Investing in Regenerative Agriculture and Food

259 Ichsani Wheeler and Lenka Danilovic – How to make water our friend again thanks to hippies with satellites and indigenous water management

November 07, 2023 Koen van Seijen Episode 259
Investing in Regenerative Agriculture and Food
259 Ichsani Wheeler and Lenka Danilovic – How to make water our friend again thanks to hippies with satellites and indigenous water management
Show Notes Transcript Chapter Markers

A conversation with Ichsani Wheeler and Lenka Danilovic. Ichsani is a scientist, co-founder of OpenGeoHub and EnvirometriX, while Lenka is an hydrologist and intern at OpenGeoHub. In this conversation, we talk about the world of remote sensing, and we unpack what the eyes in the sky can help us learn about indigenous land and water management.

How far back can we look at arid landscapes that used to be managed to produce abundance? How did they manage extreme weather events like El Niño, or did they see them as extreme abundance events? With a wealth of practical science knowledge between Ichsani and Lenka and the absolute cutting edge of open-source remote sensing, this is a rare treat to understand how to make water our friend again.

This episode is part of the Water Cycles series, supported by The Nest, where we interview the dreamers and doers who are using the latest technology to figure out where to intervene first. They are making or trying to make the investment and return calculations. so what is missing, what is holding us back? Maybe we lack the imagination to back them and try regeneration at scale.

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Speaker 1:

With the Norse pleasure. I'm welcoming back Isch on the podcast to dive deeper into the world of remote sensing Together with her colleague Lenka. We unpack the eyes of the sky and how they can help us to learn more about indigenous land and water management. How far back can we look in arid landscapes that used to be managed to produce abundance? How did they manage extreme weather events like an Nino, or did they see it more as extreme abundance events, with a wealth of practical science knowledge between the two of them and the absolute cutting edge of open source remote sensing? This is a rare treat. How to make water our friend again, enjoy.

Speaker 1:

If it's true that water vapor accounts for 60-70% of the greenhouse effect, well, co2 only accounts for 25. Why do we rarely discuss it? Well, we choose to ignore it because it means we literally need to re-vegetate the entire earth. Bring back the marshes, the mangroves, the perennial pastures with trees and regrow real forests that can bring back rain in strategic places. In short, bring back life, lots of plants, trees, animals back to many places on this earth natural climate engineering. It is time we take our role as keystone species super seriously.

Speaker 1:

In this special water cycle series, we interview the dreamers and the doers who are using the latest technology to figure out where to intervene first. They are making, or trying to make, the investment and return calculations and plans. So what's missing? What's holding us back? Maybe we lack the imagination to back them and try regeneration at scale. We're thankful for the support of the Nest family office in order to make this series. The Nest is a family office dedicated to building a more resilient food system through supporting natural solutions and innovative technologies that change the way we produce food. You can find out more on the NestFO.

Speaker 2:

That is thenestfocom.

Speaker 1:

Welcome to another episode. Today we have a very special one, obviously, focusing on water cycles, as this is the water cycle series, and we have Isch back on the show after a year and a half, depending on when you listen to this. We interviewed her and Tom in February 2022. We're recording this at the end of September 2023 and we have a new face on our new sound on the podcast because we're not a video podcast yet and probably won't be. We have Lenka here, hydrologist and an intern at the Open Geohupt, to really unpack water cycles, eyes in the sky, indigenous water management and so much more. So welcome to you both and welcome first of all to Lenka for the first time here. To start with a personal question how did you end up in the water and soil space of all the other career paths and rabbit holes you could have fallen into? Why this one?

Speaker 2:

Well, I thought that you were going to ask why soil, but then my answer would have been water and soil.

Speaker 1:

I think it's intimately connected.

Speaker 2:

My bachelor was schooled in soil, water and atmosphere. Basically, I studied interactions between all of these parts of earth, and then my master is called earth and environment, which means that I went even broader, but the processes remain the same. Why? Well, I've always been looking at interactions and nature. I think I spent a lot of summers in the countryside, and I'm a city person. I'm privileged enough to have a summer house in the countryside and there I've always looked at why are things the certain color that they are, or why does the water flow in this direction? So this really led me to want to study the physics behind it, and today I think it's crucial for survival in essence.

Speaker 1:

I think it's a very good summary of this series as well. We can't not afford to not look at it. It's so crucial. And then how did that lead you to open GeoHub and the internship which you're about to finish and you're going to do fascinating PhD, finishing your master. So there's a lot to come. But what led you to the open Geo space and literally space side of things?

Speaker 2:

Well, simply because they're probably the best in what they're doing.

Speaker 1:

You're just saying that because issues are not.

Speaker 2:

No, no no, no, this is something we have, this mutual recognition when people have the values and the dreams, the visions that you share. And I wanted to learn how to code, which I managed to some extent, or I scratched the surface.

Speaker 3:

She's great she's being so modest. She's done awesome.

Speaker 2:

But they have chunk of data right and I want to see, as a hydrologist, what can we do with it and whether we can make that useful, and I'm sure we can.

Speaker 1:

So your internship at Open GeoHub? What did it entail? Just for? We have to probably translate it into dummy language, but I'm going to be the translator and ask a lot of clarifying questions. But what did your internship entail?

Speaker 2:

So basically what we did is we evaluated this invest suite of tools it's made for. It's a software made for integrated valuation of ecosystem services and tradeoffs, so it's basically a tool set with many different models that use very simple spatial explicited data to create outputs that can essentially help decision making in relation to ecosystem services. And the outputs of these different tools are not necessarily putting a value on natural processes, but they can also be about quantification For example, in a landscape, where does the water go? And they work on regional and local scale. And we wanted to test multiple models to see how this works and whether it will be useful for us for later.

Speaker 1:

So the set of models was already out there and you were approached by a client of OpenGeoHUB to say, OK, can you test if they're useful, if they're relevant for us or not? How good are?

Speaker 2:

they, yeah, and if we can maybe improve them, work on them, yeah. But what is behind it is that we wanted. The question is OK, you have these models, but can they tell you something about water or soil management upstream that will affect the municipalities downstream, so about connecting the catchment, basically.

