Water Resources Podcast – Augusto Getirana
[00:00:22] Bridget Scanlon: I'm delighted to welcome Augusto Getirana to the podcast. Augusto is a Research Scientist at NASA's Goddard Space Flight Center in the Hydrological Sciences Lab. And today, Augusto would be speaking in his own capacity and not representing NASA in the podcast. Augusto's research involves a development improvement and application of state-of-the-art models and integration of remote sensing data.
And today I think we're going to focus on applications to global and regional flooding and the relatively new SWOT surface water and ocean topography satellite for surface water monitoring globally, and improvements in NASA models and integrating with satellite data. And lastly, because Augusto is from Brazil, we'll talk a little bit about the Amazon, his work in the Amazon and floods and droughts and the need for planning in Brazil. So thank you so much, Augusto, for joining me today.
[00:01:25] Augusto Getirana: Yeah, thanks for having me. It's a pleasure.
[00:01:27] Bridget Scanlon: So Augusto, maybe let's start with your recent work on global floods in 2025. I thought that was a very interesting analysis and compilation of the flooding in the world in the last, in 2025, and you used EM-Dat (Emergency Events database), I guess emergency events database to evaluate flood fatalities and economic losses in that year from flooding.
And I guess it wasn't really that high in 2025, 4,200 deaths related to flooding, which is still huge. And then an estimated $28 billion worth of damages. So maybe you can describe the analysis and the methodology you applied and the modeling analysis and the resolution of the analysis.
[00:02:16] Augusto Getirana: Yeah that's a good start. So just to give some background to listeners so we used a HyMAP map force with GLDAS runoff. So GLDAS is the popular Global Land Data Assimilation System and HyMAP map is the hydrological modeling. And that platform, which is a global hydrologic model developed at NASA Goddard Space Flight Center hydrological science lab. And that is including the land information system or LIS which the modeling framework also developed at NASA GSFC. Back to the floods in 2025. Based on this model outputs at five kilometer resolution we observed that there is no clear increase in extreme flood events in the past 22 years. Actually 2025 falls within the low tier, as you mentioned. In the number of rivers showing extreme flows when compared to the past two decades.
And when you overlap the population data with these extreme flow maps from the model, we get to a similar conclusion in terms of people exposed to extreme river flows. This means that the exposed population is also in the low tier compared to the past two decades. But also looking at the emergency events database, the EM-DAT dataset as you refer to we also find that the last year falls within the low tier in numbers of deaths and damage resulting from floods. So that is aligned with the model outputs and also looking at the annual time series of all these different variables. This means the model, the extreme flood events, observe that and damage. We don't see a particular trend. These findings go against our general assumption that flood frequency and intensity have been increasing, which could be a matter of a general perception resulting from an unlimited, instantaneous access to global information. But at the same time, EM-DAT. That the disaster dataset has some limiting criteria to enter, to define a disaster to entering that database, as the number of, that minimal number of deaths minimal number of people affected, and a call or a call for international assistance.
[00:04:31] Bridget Scanlon: That's interesting, we're mostly hearing that everything is getting worse and it's good. And I guess I was also looking at AON Insurance, reinsurance their catalog of climate extremes and very consistent with what you were finding.
And they mentioned, in the US hurricane landfalls were low. and then they also mentioned severe convective storms being a big thing in the US. But so can you talk a little bit more about the major floods that occurred in 2025 in the different regions?
[00:05:03] Augusto Getirana: Yeah. In 2025 we saw major floods across multiple regions each driven by different mechanisms, but with severe human consequences. As you mentioned, there were around 4,200 deaths last year, which is not a record. It's actually, as I said, it fell in the low tier. So first in parts of Asia mostly south and southeastern Asia floods killed over a thousand people, largely from prolonged monsoon rainfalls that overwhelmed rivers and the infrastructure. There was the flooding in central Texas, that was a different dynamic. In that case, intense overnight rainfall over steep terrain that triggered rapid flash flooding. And there was little warning time that also caused multiple deaths. And also, and a different one that was in south Brazil, heavy rainfalls hit soils that were already saturated after extreme flooding the previous year in 2024. That was an actual disaster. So that led to a repeated inundation. So basically what 2025 showed us is that floods aren't just about extreme rain. They're about timing, land conditions, topography and exposure, and climate influences the hazard.
