talking about is modelling these kinds of decision spaces where the environmental or how high is that flow going to be is only one piece to that puzzle that urban planners or urban designers would get that piece of information. But you would also understand the risk level of your city council, where the houses are on the floodplain and what the cost of being wrong would be. That’s not something that a hydrologist can decide. That has to be something that the client who procures the hydrology scenario decides and takes into account. And then you would either choose the lowest, the middle or the top end of that uncertainty envelope depending on what risk you are willing to accept.
Bob:
It’s also a political model and it really depends nowadays, at least in terms of the computer inside people’s heads,
Tricia:
And this is why when people talk about, oh, aren’t you afraid of artificial intelligence taking over your job? I’m like, no way. My job’s just become way more complex. And actually, if anything, the social sciences and the person and the decision-making has actually become more relevant. AI can do a lot, but now we have a lot more to do. It’s going to help us in ways that we haven’t been able to see before then. Thank goodness we’re going to need it.
How to Model for Water Security, Quality and Quantity
Jenny (32:37):
Yeah. I want to back up a little bit because I really appreciate it. In this presentation you just gave, talking about the federal, what your recommendation is, you’ve touched on a little bit here, focusing on economics is one of those pieces and also this adaptive risk-based design that switches, I appreciate that. Can you speak a little bit about what question you would want to ask? Meaning with that in mind, with this framework in mind of a federal water policy framework and mandate? You were talking about how your water model is only as good as the questions it’s asked. If you were given free reign, what would the question be to help move us in the right direction in terms of understanding water security, let’s say both quality and quantity?
Tricia:
That’s a great question at a loaded one, I don’t know that I actually brainstormed that, but I would say that it would have everything to do with what is the resiliency threshold for the Canadian water supply? And I use the word resilient on purpose, not sustainable. I know some people don’t like it, but I need to make this distinction sustainable is what we have today. And preserving the ability to meet that into the future, I would argue what we have today is already inadequate. We are already oversubscribed for water licences in the South Saskatchewan River basin. We are already in a water deficit. We need to do better than that. Resiliency takes into account the ability of a system to adapt and have adaptive capacity in the face of hazards and how that system is able to recover. I think honestly, we need to roll things back.
We need to become much more water focused and water central in terms of our governance and decision-making. And instead of just haphazardly building a community within a city in location X, because the land is available for cheap and there’s a developer who says first, “Okay, well full stop. Is there a water supply to do that?” If we’re going to procure new economic development and grow in industry, not only in terms of oil and gas, which is the obvious low hanging fruit, but also in terms of things like Google data centers or massive computing facilities, okay, full stop, how much water is that going to require? These are questions that we’re not even asking and that’s why we don’t have the models to be able to answer those is because there hasn’t been the demand to do so. But honestly, it’s the most important factor if we are going to continue to grow our population to thrive in this particular location, which happens to be some of the driest regions of Canada and support future generations well into the future with climate change.
Jenny:
Yeah, could not agree more. This thought of to me, can we center our economy on water, water quality, availability, and like you were saying, not just in a human use way, but in an ecologically resilient way. To me that is just massive in terms
Tricia:
And it’s a climate issue, it’s also a social justice and human issue. We know that there are still people that don’t have access to proper and clean water supply. In this day and age, that’s just unforgivable. We need to do better, right?
Jenny:
A hundred percent. And I just think if that was our focus, it would really help us make those decisions. Like you’re saying, for example, the water smart who does a lot of the water modelling, modelled the planned hydrogen projects and was saying you’ve got most of your projects in a basin that does not have the water supply to provide you that try. Again, these are where we are wasting time because we’re not looking at the water picture. A big part of that to me would also be fracking. We have some municipalities mentioned in that discussion that have banned fracking well, but then where is the water coming from because the fracking is still happening and water is still being used for it. One question with respect to this local issue in terms of the overall water modelling effort, and I’m going to say quantity effort, I’d like to touch more on the social sciences in this. Tricia, can you help me because there’s a lot of water that’s being used that I imagine the system cannot incorporate.
Tricia:
Yes.
Jenny:
To be specific, I’m on the watershed, like the watershed council coordinating committee for the Bow Basin, and one of the conversations was around that its tributaries and surface water is not really being accounted for. The use of that water is not being accounted for. Can you speak a little bit about, not necessarily specifically on that, but you get the idea of this social activity that’s happening that is potentially not being incorporated fully in the model.