Speaker 1:

And then it gets super concrete because it's literally about flood mitigation or flood prevention. The question was and drought, could interventions upstream in a water catchment area? Of course we know it does interfere, but can you prove that there is that connection between interventions on farmland, forestry, of whatever land upstream compared to the effect of potentially preventing floods and droughts for the municipality downstream?

Speaker 2:

Yeah, because that's the same problem floods and droughts.

Speaker 1:

Yeah, flood, I mean we had somebody Alphalo and was specifically saying drought, fire and flood is like the cycle. Not always fire in many cases, yes, but that's sort of the rhythm many landscapes, unfortunately, go through these days. So was there fire involved as well in this one? Not yet.

Speaker 2:

OK, Not yet, but we are looking at deforestation effects and we tested it for California, for example. So we already spotted changes in droughts and floods in relation to deforestation as a consequence of fires. So it's still linked there.

Speaker 1:

OK, so basically, what was the conclusion is a big word, but how good were the models and how much could we improve? Like, were they useful in the flood piece? And, of course, feel free, whatever who wants to take the questions.

Speaker 3:

So the original brief was to, as Lenka was saying, to assess these models to see what we could actually do with them and the extent of their capacities to reflect the reality on the ground, because we do know interventions in the upper catchment influence the outcomes in the lower catchment. Obviously, it's taught to every natural science student, but part of the challenge that was given to us that we asked Lenka to help us look at was how can you actually measure and evaluate and attribute, like avoided flooding, units of avoided flooding or units of avoided drought, same thing to particular places. So we take the management to the side and we go. Can the models from looking from the sky, from the eyes in the sky and the process model underneath? Are they sensitive enough to detect where we know there are changes? So, was it successful? Well, the investigation was very successful, but we found a really mixed picture, really. So, lenka, do you want to go over it or you want me to? Yeah, I, I, I, I, I. We found a very mixed picture.

Speaker 2:

Yeah, so there are good things about it. I think invest is a good start at modularity, so the tools that it uses are interrelated, often require similar inputs. There's multiple scales that they try to build models on, and well, it's a fairly simple fizzing behind it, so it's not computationally very demanding. So that's the good sides of it. But in terms of the outputs, I feel there's a path.

Speaker 1:

Yeah, but we're missing the nuances, so we're missing the little signatures we actually want to model, and in that sense, For example, what could be a signature, or like a little what is too small now that doesn't get caught in the model.

Speaker 2:

For example, if you want to involve vegetation, you are lacking.

Speaker 1:

A small piece of a catchment. It's very tiny, a very small variable.

Speaker 2:

A little forest. Let's say in a catchment, it will be seen as a value, as a single static value in a lookup table, and we want to make that a temporally dynamic signal that we know that we can measure.

Speaker 1:

Okay, you have to explain what that means, meaning that a forest is not a forest. Am I hearing it right? It really depends what kind of forest, in what stage, in what type.

Speaker 2:

Type, or even we can play with that.

Speaker 1:

We can play with? What type of a forest. So it's basically now a forest or it's not a forest, like the piece of land. You have to select yes or no.

Speaker 3:

Is it a forest? Is it a grassland? Is it a? Yes, that's it, and you're saying I would like to go deeper.

Speaker 3:

Sorry. So we need it to be able to pick up the nuances that, if it is a grassland and it's still a grassland, we need it to be able to reflect the condition of that grassland, Because you could have a degraded grassland without much cover and the behavior of the water is going to be quite different as compared to having a thick sword with a full coverage of grass. And so that nuance, that's the signals that we're looking for to bring into these very simple models, To put a bit more sensitivity to the actual specific place and how it is performing ecologically.

Speaker 1:

That sounds extremely difficult, because it's almost the same. I had to think about nutrient density, like we're saying at least tomatoes not the same as that.

Speaker 1:

Tomato, in the sense of this forest, is not the same as that. Like a grassland could be 10 different types and have massive different influences on the water. So how is it like? Okay, let's take one question Is it possible to add that kind of sensitivity now? Or is there a lot more research needed to then say, okay, a healthy grassland does more or less this. We know that already, or is that still unknown? We just know that grassland can be very different.

Speaker 3:

I think sorry, there's two ways you can approach that question. There's one where you do a lot of field studies to try and make your lookup table better right, and then you go out and you study all of the regenerative approaches and all of the conventional and you take 20 odd years generating a better lookup table right. You can do that way and that's kind of enough which we don't have.

Speaker 1:

20 years yeah, no we don't.

Speaker 3:

So we're looking at finding the biophysical signals in the remote sensing, so let's say the temperature or the moisture or the greenness or these kind of generic signals you can get everywhere and then to bring them into the process model to see how it affects the outcomes, right, so it's kind of experimenting while doing, and then you make everything an experiment essentially. Then you're comparing okay, we know management A and B is happening over there and management C and D is there. What do we see coming out of the model? That's different? Is this sensible? Is it defensible? Do we need to go and validate these results? That kind of structure? But, lenka, could you add?

Speaker 1:

And, by the way, we just and we go to Lenka. I didn't welcome you back on the show at all. So welcome back each. It's fine, you do it later. I did it, but then we went straight to the question. Anyway, lenka, so how so? The first option we don't have time for that. The second option is an ongoing, is a constant experiment. So how does that plan out? Or how does that go? Ideally, to build the model almost while you're flying the plane, but it seems like we need that.

Speaker 2:

Yeah, we need it. I think it's definitely possible. So, for example, one of the hydrological models uses the reference of a transpiration and crop coefficients. Now, I know these are maybe two technical terms or two specific, but basically what crop coefficient do is that they say, depending on your surface cover, land cover, you will have this amount of evaporation or that will account for reduction in evaporation. To this extent it's basically like a percentage. It reduces your operation depending on whether you have very wet grassland or forest or very dry grassland. So we have that already in the model.

Speaker 2:

But we don't have the kind of the change over the season even though we use 12 different values for these crop coefficients to mimic every month. But in one month we can have a drought and not spotted right and we want to do that. So there are papers published already on matching NDVI and green, as that we see from satellites with these crop coefficients. So we can translate that into them and link it to physics, to this evapotranspiration reference evapotranspiration model, and I think you can basically do this for every part of the models and invest. Hi, if somebody wants to invest in this, please let me know. But I think it's something we can get closer to doing. I don't know if I can give another example.

Speaker 1:

Yeah, absolutely Please.