But vulnerability determines the severity of that impact.
[00:06:25] Bridget Scanlon: Yeah. That's a really nice description. And oftentimes we're looking at flood risk and that includes hazard. The hazard from the flooding and then the exposure and the vulnerability. And so it, it's interesting to think about the different factors that drive these major floods.
And you mentioned monsoon, and then in central Texas, it was a holiday July 4th. A lot of people unfamiliar with the area and happened overnight and all of these different factors that contributed to almost 140 people dying in that flood. And then the importance of antecedent soil moisture conditions in Southern Brazil. When the soils are wet, there's no space for the water to go, and so then that increases your chances of flooding. So, very interesting. And Augusto, you have done some very interesting work also at a city scale in Rio de Janeiro, where you are from to evaluate flooding issues there and try to help the communities better manage floods.
Maybe you can describe that for us.
[00:07:31] Augusto Getirana: Yeah, that's a very exciting work. It's this unique partnership between NASA and the municipality. It's the only one that NASA has ever had. It's been around for 10 years. We just renewed for five more years last December, where the goal of this partnership to combine NASA assets with local knowledge and expertise to address urban hazards.
So basically, you're applying our assets to the urban/local scale and try to make it transferable. So it's kind of a guinea pig for our capabilities. So in the framework of this partnership, we have developed a flood monitoring system for operations so NASA has this global LIS system that was downscaled to the city of Rio. In the past years, we've been working on an urban flood monitoring system based on HyMAP, 200 meter spatial resolution with a post-processing downscaled to 10 meters. So this means that we can have flood maps at the building scale as a result. So that system is in the final step of operations, and once it's operational, the next step is hopefully extend to the system, to a one day forecast.
It's important to highlight here that such a partnership is only possible because of the strong engagement that both parts have. We had like monthly meetings for the past several years, constant email exchanges, workshops. They came here together. We've been there to train them how to use the NASA tools and also the local team is highly qualified, in our calls and in our interactions, we can't speak the same language when we're technical discussions.
[00:09:17] Bridget Scanlon: That's really wonderful. And, maybe you can just provide a little bit of background to the listeners. Rio, you've got very steep topography it's at the coast and then you've got steep topography, and so you've got orographic effects. And what about the storm drainage system?
Is it well developed or not? Or, and when, what part of the year do you see most of the flooding and, how can they better prepare to become more resilient to flooding?
[00:09:43] Augusto Getirana: Yeah, so Rio has been flooding. It's a historical problem. So basically every year, between November and April, that's the rainy season. The summer, also summer and rainy season. There when you have floods. and some of them were pretty major in 2019. There was a flood, there were two floods in February and April that killed a few people and it stopped the city. So I think it's the drainage system is not as maintained. I think there's like an aspect of maintenance of the drainage system and combined with the drainage system that's not prepared for those floods since it happens every year. So in terms of better preparedness, I think having a system like this one that you're developing is the first step.
Because you don't have any information about floods, until it happens. So if you, once you have a system like this that you can also forecastone - two days ahead, you can have, okay, now we know, now we have information. So the baseline is you need data. So without data, you can't plan anything.
So now with this work I hope that they will have a better structure, better information to make better decisions.
[00:10:59] Bridget Scanlon: It will improve their understanding of the system. And, it's marvelous Augusto, how your work ranges from global scale to urban scale. And that you can bridge those gaps and downscale your models and everything to to get to that more detailed level. That is really cool.
[00:11:17] Augusto Getirana: Yeah, it's
[00:11:20] Bridget Scanlon: Another aspect, that's fundamental to your work is incorporating satellite data into your modeling. So you really integrate satellite and modeling. And NASA launched the surface water and ocean topography satellite in December, 2022, I think. And that is really advances your ability to monitor surface water globally in comparison with what we have used traditionally, which is altimetry.
