 So I don't think, I guess we don't have to use our mics in this one, but we wish better do because there are people online, there are 23 people online and we are about 12 people here. So we have a big group here. So Lauren Everett is gonna be taking notes and typing it onto the screen and Stephanie Granger is our rapporteur. I'm the moderator, which means I don't want to talk. I'll just read out the first question and people start jumping in and I would really request everybody to give their opinions on one or more questions because everybody's voices need to be heard. The first question is, what are the challenges and opportunities for future research in understanding freshwater budgets? So take it away. I would say opportunity-wise. Mic, mic. Oh, sorry. Mic, mic, microphone. Oh, mic. Okay. In terms of opportunities, if we're talking about the future, I feel like we're still sort of in the early innings in terms of remote sensing technologies. We're still developing new technologies and so as those current technologies improve and new ones become available and it's not just big, like I said in one of my slides, it's not just big flagship missions, but you can be thinking about things like CubeSats, Airborne, making use of cell phone signals, weather balloons, all sorts of things, UAVs. I think we're still early 30 years from now, we could be saying, oh, I can't believe, how did we get along without something? So I think there's still a lot. If we continue to put the resources in developing these technologies, I think there's a lot more information we can get to constrain our water budget analyses. I mean, from the challenge side, on the remote sensing too, the limitations, uncertainties, biases, having a sound understanding of them, which does play a role. I mean, there are lots of places where you really can't close the water budget with raw data, needs a lot of processing, having better workflows and understanding across the community of how to use the data well. Yeah, so just to follow up on that, I think also, we need to have more transparency in what's actually the data underlying our data sets because we have a huge growth in gridded data sets that are easy to take off the shelf and use, but we actually don't have a huge expansion in in situ measurements. And so we have kind of like the fallacy of thinking we have huge data expansion with the exception of remote sensing where we are really having much for remote sensing data sets, but I'm not sure it's really always transparent to people what are the actual data points and what are the direct data points versus the inferred data points. And I think that's really important. In cases where groundwater plays a major role as a contribution to the annual fluxes, which is almost always the case, the there's a lot more work done on characterizing things shallow, but not enough on deeper systems. And it's not exactly clear where that information is going to come from as far as on a global scale, if you want to constrain hydrologic partitioning and water budgets on a seasonal to annual time scale, the information needs that we have from the subsurface site and where that's going to come from. That's a big challenge. Okay, so to me, there is a great opportunity there is the fact that I do think there is a lot of potential and unexploded opportunity to try to see how we can use the different remote sensing data and leverage on the strength and the weakness to try to do this characterization. And being aware of what are the uncertainty, what we are really looking at and how we can compare it with the model and how we can use them developing in a diagnostic way also to see, to highlight what. And I do think that there is a lot of potential is very tricky, it can be very dangerous, one has to be very careful, but I do think that there is a lot of information and we have to think how to put it together. Yeah, so along those lines and thinking about understanding the deep system, I think there is a lot more to be learned about the components of the water budget that are deep, so inner basin flow that is sometimes ignored or groundwater discharge offshore, things like that. So components that are harder to even know exist and are often, I think, not taken into account. To kind of add up on the opportunity, I think really combining data, really integrating the different data sets that we're getting from remote sensing with in situ data is kind of where we need to go to be able to understand where our uncertainties come from, how big they are, but also to really have kind of a mix of the different communities. So have more of the people who do surface water talk to the people who do groundwater talk to the people who have modeling to kind of really not have this spitting of the community but really have everybody working towards the same problem together. Getting a little bit more tactical having been a hydrologist for a long time, monitoring, in situ monitoring data is very expensive, both drilling wells and collecting information. During the course of my career, very little has happened technologically in terms of how to make data collection more efficient, more effective, and using technologies to measure water levels and access it more effectively using remote sensing technology. And I think that's a big issue from a groundwater resource perspective is we're building models, but the technology to collect the in situ data is still pretty rudimentary. And to add up on that, I think it's not only collecting, but also sharing data. We don't have a standard way of sharing different data sets. And for example, in INSAR, if I was to give my INSAR data to someone who does modeling, it would have no idea what to do with it. So I think it's also trying to develop a standard for the community so we could just have the data within the same format or that could be applied to the same problem. I do think there are some really exciting opportunities with EM systems, Sky TEM, the images and maps that they produce are just amazing. And I would argue that getting Kowasi or the hydrologic community to argue for a Earthscope type campaign to try to map these deeper systems would be worth considering. There's a question from online, or a comment from online. Development of technologies to integrate multiple sources of data, IE pipelines, standards, interoperability, and time and space. In this way, we would be able to characterize the uncertainties and evidence where the major needs are. Yes, Matt. So one of the key tools, and we haven't said explicitly yet, one of the key tools for integrating the data are the models. And I think the models have made huge advances over the past 10 years or so. That's actually what I thought Laura was gonna say when she talked, but better models that are more explicit and more sophisticated in simulating the water budget and in particularly groundwater storage and fluxes and the advances we have in