Speaker 2:

I'm also scared about the validation of these outputs. That's something we need to work on, because they're made to quantify ecosystem services of a landscape, but there's not enough studies or we are not valuating nature capital at the moment. We don't have global data sets telling us yeah, this is the amount of sediments retained in this area and this cost is a amount of dollars per step. So if we get an output that says that this is a three million worth of a landscape, what do you compare it to? How do you validate that? And models always work with this. With physics, we can do it. If you have a quantified runoff on a landscape, you can compare it. We tested it for the US, and US is very abundant in data, so that was really nice to work with. And then the main question is how do you validate this, or how do you work with these models in regions that are unguarded basis?

Speaker 2:

So, where we don't have this amount of observations and measuring stations and can then set lights, completely replace that.

Speaker 1:

So that's one question, and the second is how does that translate into money amounts, how does that translate into? Because of course, the x tons or x avoided sediment or sediment of avoided flood is one thing, but translating that into cash is a whole different thing. And I think we sort of know that nature is undervalued, we just don't know how much. And the big discussion over the next years is going to be how to do that in a way that makes sense, and that's going to be a lot of trial and error. So, yeah, you want to say something.

Speaker 3:

Yeah, that's okay. So it's really nice to be back and to be talking to you again. I think, for the valuation point of view, what we are really focusing on is quantification of the biophysical amount. Right so tons of sediment avoided, in particular time, or tons sorry cubic meters of, because?

Speaker 1:

then you can compare to other landscapes Potential flooding.

Speaker 3:

Potential flooding? Yes, potentially. Yeah, cubic meters of potential flooding that have been avoided, let's say right, these are. You know, we have enough experts that we can look at the numbers to go. Are they in the realm of sensible? How do they compare to other landscapes? Is the output of the models? Are they defensible?

Speaker 3:

The validation step is an absolutely important one, but it will be a forever ongoing scientific process of continuously validating and improving the models and getting them better. So we expect that to be an ongoing process and not well, we can't do anything till they're validated. Because it's the same type of attitude as per past science, where you know you create a lookup table and you go okay, now I'm done for the next 20 years. It's like, no, this is a continuous process now. But back to the monetary valuation question.

Speaker 3:

So we look specifically on the biophysical quantification, because what we think is needed is that's the unit of service or value or substance, right, and then that needs to be translated to get it to money. You need to be able to translate it locally, in the context of where you are. So an example will be let's say you have a town at the bottom of the catchment and it has already flooding issues, right, and the value of that land, of urban land, is very high as compared to rural land very low. And because our what's called a return interval, our flood, how often you are likely to see a flood of a particular size these are shifting now and a lot, which is a bit concerning. But anyway, because they're shifting so much, all of the previous engineering calculations that were used to protect these towns from flooding, etc. Like canal bypasses and you know, let's straighten this bit of channel and let's try and divert the flood, these are no longer the design parameters that were used to create them are no longer valid, right?

Speaker 3:

So all those parameters, yeah, so we're seeing places where the once in a hundred or even once in many hundred year floods are now dropping down below once in ten. There are some places in Australia that are now uninsurable because several years in a row there were these just absolutely record-breaking floods, and that doesn't mean that that flood stays at the one in a hundred. That means that flood comes down and is like oh right, well, now you might see it one in ten or one in five, right? So this one in a number of years is a statistical measure and it shifts. So that's what's happening with climate change, especially now. Well, not just climate change is two things Climate change for the extra energy in the system going through into the hydrological system, which is a good thing rather than a bad thing, and then also actually widespread degradation and reduction in the type of holistic management that used to be occurring across landscapes, both from animals and from indigenous peoples. Yeah, so, but I lost my point Perfect bridge Shit.

Speaker 1:

So that's a good bridge to indigenous land management and water management, lenka, because that look, how do we give that a place or how do we look at that? And what can science and models help us to? Because we've been managing water systems for a long, long, long time and not always with these destructive outcomes as we have now. So what can we learn from the past and I'm saying the longer past, not just the past 20, 40, few hundred years? What can we, how far can we look back and what can we? What can we learn?

Speaker 2:

Yeah, I think it's really nice that you say not only the last 20, 30 years, because the reasons the last 12,000.

Speaker 1:

Yeah, why am I doing this? Seeing the plow.

Speaker 2:

It's because we are now pushed into thinking in the coming decades or in the past decades and we really focus on climate change. That's been, that's hot now you know, but we can look at trends in natural processes that have been going on for more than decades, right, because nature is very old and we can see this really well in sediment tracing. So what we try to do is understand this management. Okay, I should rephrase this. Let me see.

Speaker 3:

I should start with dryness. I understanding and am saying in this form somewhere dryness.

Speaker 2:

I don't know when I should start for where the right effect is. We're not doing this for wetlands, for wet climates, right? That's what maybe did not emphasize enough. Aerid landscapes are the ones that are really hard to model. They're the ones that have these hydrographs that we don't know how to respond to, that they're changing with this one and 10, one and 100. So that's where we need to focus and luckily there's knowledge that has been there for thousands of years that we trace with multiple signals. But what we will be working on is trying to distinguish sediment pathways, so whether they have been transported by humans or by a stream, and this is something that we can read from luminescence of sediments, and we can test it in regions where we know how old the geomorphology is. So, for example, in the Netherlands, this is maybe easier because we know when the dunes formed on the coast, we can get exact dates. And then this methodology is kind of novel and we're trying to expand it to these regions where we need the data and the to aerid landscapes, right?

Speaker 1:

I don't know if I should explain the luminescence Absolutely, because what I'm hearing, but correct me if I'm wrong is that this makes, of course, much more sense in aerid landscapes which we sort of know. There used to be less aerid or there used to be a lot of people living there. And the question now is, because a lot of the world is actually very aerid and getting more aerid is, you can sort of trace the water management systems either natural this is the wrong way of saying it but natural way or human managed. Either humans brought the sediment or a floodplain, or maybe the floodplain was partly managed by humans. But because we can look at the sediments, we can sort of follow where they were to used to be and how they were to used to shape that landscape, because we can also know how the landscape naturally was formed or how were big events in that landscape management or in that landscape forming, and the sediments give us a clue where and how water has been moving, even though there's no water now anymore, there's no river.

Speaker 2:

Exactly, you're explaining it correctly, so we can look at the river and say how was the shape?