Accounting for Cumulative Impacts in Water Modelling
Tricia (37:24):
Absolutely. That speaks in part to the type of modelling chain that you would choose to really incorporate decision making around water and water use, water licences, water withdrawals, water storage. We need that water resource management modelling. We do some of that in this province, and actually we do quite a good job of it overall. Water smart, you mentioned they have done quite a bit of that, but we don’t do it specific to the problem that’s being asked, and in some cases we don’t actually have the data to do it properly. A very good example is that when we incorporate water licensing, we have to incorporate the actual value of the licence regardless of how much water has actually been used. Why? Because we don’t actually monitor consumption. We don’t have consumptive use as a dataset at our disposal. If the data doesn’t exist, then I can’t incorporate that into the model.
Maximum licence use is the total value of the licence, but that doesn’t necessarily mean that that individual extracted the full amount of water that they’re able to. And in fact, sometimes it’s less than half. It really depends. And that has a very distinct local impact in terms of the amount of water that is used and the impact on the amount of water that would stay in the river at that particular point in time. That would be a big reason why models could sometimes be wrong or overestimating or underestimating in addition to a lack of data. Sometimes it is just a lack of knowledge, meaning water is withdrawn under permits. We know the point where the irrigation districts withdraw, but then when farmers return irrigation to a river, they often just hook up a hose and return it to the river. We don’t actually have data on what that water return is, how much it’s been gone from the system.
There’s no magic tracer within that water. We don’t know if it was withdrawn months ago or just that day or two days ago. And all of that has a significant impact on the residents time of the water in the river or on the surface. These are all issues that local municipal supplies have been grappling with that significantly impact the instream flow need or the amount of water that’s left in a river at a particular time. And how this is linked with behaviour is number one, conservation mindset. How we use water or how we overuse water, I should say. But number two, how we don’t really think it’s important enough to track it or keep tabs on our water usage. And if I asked you how much water does your family use in a day, you probably, maybe you, but some people, most people would have no idea they’d be pulling a number out of the dark.
That’s not right. This is the single most important thing that we have. It is life sustaining. You can’t go more than three days without having access to clean water. This is something that we all depend on and yet we almost never think about. And that’s where the social sciences come into play. And that then determines our policies and our laws that are made, what we monitor, when we monitor it, where we monitor it, but also how much money is put towards that. And quite frankly, governments are not putting enough money towards keeping tabs on our water systems and water is not prioritized high enough within the overall legislative system for us to be able to do what we need to do to even answer the questions that we have.
Bob:
Well, it sounds like the magpie has stopped heckling us.
Jenny:
It was a greenwashing bird.
Tricia:
Yes. They’re fighting over a nest.
Bob:
I thought maybe it was a modeller that they used for their modelling. In some, you were talking about lack of data in terms of actual water use. Is this fundamentally a problem with not having enough monitoring, measuring devices out there?
Tricia:
Absolutely. And in terms of the large scale monitoring, our federal programme that monitors flows and levels, this has been a constant battle really. There were massive cutbacks in the 1980s. We lost a huge number of gauges and monitoring locations because the government just quite frankly didn’t prioritize the spending. Since then, we’ve been gradually recovering and we have some more monitoring in place to help at the larger scale, but what I’m fundamentally talking about here is the additional monitoring that we don’t even have in place right now. We don’t monitor groundwater adequately. There is no national groundwater monitoring program. We don’t monitor water quality sufficiently. It is very much left up to the provinces and territories, and some provinces have a handful of locations where they grab samples five times a year at best. That’s not nearly enough information to monitor the cumulative effects of changes that we’re starting to see in these systems.
That can happen really, really quickly, and we’re missing a lot of that. We do not have any water use monitoring how much water is actually consumed or used. And I’m not talking about a whole licence or as a city. I’m talking about individual houses to the hour at which they’re using the water. We can really look at not only reporting back to people what their water usage is, but introducing billing rates that reflect over consumption of water that is unnecessary. And that includes not only domestic but also industrial. And then we might actually get to the point where we can clear some of the legislative hurdles for grey water reuse or water conservation practices, particularly for industry. I don’t understand why we’re not reusing water more or making that a mandatory part of new builds. This absolutely has to be something that we prioritize in this part of the world. There have been other regions very similar, Orange County, California, that are 25 years in advance of us in terms of the drought. We’re starting to see that now they have gone to complete water recycling protocols. We know this can be done. We know how to do it. There is a playbook for this. We just have to actually make up our minds to do it.