computing power at the same time. I think there are big opportunities. And again, I think over the next 10, 20, 30 years, there'll be major steps that are made in our water resources and water balance models. And in particular, how they're able to integrate data and simulate groundwater fluxes effectively. So can I add on this? I do think that there is having more model there assimilated but also having a robust way to evaluate the model specifically for how some parametrization, some process are and figure out. And I think that there is an opportunity in trying to see how we can use the information that we have. And maybe we are now, we can maybe able to have an understanding of the answer to some regional scale. Maybe we don't know exactly and the subgroup but maybe we still have characterized the process in a larger scale and that already can have more confidence and then you can narrow down at the level of the model. So target what is the level of which we can do evaluation or product and then what does mean that in term of processes. Is that an opportunity or a challenge? I'll be both. I think it's an opportunity but maybe it's a better challenge as well. I think it's both. So I jumped out of the, I should have said a modeling thing first but I agree with you Matt that we are, we do have a lot of advances in modeling which I think is a good opportunity. And actually my first point about data was because it's hard sometimes when we're validating models to understand when are we using a model to validate a model, what's our direct points. So really better ways which I think is to both of your comments to evaluate our models in more sophisticated ways and understand what parts of data sets we should be using to really validate to and to evaluate our model behaviors on and what parts of data sets we don't use or we use in different ways and when data sets are redundant or not redundant. I think to like really understand what's coming out of the models we need to do a better job of that. But then of course like I think there are great opportunities for what we can do now with modeling at really large scales and at high resolutions and I think there's another good opportunity for changing as we have kind of a different computing landscape changing how people can interact with models that generally that like the people really running large scale models is a very small sect of people and then the rest of the community gets to look at those outputs and you know maybe use, maybe download them and use them depending on how they're shared. This comes down to like data standards but maybe sometimes even that's hard because they're just really huge outputs and there's a lot of barriers to entry to that so I think there's really great opportunities moving forward to figure out how we can have better platforms to run these models on and to make it easier for other for a much broader community to run parts of these models, experiment with parts of these models, make them better because we do know when we're running global models and national models that we're limited to the information we have on those scales but locally we can do a much better job at modeling and we don't really have that information like feeding back up, we don't have a mechanism for that so. So we are approaching about 15 minutes into this conversation. We have four questions and my suggestion is let's have a few more comments and then go to the second question and we can always circle back so that we can give the last question the same amount of time as we give the first one. So any other comments on Chuck? On the opportunity for that, I think that I talked to some other folks here about the groundwater modeling network, National Groundwater Monitoring Network managed by the US Geological Survey and I know that they are very interested in working with anyone who's got groundwater data to take it as an input and I think they're using existing standards to do that. They went beyond what the USGS typically had used and are using a groundwater data standard that is I think broadly, I think it's water MR but anyways, I think that's an opportunity for information exchange. The other thing I wanted to mention though on the freshwater budget from a use standpoint, I'm with the National Groundwater Association and one of the things that we've been recently concerned about is all of the flooding that's going on and it's affecting different parts of the country in different ways but it clearly has a groundwater impact and I mean, immediately the flooding can affect water that goes into the wells. If the wells aren't in good condition, that's an issue for sure but also I think that some of the states had observed a higher level of total coliform positive results for samples that had been submitted for wells that had been flooded in some of the areas and I think it had to do with some of the, I'm just hypothesizing here but in talking with other folks, it seems like it may have had something to do with pre-existing conditions in those situations where there was a lot of rain before the flood and a lot of rain, I'm talking about perhaps like weeks worth of rain before the flood occurred and so the septic systems and for the private well owner got connected to the well and that's just, I don't have any proof of that, I don't think the states have any proof of it but they did notice a higher percentage of total coliform positives in some of those events and it would be very useful to use any kind of remote sensing data to help guide them in terms of figuring out where to look, where to test, where to encourage people to submit water samples from and begin analyzing what is going on with these sort of chain circumstances in these locations. Any more comments? And let me just interject a minute here and say that I think many of the people, the speakers as well as the panelists have talked about international stuff so I know that we have a great deal of data in United States and USGS is certainly one of the best agencies collecting this data but we want to also think motivated by a little bit of Holly's presentation how we do this in areas where we don't have data or we don't have a connection to them because especially in-situ data in countries where A, they may have never monitored it and B, how would we go about doing the challenge? John, I'm going to pick on you, I'm sorry, your USGS, I know, I know, there's John, because you're USGS and how does USGS go about, suppose I said tomorrow I want groundwater data from Niger, what can USGS do? That's very difficult for us, we have an international program office but a great deal of our emphasis is US-based so it's always a challenge for us, it's usually done through cooperative efforts that are negotiated with the other countries. So we have active research efforts going on with various countries and if they have an emphasis on groundwater then often what we're doing is