Speaker 1:

But we can still see the shape and still see where the sediments were and that human element in that, how? And then actually let's see how can you? What did you mention about sediments before that we should understand? And probably can you see that from the sky as well. Like already, you have to go and dig and send it to the lab.

Speaker 2:

You have to go and dig and send it to the lab. Yeah, but the signal comes from the cosmos, so it's called.

Speaker 1:

Okay, it tells you where to dig, but this is luminescence though. Illuminescence. What does it mean?

Speaker 3:

Optically stimulated luminescence. So this is the last time you have court screens. And when they're in sunlight they absorb something Photons, I guess, I don't know exactly.

Speaker 1:

And, as a last-day, when they've been exposed to sun, you can know that Cosmic rays there you go.

Speaker 3:

We sound like hippies, listen to us. They absorb cosmic rays and then they get buried, and then, if you excavate them and don't expose them to light again, then you can actually measure the time since they were removed from sunlight. Is that right, linka?

Speaker 2:

I'm going back a long time, yeah. Yeah, that was good explanation. So when they were last deposited in the landscape, yeah, and covered up basically when they were covered up. When they were covered up, yeah.

Speaker 3:

So it gives a very good way to date things that can go a lot further back than usually then traditional measurement of carbon dating, I think. So I'm like I'm going back to introductory soil science now, which is a long time for me.

Speaker 2:

Yeah, with carbon, you have to look for places where there is carbon, where there is organic material preserved, and for arid landscapes, we use quartz, we use sand and silt, which is the kind of new thing in luminescence and yeah. So you have to use different signatures for different landscapes and it works well.

Speaker 1:

And so what can they tell us? The past piece Like how far can you go back? Or what does it tell us about past, let's say, water management systems, either with humans playing a huge role in it or not. Like what does it tell us, and how far back can we go?

Speaker 2:

It can go back to 500,000 years and of course the further back in time you go you have a higher error margin. So it's about 5% to 10% error margin. But if you are talking about landscapes that have been formed in the last thousands of years, then you have maybe hundreds of years max that you're kind of shifting. But that's enough, for if you have the context of how the landscape has been formed, you can place these ages on sediments, on sediments, quite accurately. And that's why this technique is useful, because it's actually quite accurate and goes way back in time, because the sediments accumulate. It's based on radioactivity of elements in the crystal structure of sediments, so it's something that goes really further away from all the organic material.

Speaker 3:

Let's say you sound like such an arid slinker. So Lenker and I were born on the same day. How many years apart? 20 years apart.

Speaker 2:

That doesn't matter, that doesn't matter. Totally matter they studied the sediments.

Speaker 1:

But bringing it back to the indigenous land management practices. What have we seen there? Like? What is we I'm using the general we as humanity now like what? These methods? What does it tell us about indigenous water management or land management, which is the same thing practices over time.

Speaker 2:

They did a great job.

Speaker 1:

in short, Somehow we are able. We are able just for a couple of years.

Speaker 2:

Somehow they had agriculture in the desert and we want to know why did this work?

Speaker 1:

Maybe it wasn't the desert.

Speaker 2:

Yeah, agriculture in the desert. They routed sediments in these very narrow channels, further away from this main stream.

Speaker 2:

Let's say and that way they expanded the flood plains and made the land more fertile, far further away from the stream itself, and we're putting age on all these channels that they used to route the sediments and water. Essentially, and we also want to link it to how they experienced big floods and big droughts, because not only did they have the fertile lands in the desert that's basically only sand and very little water, it's halving there but they also had a kind of a mitigation strategy when these events would occur. So they were actually not seeing it as an enemy, as a catastrophe. They saw these huge flood events that would bring in sediments and water as a period of abundance, and then they would completely change their way of thinking. In the coming years we have floods, but we need to preserve this for the next. Let's say, I think at the time, 10 years of dry climates, and that's what we're not doing now.

Speaker 2:

A good harvest coming, yeah, now we're going to all places where there are fires and then we're just putting water on it or whatever. We're just trying to put the fires down Instead of like okay, maybe fires also want to restore the ecosystem, you know, and they give us an opportunity.

Speaker 1:

Learn that from production forests Monaco.

Speaker 2:

Yeah, exactly For rejuvenation of landscapes. And of course now they're also catastrophic and desertifying and it takes time. But maybe we just have to give that time to nature to restore itself and trust it.

Speaker 1:

And be very active in it, Because I mean, of course, it's interesting to hear like they thought as abundance I don't know if we can say that, but they definitely acted like it and catch as much as you can. And is there a way to then also look at how these agriculture systems, the land management systems, have, of course, shaped the water systems, because you basically shape the river in the way you want? Is there any data, then, or any way to look at the weather system as well, how this at large scale in a water catchment has influenced weather, or is that too difficult and too long ago?

Speaker 2:

Yeah, that's also possible. We use, I think in that sense, isotopes to see kind of the frequency of, or the distance to which the, let's say, salty water minerals have been transported into the landscape, and then you can use that to see when the floods or when the ocean came closer to the land, let's say In this region this is what I'm talking about, of course, south America, but in general, this is what scientists use these days.

Speaker 1:

So you can go back in and try it. They weren't aware of it, they were growing. I'm not saying they were influencing El Nino maybe to a certain extent actually, or influencing the weather patterns as agriculture expanded. You can actually see and tell okay, rain patterns changed or certain weather events occurred, more or less.

Speaker 2:

Yeah, so this is like which is what we're talking about now. So this is not new at all.

Speaker 3:

Sorry, I'm pardoned. The design process. It looks like to be quite a different style of thinking than, I guess, current modern thinking about how to deal with water and agriculture. I mean, currently water is get it away. Floods are bad, they destroy things. It's not seen as an abundance and an opportunity, it's seen as an enemy and something to be gotten away as quickly as possible. And this has caused other problems such as dehydration of the landscape and the degradation of the fluvial geomorphological structure of the catchment, which is essentially the shape of the catchment in response to the water that comes, gives you a lot of information about the water that's coming. And if you're not touching a catchment and it's just following natural processes, let's say you will get this structure of the catchment will be reflecting the water and it will actually form. You know it will move towards a state where it is removing as much energy from that water as possible. Right, so this idea Slow it down.

Speaker 1:

Yes, slow and spread.