Bob:
Now, you mentioned the metering of individual households. Is this becoming something like what they talk about in terms of energy use with smart meters and smart grid systems and that sort of thing?
Tricia:
Yes, and I’m very proud to say that it is part of the city of Calgary’s drought response plan, and they have committed to having all houses metered smart metering for water by 2030. I hope we can expedite that, but I’m very excited to see that in terms of people responding to what their water consumption is. That said, the current billing system doesn’t lend itself very nicely to water conservation. The majority of what we pay similar to energy is in distribution fees, not in terms of consumptive fees. We really need to flip that ratio and start putting more priority on consumptive measures.
Jenny:
And I just think it’s fascinating to your point that we see an hourly consumption of and gas, but we don’t see that in terms of water. That is an example of how we have been made water blind in what we do. And even those with this catastrophe that we had last summer, which of course we would’ve known this was a coming issue of course, from years of neglect in our system. But what water is being used for, I’ve learned that 80% of the energy we use in the world is related to moving water in some fashion or processing water in some fashion. We think about how interrelated they are, water and energy. I was saying in a couple conversations ago that for one barrel we produce, we are using one barrel of water. This is not
Tricia:
Three to four, three to four barrels of water for every barrel of oil. In this province where energy comes from oil and gas, we really need to think about water as the limiting factor. Not unlike agriculture, they’ve learned that phosphorus is the limiting nutrient, not nitrogen. That’s the critical one to focus on. For us, water is the critical one, and yet no one’s focusing on it.
Jenny:
Agree. Yeah. And I think about… I see we’re nearing the hour, and I want to make sure I’m respectful of your time. Bob, did you have any questions you wanted to ask before we wrap?
Bob:
Yes. Yeah. Jenny, you had mentioned small streams. Is it even possible to come up with realistic models for smaller streams? And I ask that because if you’re an individual living on one of those streams, or if you’re the fish who depend on that particular first spawning, those streams are very important. Yet our models are very much focused on the mainstream of rivers plus the main tributaries. Is it even possible to model small streams?
Tricia:
Great question. Is it possible? Absolutely, a hundred percent. It is. Again, this comes down to FITFIR purpose. I wouldn’t pick the same model that I use to model the South Saskatchewan River as I would to model processes that connect on a different scale and require more data and more information to run accurately on the small scale. The problem becomes how good are those models? And we don’t actually know because unless it’s a research intensive study where the researchers have committed to collecting the data, we don’t have data at a small scale. The federal program really focuses on basins that are 300 square kilometers or up, which oftentimes neglects these very small catchments that are like 20 square kilometers. And we make some really terrible assumptions with some really basic and primitive models at this point to do our best guess at what the water supply is or the impact of a changing climate. But we really need more information to be able to model those processes in detail.
Bob:
Okay. Final question from me, Jenny, if it’s okay. How do you model the legal system?
Tricia:
We don’t. I’m not a lawyer. This is a human social science problem. And honestly, this is exactly why after 20 some-odd years in the physical sciences and climate change and water resources, I voluntarily signed myself up to learn more about social studies and human behaviour because these are decisions that are far more complex than the climate system and interrelationships with water. And that’s complicated enough. But humans are a whole other level, and for the life of me, it’s very tricky to model human behaviour, even in response to large scale catastrophic events, which is what our policy is often defined from or our legal system. Catastrophic failures or ruptures of water mains defining laws that help protect us against that is very tricky because it all depends on the human or societal response and that.
Accounting for FITFIR in Water Modelling and Key Takeaways
Bob (48:38):
Okay. I think I was asking the wrong question, but I got the right answer except for one thing in terms of first in time, first in right, is that actually modelled in particular these operational models?
Tricia:
Not all of them. It has to be intentional and it has to be embedded as rules in terms of how much water can actually pass the border at a certain point in time. Water Smart has done some of that work. My team has done some of that work, and I know that Global Water features based out of the University of Saskatchewan has done some of that work. It is possible. It isn’t done all the time though, and these are the things that need to be done all the time because it’s essential to look at the adequacy of the decisions that we’re making.