technology transfer to them and helping their folks get up to speed and making those sorts of measurements and then providing those data to us. But it's really on a project by project basis, that's in my experience often brought to us by the countries in question. So I have no answer to this, can we figure out, so we in principle, we want observation everywhere but there are some places where they're more useful because of the processes and so I think that once that would be can we narrow down places where we really need it and places where maybe, and then what are the science question for which we really need it and if we can have already some result, some understanding of the process without having and then we can prioritize, I think that that's... Yeah, I had a similar thought earlier when you were talking about the pie in the sky, how would you describe the sampling structure for the pie in the sky and I don't assume it would be a regular grid, it would be something that would be prioritized or done on the basis of some climatic or physiographic feature and so putting some thought into if we could sample the globe, how would we do that from a spatial scaling standpoint and so forth, that's a pretty interesting question I think. Actually, you made a good segue to number two. What data are most useful in determining freshwater budget and what information would be useful to have which you are currently struggling, we currently struggle to collect. So that's a good one because that actually segues properly from your comment. So in this is like the data, depending which process you are trying to model to understand, do we want to understand something at the regional scale, do we want to understand and also about what are like the time, the spatial variability of the process at different location and so exactly, can we just look at the globe and say, okay, those are some hot spots so we know like because of this density populated region because water is, like if you want, it's more of an issue if that happened in Pakistan or in India than the same thing happened in the US because it's a big deal, but they impact in terms of, so and then so find some place and find some places where we can characterize what is the need and what are the priority in terms of spatial and time variability. So when we look at data needs for constraining water budgets in the groundwater systems, a large groundwater system, regional groundwater system, remote sensing, large scale, then there's head measurements, groundwater, what we call groundwater data. Even with that, you don't get definitive answers. The next level is environmental isotopes and in many, many, many cases you can't really do without that, right? And when we're talking about closing water budgets and things like that, it's one dream to have remote sensing. It's quite standard to have flow data but then you don't really complete the story without environmental isotopes and those are clearly the hardest to come by in terms of not having anything in situ. I would agree with that and I think groundwater residence time, especially along the flow path, not just in low-lying regions but along a regional aquifer is incredibly valuable for modeling studies and for assessing sustainability of water. Very young water is less sustainable than Pleistocene age or Holocene age waters. So can I take a step back? I completely agree that those data are what we ultimately need but they're very expensive and rare. So going back to how do we prioritize and if we wanted to have data everywhere all the time, we do have deformation data almost everywhere all the time within SAR. And we've seen subsidence places where there's groundwater problem that we didn't know about by looking at ground deformation data. So I think there's kind of an architecture that we could build in term of, yes we need the data set very precisely but we also have some indication of where we should look to get this data set to have the most important processes covered basically. So and I would say that we should do this with all the remote sensing data to some extent. So every remote sensing data set have different strength and so they can help and so say what this can give us in terms of the processing and what component is gonna and then use this as a first and then go and work on it. So just to go in another direction we've talked a lot about what we need to understand the natural system but I think we're really lacking data in human water use depending on where you are. There's some places where we're monitoring that well but in a lot of places we don't know we're using groundwater as like the closure term but we also need human use as the closure term so humans we need data on the water we're using. So online, this is a brief second comment and preliminary comment to the first and second questions. Data-driven models have evidenced encouraging abilities to improve data sets, integrate multiple sources of in situ and remote sensing as well as evidence sources of uncertainty. This can be used to overcome data scarcity and heterogeneity. Okay, as I said that I would like everybody to speak so I'm going to pick. Jim, please, please. Jim is at USDA so he offers a perspective well yeah I'm actually writing down things as fast as possible because you're giving me this and I use these activities as stakeholder input so what you say is going to help me decide what kind of priorities will come in the next year or two or three and so obviously we talk a lot about groundwater and when you actually get out into the field and look for the data oftentimes the data is non-existent or it's patchy and I think coordination and knowing where to put the data that's one of the things that I'm a little confused still we talk about these data sets that we generate but where are you putting those data sets and are they going to Kowasi or are they going to some kind of data broker? USDA for example, we ask you as an awardee to have a data management plan and to tell us what you're going to do to make that data available to people so that they can use it in a modeling context or what have you and yet we have not been upfront about telling you where to put your actual data and so you're kind of on your own and that's not a good thing to have we need to make sure that we have some repositories and I think the federal government is actually waiting to see what the libraries the university libraries are gonna do whether they're going to step up and become the data repositories so far, not so much and so at that point then we have to back up and say okay does this require federal investment and are we going to have to step up and actually put some money toward data repositories and making that data available which means that you have to have you have to massage the data and make sure that it's understandable by people and it's all in a similar format and what have you so this data question is