Would love to hear you describe, the advances that you get from the SWOT mission and how it compares with what we've had historically with altimetry.
[00:11:59] Augusto Getirana: Yes. What is been expected for the past, I would say 20 years. So it's a US French joint mission, as you said, was launched in December 22 and measures water surface elevations over both oceans and inland water. So it's the first satellite, that was conceived to measure inland waters because the previous altimeters, they targeted oceans. And then we found a way like hydrologists, we found a way to use that data over inland waters. So it has this wide swath totaling 120 kilometers resulting in this two dimensional mapping of water elevations so SWOT is fundamentally different from those traditional net zero altimeter which measure only along a narrow ground track. So, as a result, we have different products that, they can be using different applications.
So the first one is the Pixel Cloud, or Pix C, which is a point cloud of individual water mask pixels, which is also available in vectors. They're created versions of water surface elevations at 102 hundred 50 meters. And there's a window when you upscale.
There's a vector product for rivers at think kilometer resolution around think kilometers with 200 meter nodes. And that product gives you water surface elevation, river width, and slope over these reaches. And because you have this, all this data water surface elevation, river width, and a slope, this SWOT team called discharge algorithm working group or DAWG they've been working for the past 10, 15 years always to estimate discharge from SWOT. And they finally came with the first version last year. And after a few improvements in their workflows, now they can, they're reaching accuracies that match their expectations pre-launch. And we've been evaluating the accuracy of that discharge over South America and what we found is that it generally does better than HyMAP modeled runoff.
So they're, they're getting there. There are more evaluations to be done in terms of when and where SWOT discharge estimates are more accurate, so we can better use, for example, in, a data assimilation framework.
[00:14:21] Bridget Scanlon: And it's impossible to monitor the discharge of, for example, the Amazon or anything. So we really don't know what's truth, right?
[00:14:30] Augusto Getirana: Yeah. the truth is we define the accuracy based on the limited number of gauges that we have. But it is true that that's where SWOT is unique. So now you have especially distributed discharge estimates everywhere, everywhere.
[00:14:46] Bridget Scanlon: And really I think these large very wide river reaches be impossible to monitor it seems like directly. So now SWOT helps with that. so now you can estimate the discharge and you can also estimate reservoir levels.
[00:15:01] Augusto Getirana: Yeah, that's another product. So there's another one of these products is this reservoir and lake water surface elevation that you can also get the what is the extent and the volume change of these reservoirs. And that's another unique capability of SWOT because previous altimeters, if you're looking off of the satellite would pass over your favorite reservoir.
But now SWOT covers most reservoirs globally. Now you have a way more comprehensive monitoring of surface waters, like including lakes, reservoirs and rivers.
[00:15:33] Bridget Scanlon: And those reservoirs, many of them are used for hydroelectricity and so in the past it's been impossible to get any information on hydroelectric generation and stuff and how they operate, the reservoirs and everything. So now you can estimate these things with the data from SWOT.
[00:15:52] Augusto Getirana: Yeah, that's one work that we've been doing at NASA gathering the framework of our SWOT project, which is to implement a SWOT based reservoir operation scheme in HyMAP. So once we have that, we can represent the impact of reservoir operation in river systems across the globe.
[00:16:12] Bridget Scanlon: And another area that is of interest, so SWOT is I think I was talking to Dennis Lettenmaier recently and he said he was happy that surface water was at the beginning of the acronym Surface Water and Ocean Topography. So you get equal rights or whatever. But another area is in the coast, in near the coast, so it was challenging in the past to estimate the bathymetry and sea level rise near the coast.
And so now with SWOT, I think you have much better coverage in that zone.
[00:16:44] Augusto Getirana: Yeah. Now there's another working group in the SWOT science team, which they're looking at the coast and estuaries. So now it's what we have the continuing coast estuary and river. So you can see, there's recent study looking at the propagation of tides. So with SWOT, you can see that because of the two dimensional feature that the satellite has, and we can also include that information in models, in higher resolution models, so you can constraint the model downstream. With a sea level change and simulate the sea level rise impact once you have a longer time series from SWOT because right now it's, what, two and a half years. But once it gets a longer time series, we can have that simulation and quantify the impact of sea level rise or even, and even tides.