Jenny:
Awesome. Okay. I have another loaded question, I’m sure, but this is more just thought provoking, Tricia, and I hope you have some thoughts on this as well. But I think about your comments with respect to the future and where we need to be headed in terms of federal, this is interprovincial concerns, et cetera, all of those things. But I think about this modelling and you’re talking about the cumulative impacts, but my question is are there conversations happening around what restoration looks like and how we can rebuild water storage capacity? Because I think of, for example, I’ll use myself in the oil and gas industry, if we weren’t developing new, we could turn around and start modelling really well how we remove sites off the landscape and how we restore the system function, let’s say water land system function. To me, what are those conversations looking like and is that a third option that’s even out there of the discussion? Because we talk about, for example, in your conversation, and I’ll make sure to share this Council of Canadians conversation, these dams and infrastructure systems that are really thinking on an annual basis or maybe 25 years out and not thinking about this thousand year timescale that you really need to be starting to shift gears to. I’m just curious, I’ll stop there. In terms of what are we seeing for optionality for people in terms of do we develop, do we restore, do something in between? How are we making those decisions? Thank
Tricia:
You. Yeah, no problem. Jenny. I would say that that is part of the shift from standards-based decision making to adaptive decision-making. Adaptive risk-based decision making takes a seventh generation view to everything. Is it okay for today? Is it okay and if not better in the future? And how does it recover from disaster and pressures and hazards that are likely to be presented in the future? And I think that’s the key is that we have to start thinking much longer term in terms of looking at consequences and effects. But the other missing piece to this is that we’re really good at defining the cost of damages. If you don’t put in that dam and there’s a massive flood, how many communities downstream get washed out? What is the cost of that versus if we put in that dam, then we save all those communities full.
What we don’t look at is what is the cost to the environment in monetary terms? Ecological cost and what is the benefit that we receive when we restore? If that dam is to be removed in the future and we roll that ecosystem back to what it used to be, what are some of the benefits of not having that dam anymore, like upstream wetlands and beavers and all of that that helps to naturally mitigate flooding but also has a secondary benefit to water quality and it’s a massive benefit. And also groundwater, we do not value that right now. This is all called nature-based accounting. The United Nations has actually moved to have the equity for a lot of infrastructure, national infrastructure and international infrastructure projects take this into account. But unfortunately, there isn’t a strong accounting system that currently knows how to deal with some of those costs and benefits of nature-based solutions and natural restoration. It’s an evolving science right now. It is something that the rest of the world, particularly Europe, is far more advanced at than Canada right now. It’s not currently written into our laws that engineers or project designers have to include this. And that is a big mistake because we shouldn’t just be asking what is the cost of not doing something? We should be asking what is the cost of doing it to the ecosystem and to the water quality and to the cumulative effects and the health of that system overall.
Jenny:
Right. And I’ll just finish with, to me, I think about the glacial loss and our ability to potentially slow that or potentially restore it if we were to really meaningfully move on climate quickly. Anyway, I’ll stop there. Bob, I’m sure you have some closing thoughts or questions for Tricia.
Bob:
This has been a fascinating discussion and you managed to take some very dry material about modelling, which I’m sure it can be quite. Thank you very much. I really
Tricia:
My pleasure
Bob:
Listening to you and very much appreciated you coming onto the podcast. Thank you very much.
Tricia:
Thank you for inviting me. It was my pleasure.
Jenny:
Anything that we missed, Trisha, that you would love to hit home before we wrap? Yeah, anything that, or even a question for the future you’d like us to think about? Anything,
Tricia:
I’d like everyone to think about their role in water usage and water conservation. I don’t think we have to wait for this to be legislated. I don’t think we have to wait for the powers that be to tell us to do this. We know it’s the right thing to do and anyone listening to this podcast up until this point is thinking about it naturally. I challenge everyone to figure out what their own water usage is and how they can improve on that. Because honestly, that’s just the right thing to do. And the more people that do, the more pressure is applied and the faster the change can happen legislatively as well.
Jenny:
Yeah. Thank you for that. I think there is such an important role for us to play in terms of bringing water awareness into our lives. And one of the conversations we had was just around licensing and FITFIR and the laws. And the question came down to if we had an emergency, what would we need to do? And it comes down to those conversations, those genuine on the landscape, what are we doing with our water conversations? The more we do that now you’re suggesting the better.
Tricia:
That’s right.
Jenny:
Fantastic. Okay. Thank you so much. I certainly hope we get an opportunity to work with you again, Trisha, I really appreciate the work you’re doing and thank you for giving our audience this information.
Tricia:
Thank you for everything you’re doing.
Jenny:
Take care for now.