really critical and that's the thing that's why I'm writing medley is you keep telling me what you're gonna do with your data I'm putting that down so I can go back and make some suggestions. Jim, let me ask another question here. Sure. So the question I have is from the USGS perspective how do they handle, I know you have FAS Foreign Agricultural Service how do you handle this data set? I mean again I'll go back to the question I asked John is if I want data from Niger on irrigation is there a way you can get it for us or is there a way USDA can get it? Sometimes it depends on whether we have an active mission in the country and so if we do so for example let's take Morocco, okay so there's a foreign egg there are supposed to be in every one of these countries that works with the United States there's supposed to be a foreign egg service individual with the embassy and that individual is the one that would be the one collecting that data and so there are times when I have asked particularly in the Middle East what the data situation is because oftentimes those are the folks that have actually tread the ground that we are now just beginning to tread. In the Middle East they've been dealing with groundwater issues and drought and aridity for 40, 50 years and we are just getting to that point where we're matching up the demand for water with our population and so sometimes we need to lean on other folks to be able to deliver some technologies and some data so that we can see which way to go in the United States and so yeah, so at every embassy there's supposed to be a foreign egg service individual and those people are collecting this data for sure but again USDA does not have a central data repository we have the National Ag Library that is gearing up to be that but it's been gearing up now for almost five years and we still don't have a situation where it will collect a wide range of data types and that's what we need particularly if you're looking at trying to match up biophysical data with socioeconomic and sociopsychological data for behavior change or adoption, you know trying to assess that so you're going to have data repository that can accept all those different types of data including time series. So one thing about the data that I've been thinking and I think people is like how do we create, what are the products so exactly that we have to generate so that people can compare and have some standard format so it's about where we put it but also if we want something that the stakeholder or the local people are using I'm starting to think I have to do shapefile of everything because that's what people use I'm just thinking so how do I translate or just make my product the information in a format in a way that they are gonna be because if it takes too much energy even if I give them gold they're not gonna use it because it's gonna be too hard to so I think that we have to and that's a discussion that takes time and takes thinking and it depends also for what but I think that that's very important. So one thing I think that we don't have to reinvent everything if you look at other community like the geodetic community or the seismic community they have developed observatories that are funded by NSF that are handling data storage for any kind of geodetic data for data that were processed from Earthscope or this data storage also you have the codes where you can just run the codes and it creates a metafile where you have your data in a certain order basically that then someone can just download and run. So I think when Jim when you're asking about what do we need maybe we need to move beyond relying on single university or relying on people doing the work and we need to push to have some kind of environment like that where our data can store then handle. So what we need we need really that everybody use open sources let's post the codes on get out but they use the user part and that's I think actually the program and now that they're really moving in the fact that you have things they're gonna be put in a way that- I agree for the codes but you can't store data online or it's gonna cost you a lot of money. I agree but just think about a way we do it. Mark. I was just feeling like agreeing that a standardized repository like Iris Pascal for seismic data is needed with staff members to help the community upload the data remind the community instead of currently you have to kind of figure out your own when you're submitting a paper you figure out where should I find a permanent home for my hydrologic data if it was standardized with a federal repository it would make a lot more sense. Yeah I agree and I think that's you know I mean I've been pushing the folks that I've been awarding grants to Kowasi but Kowasi is changing its stripes too it's not going to be repository into the future it's gonna be a broker and they're going to try to find some other like Iris or some other form or function of repository so you know I was relying on them but now they're gonna shift around and do different things. One challenge I think we have with the kind of data that we're talking about is that it's not just time series data say from wells or discharge data but also 3D spatial data so how do you deal with subsurface geophysical data and well logs and all the different kinds of data that need to be integrated into a lot of these models I think it's a big challenge it's been a challenge for Kowasi you know thinking about what kinds of data they're able to take in just because of what they would have to build in their database in terms of storing data that's not of the time series flavor or of the point time kind of flavor so I think that there are advances that could be made in thinking about databases that are more integrated in terms of data type. I just going back to the question I think we started off with some maybe secondary data needs I would start off with the primary fluxes the most important you know if you're going to do a freshwater budget you want to know the precipitation evaporation runoff and maybe the water storage change right so to me that's what you start you start there in answering this question and then there are a lot of other things that are useful and then there are also things that are useful that we currently struggle to collect and so primary those I think I grew lower the human water use and then what Holly just said about the parameters the things used to parameterize your models which are the hydro geologic subsurface variables that we really struggle to collect that are critically important. Okay so I think what we can do I think what we can do is we can segue into the third question because we are marching on schedule here what aspects of freshwater balanced beyond perhaps precipitation and snow water equivalent would benefit from NGA resources now let me give you an explanation because I did speak with Tony this morning I mean there is no