The Next Generation of Hydrography

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Topic: The Next Generation of Hydrography

Date: August 24, 2021

Presenters: Becci Anderson and Al Rea

The USGS is developing the 3D Hydrography Program (3DHP) as the surface water mapping component of the new 3D National Topography Model (3DNTM.) The 3DNTM is the next generation of the 3D Elevation Program (3DEP) and National Hydrography Datasets, and includes high-resolution elevation, inland bathymetry, hydrography derived from elevation, and connections to groundwater and engineered hydrologic systems. The 3DHP will provide critical data related to flood forecasting and response, agricultural planning, infrastructure design, fisheries and stream ecology research and management, water quality studies, and other emerging applications.

This presentation will provide an overview of 3DHP plans including scope and timelines for the emerging program.

Links:

  1. Kootenai River Topobathymetric Lidar Validation Survey Data - ScienceBase-Catalog
  2. Elevation-Derived Hydrography Specifications (usgs.gov)
  3. Probability of Streamflow Permanence (PROSPER) (usgs.gov)

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Date Taken:

Location Taken: US

Transcript

(Al Rea) 
This is the USGS Hydrography Community Call. Becci, Are you ready to share your screen and get started or? 

(Becci Anderson) So today Al and I are gonna talk about where we're going with our future in 3D. The 3D National Topography Model and the 3D Hydrography Program. We're really excited to be talking about this. We've been working for about the last nine months on a document encapsulating our ideas about where the National Hydrography data sets- kind of across the board are going. And, uh, it's it's been a lot of hard work and still in draft, but I think we've made a lot of progress and we're pretty excited about it and excited to share with you. So all of this for us starts with a new concept called the 3D National Topography Model, and this idea is really based in the fact that elevation shapes hydrography and hydrography shapes elevation. In that topography is defined by both of them. And a long time ago when when we were doing most of our primary mapping on topo maps, these two datasets, or these two pieces of information on the maps were much more integrated. They were more coincidently mapped, and as we moved to more digital products and GIS data, they started to diverge and now we are bringing them all back together again with this concept and. it's really key that these datasets fit together. The 3DNTM supports the 3D Nation vision of a continuous data surface from the depths of the oceans to the peaks of the mountains and 3D Nation is a concept that NOAA and USGS have been working on together, with NOAA focusing on ocean bathymetry and the USGS focusing on the terrestrial piece. These data will be foundational to initiatives like FEMA future flood risk data and risk rating 2.0, The national water model, Clean Water Act, the National Landslides Preparedness act. Also, we are focusing on how to provide the universal sharing of water information as a part of the Internet of water. Uh. We believe the 3DNTM will underpin a broad range of applications like flood risk management, hazards response and mitigation, infrastructure management, climate change science and many more. And we're also looking at enabling new and emerging applications like multiple vintages of change detection and water related applications where we're really moving from even the neighborhood kind of a level down to a street level because of the density, accuracy, and precision of these new data. There are four development tracks for 3DNTM. Uhm, topography. Within this context, UM. The I guess years ago we started focusing with 3DEP, 3D Elevation program, and The NHDPlus High Resolution on baseline datasets and so the first track is really focused on continuing with those until we complete them, and 3DEP has made a huge amount of progress on collecting lidar nationwide. The NHDPlusHR has been completed and a beta version for CONUS for the conterminous USA, and is in process in Alaska, and we're working on in CONUS Right now we're working on at the first update, I should say CONUS and the islands. Uhm. While we've been working on these baseline datasets were also working on piloting the integration of hydrography and elevation. So we're doing this both with deriving hydrography from elevation and really making the linkage between the hydrography data and elevation, but also looking at pilots for inland with imagery. And that is something the elevation group or 3DEP is focused more on. What we've started to work on now is designing and implementing the next generation of integrated data, and I'll talk more about that in a moment. Uhm, and the last track that we're really just dipping our toes into is researching and developing 3D data model. The question here is where can we go in the future with these two datasets? Where rather than or these two kind of large mapping programs where instead of having them separately but kind of integrated, we map them and keep them in a more common space, a more common model. We think you know this could really crack open and enable a huge number of new applications. So right now, while we're still working on completing the national baselines and piloting. What I'm going to talk about today is really focusing on calls for action for the 3DNTM in particular, the 3DNTM call for action, part one, 3D Hydrography Program. This document is currently in draft. We just are wrapping up the review with stakeholder groups for this document. Most of the reviews were back to back on the twentieth and the NHD WBD stewards reviews are due back on the 27th, so if you're in that group and you haven't sent them in, you have a couple more days. Uhm after that, we'll be working through all of those comments and then we'll have what we work through internally as a peer review. And then we'll go to publication at some point in the next couple of months. That's usually a long process at USGS, so I'm hoping this comes out of the goal is by the end of this