There other works that by groups in Germany, they're using SWOT to, they combine the the natural tidal variability SWOT and they can, get a, the SWOT based tides so we can use that data and ingest it in models
[00:17:50] Bridget Scanlon: And since you have also have estimates of fresh water discharge to the coast, you can estimate the impact of fresh water inflows into the ocean to evaluate its impact on circulation and things like that. I assume.
[00:18:04] Augusto Getirana: Yeah, when you're looking for topics on what to do with the global discharge product, that's one thing that I had suggested is to. There are past estimates of global contributions of inland water to oceans based on, limited number of gauges or even models.
But now we can do the same thing with SWOT.
[00:18:23] Bridget Scanlon: You have global coverage because you have this wide swath, 120 kilometers, and then the revisit time I think is about 21 days at the equator, but then it's much shorter as you go towards the polls because you've got increased coverage. Maybe you can describe that. You know how frequently you would get data.
[00:18:43] Augusto Getirana: I would say that's a limitation in terms of a temporal monitoring and, so over the equator as I said, you have a 21 day revisit and when you get close to high latitudes you have more often visits. And that's where you have combining SWOT with models.
You find the optimal combination. Because the model play that it, it's kind of this dynamic interpolator between two observations. Yeah. So yeah, that, that gap could be filled with modeling frameworks.
[00:19:16] Bridget Scanlon: And Augusto, you were involved a lot in doing modeling, to support integration of SWOT data once it become available. Can you describe some of these models?
[00:19:27] Augusto Getirana: Yeah. HyMAP was developed about 15 years ago. I was in my postdoc, CNES the French Space Agency and that postdoc was in the framework of SWOT. I was involved in SWOT in the early stages. The development of HyMAP had the goal of integrating SWOT. But then I moved to NASA and then all the priorities came up, and then I got detached somehow from SWOT, but now I'm back. So the past 15, 20 years there's been a lot of effort on integrating or find ways to assimilate what, so back then people were using synthetic data. So they were generating what SWOT would look like and test in these synthetic cases, how SWOT would contribute in improving discharge simulations. But now we have the actual data, so that's the next step. There are modeling groups out there. I don't want to list all of them because I'm afraid to miss But, yeah, we are very close to having a system. We actually, I gathered, we, did this test with the integrating simulating water surface elevation from SWOT into HyMAP. And we see that it improves discharge and water surface elevation in the Ohio River Basin and the next step is to move to the CONUS scale and then globally.
So the ultimate goal of our project is to demonstrate that SWOT data simulation can provide us with a better estimates of surface water dynamics.
[00:21:02] Bridget Scanlon: And I say online that they mentioned that the SWOT mission has a nominal three and a half year lifespan. But I know from GRACE satellites, they had a nominal lifespan maybe of five years for the first mission and it lasted 15. So do these nominal lifespans mean very much, and do you expect SWOT to last a lot longer than that?
[00:21:23] Augusto Getirana: Yeah, like all NASA satellites, they have this like short lifespan, but at the end, know, like a dream you lived for, I don't know, 20 years. You mentioned GRACE and then you have motive. I think now the idea is to just, think ahead of time and just assume that will live longer.
So we can use this data and maybe transfer them for operationalsystems to support decision making. So let's not wait and see what happens like 10 years away and work now and expect that the satellite will live longer.
[00:21:55] Bridget Scanlon: And if you do get it integrated into operations, then that really puts the pressure on to maintain the satellites and to have another mission and to keep the show on the road.
[00:22:06] Augusto Getirana: Shows the relevance and, the impact of the satellite. And that's what we do at NASA we develop a lot of modeling systems for operations.
[00:22:16] Bridget Scanlon: Yeah, that gets onto the next topic. Your integration of satellite remote sensing and modeling. And you have been involved in many projects at NASA pi or co-PI or co-investigator looking at different aspects of land surface modeling. You already described that a little bit with using for your global analysis of floods in 2025.