NGA website with all the data housed okay so it's not that kind of agency and so they do process data like DEM data etc and make it available through NASA or USGS or whatever you know the other federal agencies so the question now here is not that we really know what NGA has with respect to data but more so is what can we expect them to help us with so we're trying to turn the question on its head a little bit here so what are your thoughts on that so what are the aspects of freshwater balance would benefit from NGA resources I mean what can we ask them say that can you help us with XYZ I mean if they can I mean something like NGA if they can be a steward for airborne campaign that would take airborne electromagnetic which has a footprint that's much smaller than remote sensing and so it gives you a lot more precision especially that would be very helpful in many places yeah but remember I'm talking about countries of the world where I do not know if they would take very kindly to a US aircraft that's exactly why I said NGA somebody just mentioned a hundred and thirty million dollars but we digress I mean what are the no let's not this thing so what data would you want I mean would you want the 3D seismic data would you want the irrigation data what would be the most this is the real question here we'll worry about how it's done later so what would be the most important data Laura I mean you're a person who does this thing what would be I mean the one thing which NGA can provide you and again we're not talking about data in the central valley we're talking about data in Niger so I'm trying to go back to places where you and I are most people in this room have not worked sure so please well I already said data on human water usage so I second the need for that if I'm going to build a model any data on the parameters that we actually use for our models like permeability, porosity things like that are really valuable but the flip side of that if you can't get that then what we really need are observations of water levels and storage and really if you're going to build a groundwater model and you want to build a good groundwater model you need not just heads but you need fluxes which is what Hariya also said so that's like gets beyond just like what's your stream flow but actually any places where you could actually observe anything about what base flow is and what groundwater discharges you just asked me what I want though I have no idea how you're going to get that like in Iran I don't know how no how is the second part I said the question over here I mean the question in the breakout is what aspects would benefit from any resource yeah so I mean I feel pretty good about like precipitation and land cover and then we go deeper and it gets harder or more complicated two things one is I think any water data they have that they think they can declassify will take it right so we don't know what they have but if they have water data and they want to declassify it great we'll make some use of it the other thing is I think they can you know potentially help by partnering with us to improve either you know instruments or models either one they want to partner with us and what we're already developing could be mutually beneficial I'm sort of reminded of the time when height of Mount Everest was measured in the old days for the first time it was done by stealth I mean there were people pretending in spies who were pretending to be people going around making sextant measurements from different places right so if there is really a sensitive place of the world where we need water data they probably need people like that on the ground making, taking samples things like that well my take on this question is really focusing on water use and what NGA could help us with is getting the the area to be a a smaller geographic area that has a reliable result would be critical because you know we think about water use irrigations at the top of the list in terms of quantity and knowing where that that changes quite a bit would be significant certainly drinking water supplies around major cities whether it's in the United States or in other countries would be important mining isn't necessarily as extensive around the world but certainly where it occurs there's a lot of lot of groundwater use related to mining and it could affect local communities in different and ways that you know may be useful may not be helpful to those communities so I think focusing on the use and getting the area down that's got reliable results would be very critical to the United States or any other country I have a specific request to have one specific request that you can't get Nile data Nile River discharge data past 1983 I think it is from the global runoff data center I I bet NGA has it they probably have a few other rivers too my guess is NGA has data on multiple scales that could be very useful because they're looking not only at global conflict areas but at localized conflict areas and we need to explore that with NGA is what's the scale of the data that they have in their own repository most of what they have I imagine is mapping data land use land cover they probably have a lot of weather data also that could be beneficial for improving model accuracy remember one thing when we are deliberating in this breakout and the three others which follow all of this is written in a report which Lauren is going to painstakingly right after the meeting is over so this goes to NGA so your voice from this report will be heard by NGA so your Nile River data request will probably be noted so so the thing is that you know you're trying to make them aware of what the community needs to do a better job at these things so you know what they can do or how they can do it as I said very secondary to this discussion is what we want is the first thing and I will add to Matt's my own pet peeve that we do not have discharge data on the river Ganges or the groundwater data details groundwater data in the Indian subcontinent for example for people working in the Ganga Brahmaputra River basin Lauren yeah also on I just want to expand a little bit more on the human water usage we need data not just on usage but also on infrastructure which is something that is often more sensitive even than the water usage data but if we're going to do any sort of like scenario planning understanding how people can respond on it's one thing to know like where they're irrigating and not but another to know like what are the what are the reservoirs what are the reservoir capacities where are the irrigation you know how can you actually plumb the human system and that's really important from like a sustainability modeling standpoint in a sort of strategic perspective if you go to Africa today you'll see the extent of Chinese investment in developing infrastructure within Africa and by doing that they have access to a lot of regional information that