Speaker 3:

So if you go to like, if you go to much older landscapes that are still intact, you can see these structures Are there still older landscapes that are intact and natural.

Speaker 1:

Yeah, there are good examples there's.

Speaker 3:

We've done a few tours on Google Earth looking at older places that still have these kind of intact structures. So this is like in Australia. We call them chain of pond systems. These are like big, broad valleys that have very flat bottom and you will have distinct ponds that are really quite deep and have water in them, even in the dry season, right.

Speaker 3:

And then when it does rain because Australia has a very yeah, flood and drought, let's say when it does rain the entire valley basin fills up, like the entire bottom section of the valley fills, and the whole flood will move across the top and at the same time, it's recharging all of the surface groundwater underneath, and so this is like a buffering mechanism, right, you get more water in the ground, it buffers the damage of the flood and it removes as much energy as is physically possible from the water, right. So the natural systems tend towards towards this, this kind of I don't even know the right words for it. I mean, I used to tell my students it's like it's you're lovingly helping your enemy to the ground. It's from like a keto or a kung fu or something. But the point is is that you're no longer like using brute force, we're just going you must go.

Speaker 1:

Now. You're removing the energy, because that's what's doing the damage. Yes, slow down.

Speaker 3:

Yes, the concentration of the energy does damage, but the dissipation of the energy, so maximizing the dissipation this does incredible good. This is how nature works and I think it's. I think this is the line that many indigenous groups see it, because if you watch a landscape long enough, you can see it Right. You take away these preconceived notions that we must, you know, treat nature like a machine. Take this away. Observe you can see this process occurring Right. Take from the smallest little ripples in sand and how they repeat their structure and drop the larger sediments and then the smaller, to the way that in like European countries that are younger and wetter, that there are steps. There's like a pool and a little riffle of stones, and then another pool and then a little riffle of stones. This is a physical manifestation in response to the energy coming into the system that's translated through the water. I'm worried. I sound like a hippie.

Speaker 2:

No, no, no, I'm very curious how it connects to sorry Lenka, go ahead it doesn't then matter whether you have a feedback towards the weather right, because you just wait and observe and use what you have in yeah, it's inevitable. Exactly.

Speaker 1:

Yeah. So, what does it should teachers show us about restoration and about the active part of restoring? No, actually that's the question. I think a place wants to be somewhere.

Speaker 3:

A place wants to be something. Is he saying that we use often, and I think in especially Western engineering and science, we've especially the historical stuff We've assumed the place. Yeah, the place has no agency. Essentially, there's nothing else, it's just nature is the enemy. Let's dig a channel.

Speaker 3:

It's the most efficient approach and our engineering is very powerful, but it's not in most cases, it's not observing the design, I guess, the physical design of how nature flows and functions.

Speaker 3:

And it doesn't mean it can't, it absolutely could, and there are good examples of it, like water sensitive urban design is a perfectly good example. You're using planted gardens that are sandy gardens, with plants in them, to clean your stormwater. Because, it turns out, putting plants in a sand filter causes that sand filter to actually be a soil and clean the water for longer, whereas if you just put it into straight sand, it clogs in I don't know six, 12 months you have to change it again. So that's the kind of, I guess, the shift in the thinking. We don't have to reinvent engineering. We have excellent tools, but we need to examine closely our relationship with natural systems. Are we really in command and control? Because this is, yeah, this is not looking like it's the case. So that's why we're saying like how to kind of be friends with water again, like I don't know, it seems like trying to fight the wind.

Speaker 2:

I would focus on this again. It's exactly. We've been doing this for a while. It's just. It seems like we've forgotten, but I think the system has become more complex. For sure, but I think there's still there's signals from nature, right, that we have to listen to that goes beyond us. Like I remember at the start of the pandemic Isha and I just had this conversation Ah, you know, this is just modern nature telling us to slow down and like freaking out and trying to explain that maybe we should just yeah, and I didn't see it at the time.

Speaker 2:

Okay, it was also really hard and I had online education for two years, but I saw it as a really the kind of the last chance that the nation was giving us to rethink, to stop for a second. It gave us time but we didn't use it as well and yeah.

Speaker 1:

We did prove we started baking. Yeah, we did it. While baking is good, we proved we could work together.

Speaker 3:

Quickly. Have you been approached or?

Speaker 1:

Like it's been an interesting test and then it got derailed very quickly. But if for a week or two or three we were all together in it and which was an interesting feeling. But have you been working with, like, the few indigenous peoples that have been still managing landscapes of way too few? But if you look at the biodiversity they manage it's immense. Is there that connection, let's say, between just going to quote that, hippies with satellites and indigenous tribes? Are you, is that connection we made, or how do you approach that? And are you mostly looking at indigenous knowledge from way back?

Speaker 2:

That was a question for me, right, or me. So we are mainly looking in the past, but I would say what's maybe Open Geo Hub is trying to do is creates data before we lose it, before we forget about it. It's essentially knowledge that we need to be able to look back into in the coming decades. We need to trace all sorts of signatures, have them with us on this journey to try to restore our landscapes right. We cannot afford to miss something out, especially if we have people that can do it in a very fast, efficient, reproducible way and that share it on the go.

Speaker 2:

I think the fact that we are opening knowledge, that data is becoming accessible to people, I mean the pity is that what we are tracing with sediments, what we are dating, is we put into a couple of scientific papers and people might not see it, as we have to put way more effort into delivering the message across. And what we do is well, my supervisors. They actually collaborate with the local museum and that's where you can interact with today's community. It probably also has some legacy of the indigenous knowledge, but I don't think it's there. I'm talking now about Peru, but I think in general, we are losing a bit of this indigenous knowledge today, and then it doesn't have to be also indigenous. I think it's in us, like connecting with nature, something we have to do or reconnect. It's not something we can. We have to kind of learn from the past. I think it's just we have to find it with ourselves again.

Speaker 1:

So how do we connect it, then, to current land practices or current, let's say, land stewards that are managing watersheds, or are, let's say, somebody's listening to this and say I'm working in southern Spain or I'm working in wherever. What can the eyes of the sky tell us or help us? Because we're trying to read the landscape, but we just feel like we miss a big chunk, or we just don't know what we don't know.