You used global land data assimilat runoff. And then you fed that into your HyMAP model, then to estimate discharge and flooding. You are also involved in the North American Land Data Simulation system and you are continually updating that. So can you describe, the most recent, the NLDAS-3 version, what it can do now and what the advances are relative to previous versions.
[00:23:04] Augusto Getirana: Yeah. NLDAS-3 will be a big advancement compared to the previous version, NLDAS-2. So NLDAS-3 will have. We are, working on that right now as we talk. So we have a one kilometer spatial resolution compared to the 12 and a half kilometers spatial resolution from the previous version. And NLDAS-3 is a joint effort between NASA gathered in Marshall Center. And in addition to the one-kilometer resolution. the domain now spans from central America, including Caribbean, North America, Alaska, and Hawaii. So that's a big difference from the previous version. And the outputs of NLDAS-3 are expected to be released daily with a seven hour latency. So that's another big change compared to the previous version. We based on NOAH-MP land surface model and they'll be ingesting this new methodological data set that we developed exclusively the system. And on top of all this, we'll be assimilating the rest of water storage from GRACE from its map and the European Space Agency Climate Change Initiative (ESACC() leaf area index model and machine learning based product is no product. So we are constraining the model in multiple ways. And on top of that, there'll be HyMAP providing surface water dynamics. And as a result will be supporting water managers and flood preparedness. We've been closely working, engaging, with over 150 professionals across 46 US states. And our key stakeholders are NOAA, the National Integrated Drought Information System, and the National Drought Mitigation Center. So, we're work closely working with these people so we can address their needs so that this is a system that is being designed based on end user needs.
[00:25:07] Bridget Scanlon: But that's amazing. And it's great that you're using all these different types of satellite data to constrain the models and this data simulation and continually updating the model. So, GLDAS is global, and NLDAS is now expanded area and a higher resolution.
And then constraining with all of those data SMAP for soil moisture, GRACE for total water storage and SWOT and all of these things should really improve the reliability of the output. And then it's impressive that you're connecting with the stakeholders in so many different states to help with water resources management and flooding and all of these different things.
[00:25:47] Augusto Getirana: Yeah, this has been a new NASA priority in the past, I would say year or two, that earth action, earth science to action, which is like what, when we develop something new, like using satellites or modeling systems that you focus on how that work will be improving US taxpayer's lives and also global populations lives. So to show that development will have an actual impact.
[00:26:15] Bridget Scanlon: And then, I mean there are a lot of countries that have limited monitoring or modeling capacities and so for those regions, probably what you guys are providing is probably the only thing, and it also, it provides a baseline for other things, for comparison and everything, so really valuable.
[00:26:35] Augusto Getirana: In addition to NLDAS-3, we are also developing this global system that is called NASA Hydro Globe, which has the same configuration of NLDAS-3, but it's globally at five kilometers spatial resolution and is also the backbone of GLDAS with coarse resolution but it's the I would say that's arguably the most popular data set that derived from models that we produce.
[00:27:01] Bridget Scanlon: And so this five kilometer global when do you expect that that would be released or when will that be?
[00:27:07] Augusto Getirana: So there was a first version, I think ~ 13 kilometers that was I don't, I'm not sure if it was released, it was developed two years ago. We are now working on an updated version, this one at five kilometer, and including more DA capabilities. It should be some time this year because these models at five kilometer globally, it's, it takes several months, especially with all these data simulation capabilities.
[00:27:33] Bridget Scanlon: Yeah. And Augusto you're from Brazil and I've really enjoyed visiting Brazil many times, and I've been very impressed with the Brazilian government supporting students to study abroad. And and you mentioned, going to France for your PhD in Southern France.
And working with the IRD group the French group, IRD and I don’t know how to pronounce international research pour le developmentor something like that.
[00:28:03] Augusto Getirana: Yeah.