is very crucial and in a way it's a missed opportunity if the US was making the same kind of investment they would have access to data streams like that two people have not spoken sure I think as a modeler the most important left box area is the underground structure so not only from the soil layers but also deep into the bedrock or confined aquifer structures are mostly unknown so it's hard to model the groundwater contents so if they can build up some kind of data that would be very helpful very wise any other data requests okay let's go to the last question we can always circle back or we can have a longer break if you want entirely up to us what are some examples of successful collaboration opportunities intra agency international interdisciplinary and what are the promising partnership which could help advance our understanding and I'll start with John and Jim because you know you guys are at USGS and USGS so I know you mentioned John that the international office so what are some of the successful partnerships where with USGS I mean I know USGS a lot of international work I didn't realize it would be representing the entire agency here based on my experience and my exposure we have examples with Brazil for example most recently that I'm well aware of looking at mapping irrigated lands calculating evapotranspiration modernizing stream gauging methods developing large-scale particle intra volometry methods for example and the use of UAS and ways of more economically gauging a larger number of streams and that's the example I had in mind when I when I mentioned that often you know nations will approach us and it's very much a co-funded effort you know we don't really have the resources to to lend grants to agencies to help transfer technology the other thing I find though in a lot of these efforts is they take time they take quite a bit of time to make progress mainly for communication reasons and so I just want to make a point that you know for things to be successful they need to be in place for a while and you need to have interactions quite frequently and very personally in order for them to be effective so that's just something to just an aside to keep in mind I'm sure there are other examples you know in the Middle East we've had a lot of partnerships especially with groundwater I think I think in terms of underdeveloped nations those are you know Brazil well they're not underdeveloped but I mean you know we don't we don't again necessarily have a sort of aid program where we're going out and doing these sorts of things they tend more to be ones in which we're both benefiting and learning from the process and the implementations that we're doing and that's what stands to work for us if we can't justify what we learn from the process we usually can't engage in it let me ask you a follow-up question so just like Jim said that in every embassy US embassy abroad there is a foreign ag person is there a representation from USGS in some other form like the science advice you know the science I know there's an environmental science and technology office in every yeah we don't have an equivalent you don't have an equivalent okay so there is a federal mandated agency for AQUI agency for AQUI agency for coordination of water information I don't know if everybody's familiar with that there is also a subcommittee on groundwater and they're always trying to talk to one another about data needs data resources data integrity data quality and everything else like that so for those that aren't familiar with it check out AQUI and check out the subcommittee on groundwater a lot of these issues the interagency coordination is trying to coordinate and develop some solutions for over the last couple of years that effort has diminished obviously because of federal funding but they've been very active in fact the national groundwater monitoring network was developed as an offshoot of AQUI and the subcommittee on groundwater so I think there's probably more information out there than everybody anyone individually might be aware of so I'd suggest you check that out let me just interject and try to get Jim's perspective from USDA on the forum on the collaboration so the most recent has been with Israel we just recently actually truly collaborated with them to solve issues that and including groundwater as well as surface water and the use of nontraditional water sources for managed aquifer recharge for example we brought monies from both the US government and through BAR the binational agreement on research and development that is part of and funded by the Israeli government together to solve problems that are important to both countries and and it helps to have linkages that you've built with these countries because it just so happened that at the time we we rolled this out the head of Israeli water was an individual that post-doc at Utah State when I was a university professor there so we had built some connections there that made these kinds of activities work much faster than they would have normally and and and so and the same thing we're working with Jordan to try to do the same thing we have relationships with China and the and Britain to do similar things and it's really a sharing of money so that we can bring money together because then you're really in the two countries are really invested in it and it's and we've been really working focusing on trying to reduce the footprint of agriculture relative to water that was that's the key and to reduce irrigation by up to 50% in both countries and obviously israel has just as much information to give us as we have to exchange with them i mean they of course have been using non-traditional water sources for a long time we have not with the exception of california texas florida and washington state those are the big four that are using recycled water to irrigate crops but you know it's those are the important things it you know paving the way so that you know so and having those experiences overseas where you meet folks and they actually see you face to face makes these things work a lot easier so one example that I can think of that I wasn't involved in but I thought was pretty neat was a collaboration between the usgs of clifas and the four countries that share the newbie in aquifer so I think it was funded by the IAEA and they worked together for I don't know six months or a year and and together developed a groundwater model that would help to manage the the newbie in and I think it was a really good collaboration because it got buy-in each country had somebody actually working on this model and you know I don't know how much it's being used or how successful ultimately it is but I think cooperations like that among governments are really important for trans boundary issues and also you know like you said just getting the communication going can maybe help us deal with some of these data issues and and sharing issues that