calendar year. Might be just over into winter though of the next calendar year, but after we, you know, have focused on this. Call for Action part one. We are intending to do a Call for Action: Part Two that's looking at the next generation of 3DEP data, including elevation data collected at quality level at new quality levels, and integration with inland bathymetry. So why modernize NHD? Well, hydrography data are really essential to critical applications and we know through the hydrography and requirement Hydrography requirements and Benefits Study that was completed in twenty sixteen that the current program we work with with  1:24K  That provides about $538 Million  in annual benefits to users. But if we were to implement a modernized 3D enabled hydrography program. We're looking at over $1 billion dollars in annual benefits, so with the current NHD approach, we're really looking at collaborative data management, and this has been really successful. So the NHD portfolio of datasets, which is the most comprehensive and current data of the nation's surface waters, has over 9.4 million miles of stream network mapped in it, and eight million water bodies over 130,000 nested hydralogic. Units that is a whole lot of data and we couldn't map that data we we would never have at USGS. The local knowledge to understand it all. If we didn't leverage or stewardship program which there are MOUs with 41 States and Washington DC. Having those stewards working on the data, updating the data engaged with us is really the only way that we can know what's going on on the ground in these places. But taking that approach has led to updates that aren't uniform, and that's a problem going forward. So some of the areas have never been updated. UM, sometimes there are, you know, more than forty years old when you look at the line work that was taken from the original to, you know, taken originally from the total mass and has never been updated. This has led to national consistency decreasing overtime. Also, as we've worked with groups, we have kind of rough specifications and rules about the way that the data are mapped, but we haven't been particularly stringent with some of the information which has LED, for example, attributes needed to be filled in slightly differently and depending on who's doing the update. If you look nationally at them. They are not consistent. There's also issues with connectivity and the NHD network and some lingering delineation issues in the WBD and these data don't align well with new 3DEP data, and we're really in a time right now where. Because of computing power and just kind of national approaches within the federal government, we're kind of at a moment where we can start utilizing large national datasets for big benefit. For example, with the national water model. It's really important that we're able to feed the geospatial network into the national water model. That's consistent so that when there are actually running the national water model on the geospatial framework, they're getting consistent results back out and there's a lot of other applications that are similar to that. But hydrography derived from Malibu elevation, offers a solution to this problem, which is really fantastic 'cause we are also in a moment in time where we're really able to come. Harness the compute power again to derive these data in a larger way than you know was possible twenty years ago. So 3D H, P. The aim is to provide national consistency while still meeting local needs. We're going to focus on standardizing hydrography to align vertically, horizontally and temporally with three app data. We're focused on building an infrastructure using that standard hydrography as the geospatial base to support the Internet of water in the sharing of water information. We're looking with 3D HP to develop a modernized data model in schema that supports uses from all the way from cartography and GIS to hydrologic modeling. Uhm? We are looking to include enhanced connections to other datasets that also depict facets of the hydrologic cycle, such as wetlands, groundwater, and engineering hydrologic systems. We are. Proposing to do this through data acquisition, a process that follows through that best practices including coordinated governance with 3DEP. So not not just completely joining all of our working groups with governance, but how can we coordinate across better? And also continuing to have a strong stewardship program where we can get our stewards can provide local knowledge on attributes and flag issues on the geometry without having to have such a heavy lift of mapping every single line. When we looked at the program when we sat down over the last nine months and talked through this, we came up with three scenarios that you look at the hydrography requirements and benefits. Studies seem to emerge from all of the data and let me tell you, there is a lot of data in that study. So if we kind of started with completion of national coverage and looked at, you know how could that move forward source data accuracy, improved data model, major advantages and challenges of these different scenarios? The first scenario is just our status quo. What if we stop with one to twenty four thousand data and we continue to have stewards map it in the same way that we do with about plus or minus forty foot or or twelve meter accuracy? Same old data model. When we looked at that, it had the lowest cost, but there were major needs unmet like most of what we learned in herbs that were needs basically, and we continue to have inconsistency overtime. And it actually grows over time. It continues to grow over time. The annual benefits that were found in this program were about five hundred and fifty eight million. If we kind of kept doing what we were doing. Then we looked at two more future looking scenarios, one deriving the hydrography from one meter, Q L two or better elevation, and that's three depth data. Or deriving from point five meter Q L one or better elevation data. And in either case, if we have all of the base data that we need already available, it would be about a nine year program to do that work. With the one meter