[00:28:04] Bridget Scanlon: And, they're working globally also, and they are working in Brazil. So this is a really nice interchange, and Brazilians students have a great opportunity to travel and, see many different things. Maybe you can describe a little bit your experience working in your PhD in France and working in exchanging with Brazil and the Amazon and all of that sort of thing. Your work there.
[00:28:26] Augusto Getirana: Yeah. So that was back in 2006. So the Federal University of Rio had collaboration with the, as mentioned, the IRD, the French Institute for Research for Development. So that's how went to France to do part of my PhD, which ended up being most of my PhD.
I spent three years there working on my thesis. And the topic was the use of radar altimetry to improve the hydrological modeling of the Amazon Basin. So that's how I got, familiar with modeling with the, altimeters. And then that's how did my network in France, and then I finished my PhD. And at that time it was as you mentioned, Brazil was investing a lot in science, like in sending students abroad. So I was lucky to be there at the right time. And of course, that later on we had all the governments that almost defunded the science in the country. So after my PhD I went to work at Meteo France. I spent about one year there working on west Africa hydrology with Aaron Boone. And then after that I started this postdoc working on SWOT. So I spent a total of five years in France. There was a great experience and I got exposed to different topics like Amazon hydrology, west Africa hydrology. Yeah. was great, great experience.
[00:29:53] Bridget Scanlon: Yeah And I know when I visited in the past for different projects even people back in the sixties and seventies, they were going to the US, UC Davis. I remember the parent of a colleague, saying he went to university College in California, in Davis and from Brazil.
So it's been going on for a long time and it is just a really amazing. I know you mentioned earlier, flooding in Rio every year, but also in southern Brazil in recent, in the last couple of years and the importance of soil moisture there. But Brazil has also been experiencing extreme intense droughts in the last few years maybe.
You can talk about that a little bit. Augusto.
[00:30:36] Augusto Getirana: Yeah, since 2000 there's been three major water crises in the country. So it's becoming more often, which is interesting because Brazil is the world's water richest country. The looking at like model outputs, like 20% of runoff generated globally is in Brazilian territory. We have 20% of renewable surface fresh water. But at the same time, there's all these water crises going on. And some studies they've been they're demonstrating that these droughts, they are magnified by Amazon deforestation. When you have this feedback from the forest to the atmosphere, so it rains then there's a rapid transpiration that contributes to the atmospheric conditions. And there is also these processes called, appropriately called, flying Rivers that transfer moisture, atmospheric moisture, from the Amazon to other parts of South America, including Brazil. So there's more and more studies demonstrating that process. But I think initially like that was only a theory, but now there's some demonstrations, empirical and model-based demonstrations that this process actually happened. and that's a paradigm because that deforestation is mostly led by, agricultural expansion and cattling. And at the same time, it's impacting agriculture elsewhere in Brazil. So you're taking water from those other areas. In Brazil is one of the, it's probably the major, it is the major producer of beef, of coffee beans, of soybeans and other commodities. So if you have a water crisis in Brazil, that quickly becomes a world crisis. Like back in 2021 when you have the, that was the most recent water crisis. You paid more for your coffee as a result of that that crisis.
[00:32:39] Bridget Scanlon: And you've been able to document this with the GRACE satellite data to see the extent of these droughts. And 2015 drought starting in 2012, driven by reduced rainfall, 2012 to 2015. And then also linkages between the GRACE data and soil moisture and reservoir storage declines.
And Brazil is also, its energy sources are strongly linked to water because 70% of your electricity is derived from hydropower. Droughts impact many aspects of Brazilian lives and increasing in intensity it seems like.
[00:33:18] Augusto Getirana: Yeah, so because Brazil is so water rich, like surface water rich, I think that created a culture that, water is endless. So as a result that has a deep impact, socially, to the point that, as you said, hydropower generations about 70% of source of electricity in Brazil.
And this is because, other renewable sources of energy have been developed such as solar and wind. But still, Brazil heavily relies on hydropower. So if you have a drought in that specific basin, that where you find most of that's the Parana River basin, if there's a drought there, then the country collapses. And that's where also most of the, a lot of, agricultural production is also is found. And then the solution for that is cause Brazil relies so much on on surface water in those aspects.