exist yeah so an example I can provide is I think NASA's applied sciences program has done a really impressive job at bringing together you know experts at NASA who bring in their technologies and data and models that sort of thing together with with outside agencies private industry and users of all sorts both in the U.S. and internationally and what they do is sort of provide this seed funding for a project and and it lasts for three or four years and by the end of that time period the expectation is that the the non-nasa partner will have will have sort of adopted the technology or the data and will be able to to continue to use that technology or data into the future with with their own funding so I think it's a nice a nice model it doesn't work every time but there have been a lot of success stories that have come out of it and those partnerships are absolutely essential because oftentimes the process for getting data for talking to people at the ministry is very formal and you have to have a good relationship in order to even talk to somebody and so this oh sorry and so this the partnership between NASA and USAID has really been beneficial in paving the way and informing helping agencies and governments in country work with NASA scientists on agricultural issues water resources issues drought land use land cover etc it's it's been quite successful in many many ways another example that I can think of is NSF has the infuse project innovations of the food energy water nexus but there's also the infuse and that's also with nifa but there's also a I forget what it's called infuse china version of that where researchers write proposals you have to have partners in China writing to NSF China and in the US writing to NSF in the US and then the projects that get funded are approved on both sides and then both collaborators have funding I think you know it's been said by a couple other people that really the key is actually having some like funding on both sides that you have people that are like vested in being at the table I thought NSF infuse was being phased out yeah I I think you I think so but I'm not an expert in the yeah this was the last year for funding that but now we have signals in the soil that's a new one that has been picked up by both nifa and NSF and so we just I think we just ran the panel this last week for that one so we're going to continue to work with NSF and these keep in mind that both of us can fund international activities so we're we're both domestically focused but we can have international partners as subcontractors so as long as the cost center is actually in the United States and and by a US citizen they can have as many international partners as they want so I served as NSF program director for hydrology july 2017 to december 2018 so I know a little bit of these things and it's not specific to groundwater or NGA partnerships but there's also NSF has a bigger program called pire don't ask me what it stands for it's international something something international research and education you must have written a proposal to it no I didn't reviewed yeah so they have pires and now piggybacking on what Jim said the new the latest program brainchild of the ad for earth sciences belligerling is cope so it's coastlines and people so obviously some of this groundwater stuff can be tied to it and especially what mark showed exciting stuff today it's coastlines and people cope so you know so it's a it's a new program and the infused US China actually I handled the proposals for geo so I do know it's a very exciting thing but you know it's a it's a little complicated process at least when I handled it because the proposal sometimes NSF China had different ways of evaluating it as opposed to US side I mean US side is very straightforward you know it goes through panel and you have all the comments if you want to read about it but NSF China there were some some kinds of somebody once told me that they you have to know the panel members before you submit I found that very weird but any so so there are many of these things and and and most of the stuff which you can do as Jim said the cost center has to be in US listen that you cannot send money off to another country so that makes it harder to get collaboration in especially smaller countries where they may want some money but on the other hand like the example Stephanie gave about severe you know we did all the research in US I was one of the severe recipients but you know we went there and did some training workshops you know I did training workshops in Thailand and Vietnam so that gives you give something back to that community so that's one way of doing it that's with the NASA side so and we have a new water quality and quantity sub priority in the AFRI foundational funding line that our proposals it's a research only right now it's not a lot of money it's five hundred thousand dollars for three years but it's we have almost seven million dollars so we're going to be giving away a lot of proposals we're going to fund a lot of proposals and and it is you know we have underfunded groundwater so we realize that and so we've been trying to push folks like you and and the community to apply of course we're the US Department of Agriculture so it has to have an agricultural hook but you can easily you know relate groundwater to irrigation requirements or or what have you or you know water quality issues with with nutrient flux and what have you so be sure to to spread the word because this is a new one and we're expecting we're hoping for a lot of proposals so AFRI is the agriculture food research initiative and there are several requests for applications underneath that one of them is called the foundational and the foundational is supposed to be you know more leaning towards discovery level research like NSF and it's supposed to support these larger projects that we fund called coordinated agricultural projects that's another request and that's those are 10 million apiece but the ones i'm talking about are 500 000 but then they're particularly good if you are a new investigator for example if you're you know untenured and you need to you know start pulling in money to get tenure but these 500 000 you know we're going to if we have seven million that means we're going to fund 14 of them and so you know they're they're easier to get let's put it that way you don't have to have big transdisciplinary teams and what have you so be sure to take a look at that that's that request has been out there's no letter of intent for this particular one and it's due august 1st i think people are reaching their limit of energy so what i'm going to do now is i'm going to turn around at the risk of not speaking the mic i'm going to go and read out what lauren has typed lauren can i please see so what i want you to see is i don't even have to read it out please i want you to do is because this is the consensus of