Speaker 2:

I think it's happening I think there's a lot of transdisciplinary work now. For example, in Spain, people have been fighting fires and now they have this collaboration with the North, where they use their techniques of their management style of northern European countries and they connected with the fire knowledge and they create collaboration. So people are put together to reinvent the view. We're pushed to work together. That's what's happening. That's how we can connect with the decision makers, that they see that their engineering works are not the only solution that they need to have across the city. We're all into that. And also things like citizen science Make people aware that they live in a catchment. They don't live in a city. They're going to be flooded. There's a certain digital elevation model underneath their feet and they need to watch where they're going to buy a house or where they're going to plant a tree. We are also from the science part. We're watching this, but maybe each do also have a take on this.

Speaker 1:

Maybe floods is the first entry point. Is that because it's so in our face?

Speaker 3:

It is, but it's just going to be more. I would look, then again to the Peruvian example that Lenka is going to be studying, that it was seen as a time of abundance and plenty, because if we go into this period, looking at these big events that we know are coming, these two things we have the widespread degradation of the landscape, and then we also have the additional heating put into the atmosphere. That energy has to go somewhere and it's going to go in water A big chunk of it, thank goodness, because that's going to buffer the extremes. Then our choice then is well, we could consider flooding our enemy, and then climate change is our enemy and land degradation.

Speaker 1:

Everything is our enemy or. Flooding is like an energy outburst of the system.

Speaker 3:

Yes, of course I'm just translating for the listeners. I know every single one of you understood this, but it's just me. That is arriving to this point. We're getting into the jug again, sorry, no, no.

Speaker 1:

I think it was following what I just wanted to highlight. The point Floods are If you catch the flood, yes, and you spread it out into the structure of the landscape.

Speaker 3:

You have an opportunity to take that work, that energy, and turn it into a biophysical structure. If I am faced with a piece of landscape that is degraded and let's say it's a bit arid and it's moving into this flood, fire, drought model, and then I go okay, what this system needs is it needs to have a physical structure that is able to take as much energy out of that flood and infiltrate as much water as possible, which will then grow more vegetation, which will drop the temperature further, because you've got this circulation locally of water. The face change takes a huge amount of energy out of the atmosphere, out of the air.

Speaker 1:

Sorry, then instead of letting it burn down. Sorry, one second, that cooling piece, now go ahead. And then I want to go to the cooling piece. You say stuff like of course it's like that I think we're dropping some. Oh okay, I'm sorry.

Speaker 3:

Now more so that, and then you infiltrate more water and you grow more plants absolutely, but where are the animals? Because if you're not removing that biomass, if you're not doing something with it, if you're not buffering the temperature on the ground, if you are not either using fire management in the cool season or really just harvesting that biomass off, then of course you're going to get fire. It's inevitable, I guess. So it's kind of like we need to choose where the energy goes, and we could choose to put it into a restored and abundant ecosystem. The challenges we are facing actually contain huge opportunity, but we have to be able to see it like that Sorry.

Speaker 2:

But we're very close to seeing it. We see it from the, the satellites we follow. What's happening? What?

Speaker 1:

makes you say that we're close. Why we are close? Well, I'm not going to say we have the solution to how soil retains water and how it cools.

Speaker 2:

I think it's still. I would like to believe that there's some mystery in it, you know, because I think it's always mystery. Yeah, but it's a. It's a powerful tool that nature has.

Speaker 2:

Yeah, so, for example, now the big buzz in hydrology is soil physics and how basically seeing these structures soil structures change in time and how, for example, microbes and influence it, or how these cores in soil basically divert water, or how they determine where the water will go, and I think that's something that we're also seeing from space. So there's a couple of data sets that are also telling us something about soil moisture, so we need to see these signatures.

Speaker 3:

But this is something that you also have to measure in the field, but it's there it's coming closer, yeah, so we can see it as scientists and part of what we're trying to do, because we have to take these quite large intellectual bridges and go okay, I see that there and I see that over there, and these two things are related.

Speaker 3:

Based on all this prior knowledge and learning that we have, we need to take the expertise and abstract it away and just make it very visible and clear, with a few metrics that are very responsive to management, what is going on. That's kind of the ultimate goal, because we need to give a kind of a compass right Kind of in this direction, go that way and then watch these variables there to test how your interventions are working, essentially specifically for your place. That's ultimately where we're going to, and I think if someone is going, okay, well, you'll get there one day. But what do I do now? I think that if you've been doing interventions anytime, if you started anytime after about 2000, maybe 97, if you want to be strict, if you started anytime after that, those signals are already in the record, right?

Speaker 1:

So then it's about us catching up with the record, so let's say the last 25 years. We can easily go back.

Speaker 3:

It's already in there, okay, so it's been seen. But because it's such a massive amount of data and we are approaching, you know, trying to find those particular signals that give that nuance, that give that response, and actually in the fundamental physics we find most of them. Actually, because we're looking for those, this takes time and also computing us to catch up, methods have to catch up. So if it's happened post 2000, it's in the record already. Either us or others will find it, hopefully sooner rather than later. How that is then monetized, I think is a local question, because if you're doing flood mitigation above a town that has no weather choices anymore because the floods are getting bigger, I can't imagine that.

Speaker 1:

And no insurance.

Speaker 3:

Yeah, that would be valuable to insurance or local government or just the people living there. Yeah, you know that's when insurance and banks and regional government local government gets involved. But if you're doing that kind of work and there's no town downstream, yeah, okay, your primary value will probably be actually in the increased productivity and carrying capacity of your landscape. Right, if you are a grazier free instance, because most of these systems that we're talking about we're looking at grasslands, or more grasslands to more arid systems. I forgot your other question, coon. I'm sorry.

Speaker 1:

No, no, I'm like the cooling you like. Obviously it's cooling which sort of obvious to many, but not to most people. Yet let's say so. First of all, why is that obvious? A second how much of that cooling effect can you see already from from the sky? Like what, what? What makes you say obvious it's it's cooling down the surface and a lot of the heat actually gets lost, like it's cooling not only locally, but actually it's generally cooling.

Speaker 3:

Okay. So why is that obvious? I think from my own personal point of view, I grew up in the middle of nowhere, very rural, so my study was essentially in the tropics, in a monsoonal, a dry, monsoonal environment. So every year there would be this huge build up to the monsoon coming down and then you go through all these like series of storms every afternoon. So you'd really feel very fundamentally the heat in the morning and then building in the humidity to the point and even smell it, the point where the storm is going to turn and when the rain's coming right, so you could smell it, the color of the light, the like there's, all these things you can observe as a human in the environment.