DMS, we looked at a program that was around two meter accuracy and with the point five we looked at about one meter accuracy. Scenario two meets most needs. And by most I mean really close to a lot of them. Scenario three meets pretty much every single need that was documented. Scenario two requires significant increased investment, and I'll talk about that in. I think it's the next slide or the one after. But the benefits are high for our users over a billion dollars. Scenario three had the highest cost and obviously source data is not widely available. While we have been building out a Q L two or better program with 3DEP for many years now. There are some areas with Q one or better data, but it is nowhere near the coverage that we would need to kick off this program at least immediately, and you don't get that much more benefit really when you look at them. So for that reason, we've chosen scenario two. And so everything else we're going to describe throughout the rest of the slides are going to be a description of basically supporting scenario two. So probable costs. These are still really rough. That's the first thing I'm going to say, but it looks like right now about six hundred and seventy six million over nine years. Well, that seems like a really outstanding number to me. If we're bringing a billion dollars in benefits. Every single year, it seems like a pretty good cost benefit analysis, at least in my opinion. Uhm? The curve that you see here, we kind of kick off the program and then you see a steady curve of data acquisition, and that's where the costs are increasing. Uhm, we kind of start to level off and then in these last couple of years we've collected the data and we're just processing it out. This kind of medium blue color is almost entirely data acquisition as well as inspection costs. The other costs you see here are. The some of the other features those other hydrologic cycle features connecting to those better is the lightest flu. This blue line here is taking care of this data and we see the legacy program tailing off in this dark blue where we work our way through the NHD and WBD, completing out and update of NHD plus HR. That's what we're hoping to do. A wonderful update and then kind of retire those out as we stand up these new datasets. So like 3DEP, though 3DHP really depends on significant investments by partner organizations. And I'll talk about that more in just a moment. So building out the 3D hydrography program. So we're going to talk now about building out the program, building out the datasets, and building out the infrastructure. So the 3D HP program kind of format or approach will follow three depth and a lot of different ways. We plan to establish three DHP governance to develop and coordinate. Partnerships in acquisition plans, they'll will be modeled on the good work that three DEP has done, and building out partnerships and and acquisition. We're working right now to add 3D H P to the three depth broad agency announcement, so we're doing basically the background paperwork to get be a broad agency announcement ready for the 3D hydrography program, although. Until we have funding to fund the broad agency announcement, which you know allows partnerships between the UM, USGS or the federal government, and pretty much any other entity out there, state, local, federal, tribal, private. Until we have funding for that we we won't be moving forward with it, but we're trying to get the paperwork done now so we're ready if we get money. Also, contract acquisition of 3D HP data. We are focused on that being primarily through USGS geospatial products and services contracts, but we'd also allow for cooperative data acquisition, contributed data, and we've already been doing a lot of work on providing specifications to support a program like this. But we have. We will have a lot more specifications to do, but the new LDH specifications that came out. Will provide the kind of base for this. So this is not a perfect UM description of what what will happen in every single year. There's been a lot of movement in in these different targets for the years as we've been working forward and outlining this plan. But just to give you kind of a taste of the things that are on the list at a high level so. As I've just talked about governance and communications are really starting to kick that off even in in this year, but especially starting in twenty two we've been working on pilots for hydrography, updated using elevation data, but we are also I should. I should fill this N W I one. I think now this national wetlands inventory. All the way back, maybe to even twenty one, because there is there will be a pilot project going on in Alaska I think at some point between NHD data or elevation derived hydrography and wetlands mapping and we're really excited to work on that. An NHDPlus HR production completing that out and finishing out Alaska. That's probably going to tail out a little longer to working through specifications. And be a process and really getting data acquisition going up and then also setting up and this is really key on our side on the USGS side of things. The operations, the operating operational plan. Setting up new systems and structures and schemas. In order to support this as well as doing research and then we've already started working on the three DHP infrastructure we previously been calling this the national hydrography and infrastructure and infrastructure is an information infrastructure in an hour. Will talk a little bit more about that. But we've already started working on that and will continue to work on it out over time. A little bit about the roles. UM again, this is kind of emergent, but just to give you a feel for the fact that you know this is not something that USG has seized us. Going alone, federal partnership state and local partners, private sector and users are all going to be really important in this process. And in this program, whether it be, you know, the program itself or governance. Uh, the specifications stewardship applications. It's all really critical that this be a diverse program. Alright, I'm going to hand it over to Al now. 