this group of people so i don't want anybody's voices not to be heard or you know muted here so please can you look at this and say hey can we add something more to it uh or can we delete a sentence so can you please look at it and i'll i'll read it out just for the sake of it in so opportunities and challenges two separate breakouts there opportunities like remote sensing technologies kubesats uavs collecting and sharing data em systems large-scale model accessibility usgs groundwater modeling obviously a success story and information exchange remote sensing to guide requests for water sampling challenges are uncertainty biases raw data needs lots of processing needs transparency in the data set uh not enough on deep systems what are the data sets should be used for validation international partnerships are generally on project to project basis so any comments on this part where we can add something remove something make something stronger and with the large data sets and all of the sensors that we're using what about uh artificial intelligence and how do we techniques yeah i think we should do the word uh new new data techniques is that reasonable to say that yeah new data techniques yeah artificial intelligence knowledge discovery or all of yeah machine learning okay what the second question or second yeah second question was what data are most useful in determining freshwater budgets and what information should be useful to have we are currently struggling to collect primary flux is most important i think many people accord that human water use obviously uh i guess we could also put irrigation human and irrigation water use is that reasonable yeah and irrigation and then 3d spatial data integrating into models uh you know stratigraphic data uh and then the needs and priority depends on process isotopes groundwater residence time subsidence data data driven models need to consider to put data data management in sharing and data management and planning coordination repositories pursue international partnerships i think this most of the things are covered here anything else to add to it i if you're gonna make the distinction of human and irrigation i'd add human industrial and irrigation absolutely absolutely yes yes yes yes carly i think you have a comment from the line right yes but this actually goes back to the first question is that okay absolutely yeah okay um so for number one a challenge is in general a large percent of the semi-arid to arid western u.s has a relatively sparse distribution of in situ monitoring sites however the challenge is larger in rural areas a great deal of agricultural production occurs in those areas that's that it's vital to fully support existing monitoring as well as to expand the density of monitoring stations is vitally important in addition throughout the western u.s communities are actively involved in long-term continuous integrated water resources planning to support sustainability and resilience i think that's enough yeah i think that's okay so the third one is what aspects of fresh water balance beyond perhaps precipitation and snow water equivalent data would benefit from nga resources steward for airborne campaign when possible human water usage and infrastructure parameters used for modeling observations of water levels and storage declassified water data partnership to improve instruments or models changes in drinking water supplies mining impacts and impacts effects on communities nile river data uh data on local scale weather data to improve model accuracy discharge on the ganges underground structure i guess basically data from outside okay the last one uh what are examples of successful collaboration uh opportunities eight interagency international interdisciplinary etc what are the promising partnerships that could help advance our understanding uh success story of brazil building partnerships takes time ac wi israel usda relationships with jordan brit uh china and britain usgs collaboration with four countries to develop groundwater model nasa applied sciences programs nasa severe examples nsf infused signals and soil uh u.s nsf fire coast to people yes yes groundwater can be tied to these and usda funding proposals for pushing groundwater community to apply to afree and foundational any more comments so on number three what about i mean would the ability to actually gather metered irrigation data would that help of course absolutely so we haven't put that up there so irrigation i mean we obviously don't necessarily meter everything in the united states even but yeah certainly some places have meters where we could get that information yes uh under uh aquee there right at the bottom uh i would specifically mention the the national groundwater monitoring network okay it's a very specific um capability to share data um also the one that was it was mentioned earlier uh igrack international groundwater resource assessment i mean that's i think they're they've been successful in trying to pull together data satsa no they haven't okay so you don't think they're very successful okay okay if i may just for point of information um the survey has two two thrusts underway under way run right now one is the uh next generation water observing system effort so that's that's bringing new sensors to bear in c2 and remote sensing sensors to bear on water measurement and we're doing that through pilot watershed starting with the delaware and the reason i mention it is because we're also modernizing the national water information system to accept that sort of data so this question of how do you deal with imagery data you know we're deploying cameras at gauge sites to to do loss symmetry and stage measurements using artificial intelligence or we're deploying radar systems in the field on uas and so they're they're coming up with the standards that allow you include that sort of information into nwiss along with citizen science information and other pieces of information with appropriate uncertainty characterizations and attribution that allow you to sort through and use those data for appropriate uses so you know i think those are some examples within the us of the sort of technical things that need to be undertaken in order to create the sort of data repositories that we're talking about so i just thought i'd make make sure you all were aware of that carly do you have any more from on the uh okay um this it goes back to question three in terms of the data data that enhance the diagnosis and prognosis of surface water groundwater and land surface atmosphere interactions and design architectures for data collection and management this architecture will allow us to simplify the complexities of soil for example hydraulic conductivity and human systems like decision-making and governance thank you very much and thank you very much i think you guys are here till the bitter end here 230 so go ahead please get some cookies brownies