We should have a backup plan such as using groundwater. But even though groundwater counts for about 55% of the nation's water demand, well that's mostly driven by irrigation. But groundwater also responsible for a significant portion of the country's small municipalities. About 40% of Brazilian municipalities rely on groundwater, but they're mostly small municipalities.
The large ones still rely heavily on surface water like, Sao Paulo, that 2021 found itself with almost no water. but at the same time because Brazil should look for a backup plan, in these case is like when you have no more surface water in a specific region, you should go for groundwater. You don't have enough monitoring. So if you look at the monitoring network for groundwater in Brazil they have about four or 500 wells, which is 40,000 50,000 times less than what you have in the US. And -Brazil is larger than the US without Alaska. So that, that you can see that there's a big gap in monitoring.
And without monitoring you don't know how to optimally use that water. Now you could have ground water as a backup plan, but you cannot be in a situation where Northwestern India is, or Bangladesh is where the groundwater is depleting. You have to be smart. You have to use groundwater in a wise way, but for that you need data.
[00:35:48] Bridget Scanlon: Yeah. And you mentioned Kaveh Madani in one of his recent report. On global water scarcity. And actually it was he called it water bankruptcy, I think. And mentioning that surface water is like your checking account and groundwater your savings account.
And important to develop them both. And I know when we had Davi Mello visiting here for a year, and he was looking at the drought in Sao Paulo in around 2012, 2014 area, almost the total reliance on the Cantarera reservoir system, and then that was dropping off a cliff and, but then there's a lot of groundwater being used.
Ricardo Hirata says you know, it's not permitted, so you don't know how much is being used, but suggesting that up to 25% of the water in Sao Paulo was coming from groundwater wells. But I think you had a really nice comment in nature about the importance for Brazil to develop a drought plan, and I think that would be very valuable. Because, to understand and to monitor the system and to understand what the resources are and all of that sort of thing. Very important part of planning
[00:36:57] Augusto Getirana: Yeah, I've been collaborating with the Brazilian Geological Survey and the Federal University Rio de Janeiro in the framework of a PhD thesis that was being developed by, Clyvihk Camacho and the goal. And he works for the Brazilian Geological Service, and the goal was to use this number of groundwater gauges in a machine learning framework combined with a multiple satellite data, including, MODIS, GRACE, IMERG and other geological information to get this spatial and temporal distribution of groundwater variability across the country. So that's the first step. So he concluded his PhD last year.
We have a paper describing the dataset. And my hope is that this dataset can be eventually transferred for preparations by the geological service and being used as a guide and motivation for the federal government to install new wells to more into groundwater.
[00:38:03] Bridget Scanlon: That would be great. So it, it's marvelous that while working for NASA, you can also help your home country with flooding in Rio drought and all of these things. So that's really cool.
[00:38:13] Augusto Getirana: Yeah, that goes in my overtime. That's, yeah,
[00:38:20] Bridget Scanlon: Yeah.
[00:38:21] Augusto Getirana: Yeah, I do that for fun It's not actual work
[00:38:24] Bridget Scanlon: But it's nice to be able to give back to your home country too, so that's.
[00:38:28] Augusto Getirana: I do that cause I have all these connections with Brazil, but not limited to working with the Brazilians. Whoever is interested in collaborating, I'm always open.
[00:38:39] Bridget Scanlon: We also release the scripts of these podcasts and also highlights, and links to papers and stuff. So if people are interested in more background information that's linked to this podcast we provided on the Water Resources Podcast website. So thank you so much, Augusto.
Our guest today was Augusto Getirana research scientist at NASA's Goddard Space Flight Center and in the Hydrological Sciences lab. I really enjoyed the discussion and it was nice to hear that, your feeling is that flooding intensity is not increasing based on your analysis of 2025 in the last couple of decades. And describing these new satellite missions and how NASA is really trying to connect with stakeholders and get the science out to operations. So that's really cool. I.
[00:39:24] Augusto Getirana: Yeah, thanks for having me. It was a pleasure talking to you.