(Al Rea) OK, uhm, I think we'll take just a short break 'cause we're seeing some questions in the in the chat and talk a little bit about those while there still hot here. I saw a couple or 3 messages about bathymetry. And we we didn't spend a lot of time talking about this, but that is part of the program. There has been a bunch of work going on with regard to bathymetry in the in the coastal zone. There's for quite a few years there's been work going on collecting the bathymetry data right along the coast, and that's been, there's been a program called CoNED which I don't know what the acronym stands for, but is basically combination of that bathymetry data with the 3D elevation program's elevation data for the to the terrestrial uh, you know strip right along the coast. And part of this whole concept of the 3DNTM or the national  topographic model is  to also starting including inland bathymetry as well. Uhm, that's that's a little farther out in the development then the rest of the stuff we're going to talk about today. It is in the plan. It's part of the 3D nation. Uh, the the next sort of next generation for the 3DEP program. The 3D elevation program. Uhm, and so it's going to. It's going to be coming along, but it's not, it's not part of what we're talking about. Very. It's not a big part of what we're talking about with the 3D Hydro Program. We definitely are interested in anyone who is collecting bathymetry data, and we'd like to see if we can get that data and begin merging it, integrating it with the elevation data. We've done a number of pilots across The country and several different types of terrain with inland bathymetry and there's, I think the one that's been published so far. There's one in Kootenai River in north Idaho, and I'll see if I can find the will try and get you a link to that one. That's probably the most developed. Uh, one where we've taken the the terrain, topography, and integrated that with the bathymetry of the river and created a single surface and published that. So that's kind of it's it's still sort of developmental and research and we're going to be working on that more going forward. But I did want to mention that and please contact us if you got information and data like that. Bathymetry data or you're planning to collect that data. We do have specifications, or there's some information about collecting the bathymetry in the lidar base specifications that USGS uses for acquiring lidar data. So if you're if you're considering collecting bathmetry with lidar and than those specifications would be something you'd want to look at. OK, So let's talk a little bit about the data talking about developing under the 3D hydrography program so. It's very similar to the data that we have now, but it's not exactly the same. So you will have the stream network and waterbodies just like the NHD does. It will all be derived from elevation data, at least quality level 2, 1 meter resolution lidar data for everywhere except Alaska. and the IfSAR 5 meter data in Alaska, at least. In some areas it's going to be better quality than than QL2 LIDAR. You know, it just depends on what's available in those areas. but the the idea is that we want the hydrography to be derived from the elevation so that they are completely Insync with one another. So we we want to have a completely integrated data set at where there's you know you don't have these differences between the elevation data and hydrography data. So right now you know, we don't have that right now Our hydrography is mostly dating back to the original topo maps, which were done in mostly in the 1970's and 1980's. So there's a big time difference between the hydrography data that we have in the NHD for the most part and the newer lidar data that's coming into into the shop here with the 3DEP program. So that's a big part of what we want to do. Is is really a temporal update as well as while we're at it much, much higher resolution of representing those waterbodies, streams and so forth. in in the data. Uhm? We're we're going to have hydrologic units similar to the WBD and we will have catchments just like NHDPlus. We are hoping to design this so that the hydrologic units will nest, will be nested catchments so that you can essentially take a collection of catchments. Aggregate them together, dissolved the lines between them and say that's a hydrologic unit. Right now we have differences between the way that WBD is delineated and the way that NHD is delineated. Uhm, such  there are some automatic conflicts between the the two datasets, uh, in in that their delineation rules are different, so we need to resolve those conflicts between how that's done and come up with a new method to get hydrologic units. Those hydrologic units, I would say we don't have complete concept yet on what those are going to look like. If we're going to keep the old HUC codes, or if we may sort of archive those, it's yet to be determined. But we do want to make sure that they can be readily aggregated from catchments based on the hydrography and consistent with all of the hydrography and and. As a result of that, they're consistent with the elevation data as well. Uhm? So we have raster Data as well as part of this, so a hydro conditioned digital elevation model, you know. With all of the culverts cleared, dams kind of broken through, such that you can create flow direction info accumulation directly from that. DEMs and those flow direction flow cumulation rasters as well. As you know some other rasters very very similar to what we have with NHDPlus would be included in the 