Speaker 3:

And I think for me the reason I can say obviously is because I saw that a lot when I was kid. I mean, there's not a lot to do other than run around in nature, right? So you end up studying what you are part of and then when you go, when I went through a scientific study afterwards, I would be just finding the right words to explain what I already knew. So I guess that's why I'm saying obviously, because it's to me it's like it's fundamental physics. But then that fundamental physics for me personally is embedded in my experience of the world, that I felt it, I've lived it. This change in the temperature, the smell, the color, the environment around you is very palpable. Yeah, I don't know if that's a correct answer or it's sufficient, but no, absolutely.

Speaker 1:

And then now you have the words and the images, let's say from the data, to show that at a much larger scale than, of course, only the few square meters around you where you're walking. Do you think it's the biggest under overlooked piece in the whole climate discussion?

Speaker 2:

I would say yes. I see Lekka saying yes.

Speaker 1:

Well it's just thinking you go.

Speaker 2:

I think the soil moisture can tell you when the drought will happen, six months before the droughts. So the water does cool the system.

Speaker 2:

yes, and if you didn't have a lot of precipitation with winter, expect the drought in the summer. Yes, this is not scientifically. This is not a scientific sentence. It's a kind of healthy, conscious sentence, but it's something that's overlooked in decision-making. That's it so because you can follow the trends in the soil moisture and say, well, we are going to have a drought in June, so what do we do? Or how do we get the water in the soils to prevent fires? It's not fairly simple. It can also just affect that your soils, and dry doesn't mean that there will be fires.

Speaker 1:

But it's very likely, at least if a fire starts.

Speaker 2:

Yeah it's one of the signatures you should follow early, and that's the same with discharge and floods. You can see that coming earlier as well if you look at the soil moisture.

Speaker 3:

So these kind of signals that you would if you were in a place experiencing it, let's say without the protection of the airco and you know these kind of cocoons we've built for ourselves. If you were really experiencing and living it, you would gather and learn this knowledge quite quickly again and as you go through multiple generations it would build up again. But now what we're actually trying to do is look for these things that we know are there in the remote sensing signals to put them into the process models so that we're able to expose these kind of relationships to people without having to throw them out in the field for a couple of generations to readjust to the natural environment. Because apparently you know, let it be good in general.

Speaker 1:

Yeah, how do you speed up the signaling and thus hopefully change land management practices?

Speaker 3:

I think from our side just to try and make it as simple and as available. I mean, we're, we're each time we build something, we expose it, we look for feedback, we, and we get feedback from landholders who can explain patents in maps that we're like, oh okay, like when you have someone who has place based knowledge, right. So indigenous knowledge is essentially a place based knowledge. It's built up over a long time. It is yeah, it's a cultural body of knowledge and it's very, actually quite, thorough and quite powerful. It's essentially a type of it's, it's a science. It's indigenous science as well, not to not to speak down on any of the cultural aspects, but to look at it from a scientific point of view.

Speaker 3:

So that kind of knowledge takes a long time to build and we know many cultures still have it and we know many cultures had it and we're just going okay, can we just try to get the machines to see what we know is there? Because it seems like very modern culture likes to believe the machine and if I just slap AI on the front of it, they may just believe whatever comes out. Actually, you should cut that bit. You shouldn't put it there. Don't tell them that.

Speaker 1:

It's true, the hype cycle. The hype cycle at the moment is crazy. No, but we use machine learning. Anyway, we've been using it for like more than a decade.

Speaker 3:

It's a fancy term.

Speaker 1:

But to ask a few questions which we have to you already, ish, kind of say, back in the day, but a year and a half ago. But to Lenka, what would be your main message? To quote, unquote the financial world or the entrepreneurial world that wants to translate this into action and that maybe is investing in farmland, maybe is developing farms, maybe is developing food companies around regeneration. What would be your main message to them? If they remember one thing from this interview, what would that be?

Speaker 2:

That's a difficult question. I'm really not a good financial consultant. I would say we're not giving investment advice, obviously.

Speaker 1:

That's why I'm exactly asking that question, because I want to know from people in the field that are doing things not related to putting money to work what they would do. What would they tell people to be that bridge, basically?

Speaker 2:

I would say invest in open access knowledge. Just allow people to build data on top of data and make it available to everyone, because we're not only just we're not storing data, we're getting to making data that's readily usable. We create products that people can immediately put into models or that immediately tells a story about whether the landscape had a drought, a flood, whatever. At this point, I will just use one term and it will mean both. I really believe in this.

Speaker 2:

I think this has to change, also in academia and education. We need to make people good at open source coding, data usage, because it's pushed upon us. We need to be good data analysts and we need to know how to program, but how we share. What we gain from this process is not what we are taught Putting all the codes, to give a particular example, putting all our codes and documentation online so that people can produce the same product if they just follow the steps that we do. If you support these sort of networks, I think that really will get us closer to proving well, to making management changes.

Speaker 1:

And flipping the conversation. What would you do if I know it sounds like an insane amount of money and it is, but it is what some people are tasked to put to work. What would you do if you had a billion euros to invest? In this case, it has to come back at some point with some kind of return, which could be very low, it could even be zero, actually, and it could be 50 years. But it's not philanthropy. It has to be put to work in a way that could come back in some shape or form. But if you had a billion euros or dollars whatever currency you prefer what would you focus on? I'm not looking for dollar amounts, I'm just looking. What would you, what would be your priority list, look like if you had basically unlimited resources?

Speaker 2:

Stop climate change, just that.

Speaker 1:

And how.

Speaker 2:

I think if people could just continue doing what they're doing, but just faster in some way, that would be really good, and I think I would invest in just collaboration networks. I'm still I'm really. I see, you know, as somebody who started earth science, that people knows that the academia wants to split us into hydrologists, meteorologists, and essentially we're all doing the same thing, right, we're analyzing these nature signals. So we could just think together and not forget that we're in the same field, that we came from the same point. That will be amazing. That will be my dream, where we have actually working collaboration across fields towards a very sustainable earth.