3DHP data. The difference here with the rasters and and all of these datasets. Is that it's all one big data set, it's not. We had the NHD then we have the NHDPlus that was built from it. You know, built from a snapshot of it or something like that. We want to we want these things to all be integrated. And ideally we want them to be updated together such that there isn't a big time lag between. When NHD is updated and went in NHDPlus gets updated like we have right now, we have quite a time lag involved there. So on the attributes side basically we want to preserve most of the Functional attributes that we have within NHD, WBD, and the NHDPlus HR. We may add some additional attributes but we're also looking to sort of streamline the data model so we may have to make some hard choices about attributes. That, you know we need attributes that we can be able to reliably populate from the data that we have, so we may have to make some choices about how we get those attributes, or some attributes may fall off the table in that process. Would definitely be looking for feedback on that, as we're doing that Modernization of the data model. UM, I'll talk a little bit. I think I have a slide about data model. A little bit later where we'll talk a little more about the modernizing the data model, but I think I think you all probably recognize that our current NHD data model is a bit long in the tooth.  it was designed back in the early 2000's based on software that was available then. And you know it can be improved, so we're going to be working on that improving that. So let's go to the next slide. Uhm? So here are some of the things that we wanted to improve or enhance in terms of the data. Actually, I forgot to mention on the last slide and really emphasized was Z values on everything. These are true 3D datasets. All of the data that we're going to have in this 3DHP data will be true 3D data. Yeah, as you may know the NHD has had a Z value coordinate capability in its data model from the very beginning from many many years ago, but it hasn't been populated. Actually, we've started populating the Z values on the NHD. And some of the new, the very newest data that's been added to the NHD in Alaska has that z-value on it now in the NHD. So, uhm. Again, we're talking here about the 3D Hydro Program data, which are going to be. You know, probably won't be called NHD. Maybe it will, but it it may be called something a little bit different in the future. Uh. All of them are going to be three dimensional databases. Three dimensional vector datasets with accompanying rasters. Uhm, we want to be, We wanna get a better handle on connections with groundwater. You know, surface water/ Groundwater interactions are very important, and it's something that we've been essentially ignoring in the development of our geospatial datasets. For hydro, we focused really almost exclusively on the surface water, and aside from springs and a few sinks that that are identified in the NHD. We don't really cover any kind of interaction with groundwater. so we want to research that and understand better how that can be done. We have some pretty good ideas, we think of how that can be done and will need to work with the groundwater modeling community and so forth on trying to figure that out better. This is this is a concept right now. Really it's kind of an aspiration. We don't have full details on how this is going to happen. Uh, we've been talking a lot lately with the National Wetlands inventory folks over at Fish and Wildlife to understand that's a US Fish and Wildlife Service to try to understand how we can improve the interoperability of those data sets together the NWI, the National Wetlands inventory and the NHD have a lot of very closely related information. They have a lot of features that are really common between the two data sets, and so we are trying to understand and build a future vision that will be much clear delineation between the two datasets you know defining exactly how, what features belong in which dataset and if there are common features. How do we make sure that they have the same geometry represented in both datasets? So we're we're talking a lot with the with the folks at the National Wetlands inventory and trying to make sure that we could integrate those databases. Uhm? Engineered hydrologic systems, if you're familiar with NHD in urban areas, quite often it looks like there is a desert in an urban area. That's because in the mapping again, going back to that, topomaps when streams enter urban areas, quite often they go underground, they go into a storm sewer system, and except for the very largest streams, a lot of times you lose, you lose track of them because they go underground and you don't know where they are. Uhm, or at least, our cartographers, who were looking at aerial photography, couldn't see where those things went and so they stop mapping it. Uhm? We need to try to include, connections through those built up areas such that we know how the water gets through there. But there's a whole lot of detail in in storm sewer systems in cities that is going to be kind of overwhelming, so we're trying to kind of find that happy medium of where we, What how much detail Do we need to include in Uhm, in an urban area of the storm sewers and how can we get that information brought into NHD in a way that's useful for applications that are not focused strictly just on that urban area, but on whole watersheds and so forth so. There's some research that needs to happen there. We have some examples of. Like for example, the Washington