Speaker 2:

I think, yeah, if we could just find out a common language and also not forget that our perceptions are changing, what we are doing, that we are not objective, people right that sometimes farmers and people outside science can also provide very valuable knowledge, so we could just go beyond all these worlds categories that we create and work together. That would be. That would be it. I don't know where to put that fund billing. I don't think in terms of money, I think in terms of values and humans.

Speaker 1:

But you still need the resources to do the work or to enable others. I think I see it more like a tool and a way of others to do more work. If you had that kind of just like water enables a landscape to do a lot of things, what would you make? What would you enable to grow more if you had this amount of money? Where would you focus?

Speaker 2:

Give it to talented people that are already kind of doing this.

Speaker 3:

So not going to say open geo hub but yeah, we're in a more.

Speaker 2:

I like to believe that there are more groups like that with a really with a clear vision, and I think you can find those people Forest watch. I don't know, I'm thinking you know.

Speaker 1:

We want names in the sense that like why would you focus, or what would be, is it on that observing and then translating into land management.

Speaker 1:

Because, we've also had people say I would buy a lot of degraded land I would preserve, I would focus on dishes, right, I would lobby for certain things, which, of course, is sort of an investment I would I mean, there are some people have a whole list and some people have I would focus everything on this landscape where we're working or everything on this food company we're building.

Speaker 1:

So the answers have been extremely wide, but I hear more like the enable, the people that are currently translating the null or translating with remote sensing, like what we already know, what we could know, into land management changes, like we know so much but it just doesn't land really well, or it's completely disconnected from the few farms, the few landslides that reach out. They, they are, but that's the 0.01%, maybe even less, and they could be equipped so much better with so much more knowledge and so much more comfort of what they're doing. Then we are now like this is we don't have this knowledge in our pocket when we're making management changes on our on our farms and the other 10,000 decisions that we need to make, and you should be able to get the knowledge in their pocket.

Speaker 1:

Yeah, absolutely. What did you say? Sorry, lange, sorry.

Speaker 2:

What did you say? I said you should put that knowledge in their pockets. Same as ish. Yeah, that's what they deserve.

Speaker 1:

And a billion would get you pretty far in some landscapes to do that.

Speaker 3:

Would we even need that? I do think we need. You could have some spare.

Speaker 2:

She's scared of large numbers.

Speaker 3:

Yeah, but no, I love large numbers. I just update this I don't think everything's as hard as everyone's making it out to be. I see that we have a real coordination communication problem between ourselves and the natural environment. Right, it's still mostly viewed as the enemy, which is not a very healthy way to approach your surroundings. I thought we will go to.

Speaker 1:

Mars, and then we just wait how our Earth is regenerating.

Speaker 3:

I think anyone who wants to go to Mars can go to Mars, because I mean, frankly, if you can't work out how to fix this place, I don't know how on Earth they think they're going to be able to grow something on a planet without an ecosystem.

Speaker 1:

It's just it's a logical for me. How on Earth it's a good sentence? Yeah, there you are.

Speaker 2:

How on Mars? How on Mars. They can do it quite well, I think. Just let them go to Mars if they don't want to stay on. Yeah, yeah.

Speaker 1:

It will take some energy out of the system.

Speaker 3:

Yeah, that's fine, they can go. Yeah, they can go. I think that it would be really nice to make our technology serve our culture instead of the technology drive or run over culture. Because, honestly, if I look at so, like Indigenous land management from Australia and let's say specifically, one place that I have in mind is called the Budge Bim, right, so this is in Victoria. It's the world's oldest aquaculture in the world. It's eel aquaculture and it's older than the pyramids and the site is enormous and this is clear active aquaculture growing, capturing wild eels coming in, creating new ponds, chiseling channels through solid rock.

Speaker 3:

It's serious engineering for the point of view of maximizing an abundance that comes, taking something that comes like a flood or a migration of eels and then making a lot of habitat for them so they can really grow very happily and then harvesting from that. So the reason I bring this up is because the dating numbers that I've read like it's hey, some of the traps are six and a half thousand years old, but the cultural stories, the creation stories about the landscape, are more than 30,000 years. So the oral tradition, the oral tradition, the oral story of the place, is more than 30,000 years. What have we got, you know, are you thinking about the Greeks or the Roman? Like, come on, like we really need to get technology serving culture. So that would be nice.

Speaker 3:

I would chuck all the money into that, because if we can't find each other, if we can't, like Lenka was saying, get the knowledge in our pocket, if we can't make it serve us, what's the point of it? And then we're just being consumed by it. And that's what worries me in all of this. We know a lot already, not just from our own culture, but from many cultures. How can we come together? How can we see the water as our friend again in the environment? How can we make practically? How can we make the most of what we're given rather than reject it and decide that we want something else? How can we accept and then turn I'm done, I'm ready.

Speaker 1:

I'm sorry, I wanted to ask a question, which is usually a nice final one. If you, you might be the same answer you gave to the investment question, but it could be a completely different one. If you had a magic wand and you could change one thing overnight, what would that be?

Speaker 2:

I would put people on bikes, I would make everybody ride bikes. So not to say and this, of course, will not be put on the podcast just destroy fossil fuel, but yeah, just make everybody really capable of riding bikes. And I think that was all our issues.

Speaker 1:

And then would make you read a landscape very differently, that's for sure. It would make you physically active in a very different way. Air quality becomes super important suddenly and coming from a country where bikes are sort of you cycle before you walk.

Speaker 2:

I come from Serbia, I come from Hilly place. No.

Speaker 1:

I come from the Netherlands. I was born on a bike, so I'm very much into this magic wand answer, so I'm all for it. I want to thank you both so much for a wide-ranging conversation with many interesting rabbit holes which we could explore in countless other hours, I think. But we wrap it up today to be conscious of your time and don't hold back of any hard data crunching, remote sensing, translating this into relevant action items for people on the ground. So thank you so much for the work you do. Thank you for coming back here Is and thank you for being on the podcast for the first time, lenka, and good luck with the PhD in Peru, thank you.

Speaker 2:

Thanks, girl.

Speaker 1:

Thank you so much for listening all the way to the end. For the show notes and links we discussed in this episode, check out our website Investing in RegenderWaggerCulturecom. Forward slash posts. If you like this episode, why not share it with a friend? Or give us a rating on Apple podcast? That really helps. Thanks again and see you next time.

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