D.C. Metro area was recently brought in the storm system there storm sewer system. There was brought into the NHD. You know they did some. You know they chose. They made some choices as to how much detail to bring in. It's not the entire system, it's a subset of the entire of that entire system. But we need to kind of look at that and see does that mean our needs? Does that meet the the Community needs as as a whole, and if so, how would we implement that with who knows how many metro areas around the country we would have to work with? That's that's a major challenge there, so a big. Uhm? You know potentially big big effort there, and we've got to try to match that with whatever resources were going to get in this effort. And then finally, interoperability. Basically, this is just the the concept that we want to make these data. We we recognize people use hydrography data, not in a vacuum. There using it with all sorts of other data sets like geology, soils, so on and so on and so on and. All of our data needs to be. staged in a way that's easy to use. A would like to get away from the idea that in order to use the data you have to go find it for. You'll find what HUC you need and download that data to your system and work on it there. You know we need to make these systems so that it's it's very, very transparent. Such that, uh? People can find it use it without having to know a whole lot about the underlying structure of the data and how it's stored in tiles and that sort of thing, but also so that machines can find the data so that the data is described in ontologies in ways such that you know machine. This artificial intelligence type systems can actually say hey, I have this kind of a problem. I need to find how the water gets from point A to point B. I need to find some something that maps the hydrography. Between those points and it would find us, it would find our data, it would it would find the data that it needs through those kind of. A very kind of community oriented, UM. Community agreed upon semantics. Uhm, what definitions of what's in these data. so this 3DHP infrastructure, This is something we're working on right now. We've been. We've been working on this quite a bit. The idea of how do you, How do you reference data to the hydro hydrographic network? How do you use that? I mean, we've used linear referencing in NHD from the very beginning. Many people are building datasets and have built over time, built many, many, many datasets that use reach codes and measures. So this is sort of formalizing that into a system that is very web oriented where you know. There in the center of that center bottom, we have the hydrographic framework that's our datasets. You know NHD, NHDPlus HR. Eventually the 3DHP data will be that foundation. We have tools for hydrographic, addressing over there to the left. Those are tools you're probably familiar with. Some of you at least have used the hem tool. We have a new web based tool that we're hoping to roll out here in the next few months. Called HydroAD for which stands for addressing. We've we've decided that events are a little. It's a little too much jargon. People sort of understand if we say we're we're trying to find the hydrographic address of this point on the network. And so we're we're using the term addressing there. Up in the top, across the top there that's you all out there you have data that you have that should be referenced in some way or another to the hydrographic network. We were building and we have specifications on how you should publish your data as a web feature service. There's just a set of fields that you need to include, and there can be integrated into the system and then finally, we're developing these catalog search and discovery tools that will let us let people find data that they're looking for. So this this whole kind of infrastructure is being formalized and it will provide really the geospatial underpinning of something called the Internet of Water, which is an evolving concept that is kind of getting going now. It's led out of Duke University. Alright, just a again. This is just a review. I've sort of covered all of this mostly so we we've got the stream network. Catchments, hydrologic units that are aggregates of the catchments. All attributes, uh, I think we've mostly covered, uh, these these concepts here, but just kind of reinforcing. this is all one, Kind of complete data structure. It's not a bunch of separate products like in NHD, WBD, NHDPlus so on. It's it's all one big thing. And it's all three dimensional. Uhm, some of the attributes that we want to cover. Again, uh, we wanna keep these kind of attributes that we have in the NHDPlus. We have these navigation attributes like 'from-node-to-node', hydro sequence, level paths, all of that. We have all these other things like stream order, and so on we have. Modeled run off and we have basically modeled flows through the EROM process. We would we would want to continue doing that sort of thing and additional models based off of the data, one that's a high interest is something called PROSPER, which is a model of Stream flow permanence, whether or not a stream dries up. Basically it can give you it's a probabilistic model for weather that stream is going to dry up in a particular year or not. Uhm, and ah, so that's one that's a strong interest, I think to try to run that nationally, and it would all be based off of this kind of data. These raster surfaces, basically these are the ones that we have in the NHDPlus right now. They would They would, I think all pretty much applied to the 3DHP. We would not do quite the same type of process that we do with the NHDPlus lists like burning in the streams into the DEM surface like we do. Because the the streams are derived from the DEM surface we'll have will have a much lower amount of burning, having to having to go on, and basically that would be more or less confined, confined to things like culverts and dams to to clear obstacles like that. To touch just briefly on some of the research. Uhm, uhm? You know some some things that we need to research. the data model we we would like to try to include a way to use linked open data. This is something that the Canadians are doing right now with their new data model. They're developing a new hydrography data model for Canada. We've been talking quite a lot with them trying to learn from what they're doing. They're a little bit ahead of us on the design. The Australians have some interesting concepts that they've been working with, similar in a lot of ways to what the Canadians have been doing. All of that is based on an OGC standard called the high features 'HY features' Standard that it came out of the OGC a few years ago I think about three or three years ago or so now. We also you know we want to look at how do we bridge from our current data sets to the future datasets? How do we identify common tie points or common segments between network segments between those datasets? Some sort of cross tabulations or cross table crosswalk tables between them, that sort of thing? There's there's a need for research of that. Also, we want to really focus on kind of building these data pipelines. How do we flow data through Some more or less completely automated processes to update and improve the data as we are working through there so that you know things are being Acquired and updated you know in near nearly real time. And uhm, tyed in with all those models as well in in nearly real time. Uh, we we still we have generalization and multiscale. We want to we want to be able to take this very, very detailed information and generalize it such that it can be used at different scales where people don't. For applications with where people don't really need the level of detail that's in this data, that's that's going to be very important. But trying to make sure that everything is still off based off of a common base of the most detailed data. That we have. And then, finally, uh, you know, we we want to be looking at using AI artificial intelligence on high performance computing type platforms that we have available to us to see, you know, can we automate some of this process is that we currently do by hand, which is, you know, identifying where are the culverts? That sort of thing. So. Uh, that's that's the uh, sort of a hint at some of the  next things that we want to do. so Basically what what happens next up first is completing that call for action that Becci described earlier. That's going to happen this Fall and Winter, probably into next Winter sometime, though that should be published as as Becci mentioned, we're getting feedback from stakeholders on that right now. We plan to update the draft and then run it through our publications process, which which takes some time. Uhm, we want to... Then we'll be doing a lot of outreach trying to educate and build support with all partners and users. Uh, we have already started doing some pilot projects, deriving hydro features from elevation. We didn't have a chance to talk about that, but last month we got to see a lot of that from Alaska. If you didn't catch this call last month and you can go back on our YouTube channel and check that out. Because we've, we've done quite a bit of work in Alaska along these lines. Uhm? Then there's this. We have to develop an acquisition plan, including that BAA, which, if you're not familiar with that, that's the way that the 3DEP program has been working with this be a process which basically lets them let's projects compete with other projects for matching funds. In other words, in Something that's easy to understand from USGS to get to get funding to produce the data to go acquire the data. Uhm, and then, uh, you know, building out some prototypes, we were going to start trying to build out some prototypes  of all of this stuff here in the next few months really and start researching a new data model. All of that stuff. We're we're really hoping to work on over the next several months and years. So that really is what we had. 

(Becci Anderson) 

Uh, so next month is going to be Al presenting on his reflections on 34 years of GIS for water resources science at USGS, because Al would you like to tell the group while you're doing that presentation? 

(Al Rea) Uh, well, yes. So I am reaching that age and I'm going to retire So at the end of next month and so that will be my last hurrah here and just. Yeah, just a preview that slide there. That is not "the" computer that I worked on when I first started with USGS, but it's it is one like the one that I did and those are. Those uhm short. boxes there that look like about the size of a washing machine. Those were 300 megabyte hard drives, so that's that's the preview of next month. I'm not going to talk all about old the old days though. 

(Becci Anderson) Well, we'll come back and answer, just spend just 5 or 10 minutes going through the answers to some of these questions and then come and celebrate Al's lengthy and wonderful career with us. We're so so sad - I especially so sad to see Al go. But come and celebrate Al's predictions for the future and is reminiscing of the past as well.