 Good morning, good afternoon and good evening to all of you who are joining us today for the first observation or the management community of practice meeting. Today we're going to be discussing three different perspectives on understanding different types and applications of earth observation data. This meeting today, it will be recorded and made available on demand on the IWA website, so after this meeting you will receive a link to this recording as well as the presentations. Below in the chat box you can use this for general requests and for interactive activities like introducing yourself and maybe mentioning your line of work and maybe the sector that you're working. And you could also use it to chat with your other with the other meeting attendees just to see you know, maybe you meet somebody that you've worked with before on a project or so next question next slide sorry. So just a bit of background about this community of practice so IWAs work on earth observation for water management is a result of successful partnerships and collaborations. We are a part of the consortium of the European project Primwater which looks at earth observation technologies for better water management. In Primwater, IWA is responsible for communication, dissemination and exploitation of Primwater products and end users engagement. Primwater is also represented in the steering group of this community of practice. We also have an memorandum of understanding with geo act watch, which aims to enable water professionals to access and share information on the application of earth observation of earth observation information and technologies for improved water management. Both IWA and Primwater are represented in the aqua steering committee and working group one, which is focused mainly on outreach and user engagement. Primwater and aqua watch also collaborate in promoting their activities within their respective networks. So to give a bit more introduction into this community of practice, I'm going to hand over to my colleague Lars, who is a member of the steering committee to give you some more background. Thank you very much, Erin, and good morning, good afternoon, good evening to all of you wherever you are. My name is Lars Boyer Hansen. I'm with the International Consultancy Company, DHI. And on behalf of the steering group of this community of practice, I'm very happy to bid you all welcome to this first meeting. We have a very exciting agenda ahead of us. Right after this introduction, we'll have three presentations. The first one given by Tapas Biswas will be on development of an EU based optimal integrated water quality monitoring and forecasting system for inland and coastal waters. That will be followed by a talk on water assessment using earth observation given by Kenneth Mubir. And then lastly, we'll have a presentation by Lisa Maria Rebello on earth observations for sustainable water resource management. After these three presentations, there'll be a Q&A round. And then we'll break out into separate rooms where we can initiate in hopefully a lively discussion and sharing of opinions and continue the Q&A session. Followed by that, we will convene again and summarize the breakout room discussions and then finally close the meeting. So what exactly is this community of practice? It's called earth observation technologies for water management and the overall idea is to bring together experts across different sectors with different backgrounds. But all sharing a common interest in how we can use earth observation technologies to improve our knowledge about water quality and water quantity management. The CUP is connected to the IWA digital water program also where we have a platform to share experience and connect with peers and strengthen the transition on how we can digitize water solutions and underpin the digital transformation within the water sector. And of course the sort of hope with these CUP is that well we can both increase the awareness within IWA but also beyond IWA on all the potential that lies in using earth observation technology for water management. IWA is already acknowledged with the platform for a means of sharing and showcasing ideas and best practices within this. And here we get a chance to engage more and have more focused dialogue on this topic. And specifically for this meeting, the idea is to discover concrete examples of where we are using earth observation and concrete applications on how earth observation can help us in the management of our water resources across themes and domains really. And of course this is, it gives in the name community of practice so we very much hope that you will all take active part in the discussions, both in breakout rooms, but also in the chat. This is all about sharing experiences, raising questions so we can have this lively dialogue. That was the very quick fly in. And with that, I will be happy to pass the word to Catherine who will introduce the three speakers. Great. Thank you. Thank you, Lars. So just I'll introduce myself. I'm Catherine Cross. I used to work for IWA, leading on the strategic programs but now work for them as a consultant and also for a number of other organizations including Australian water partnership and IUCN and it's really exciting to see this community of practice evolving and coming to fruition so it's very exciting to have this meeting today. Our first speaker now will be Dr Kenneth Mubia who is the user engagement manager for Digital Earth Africa establishment team. His role includes technical support and user engagement and support, driving usage of the Digital Earth Africa services and engaging with the Digital Earth Africa network of partners across the continent. He says that a time has come that Earth observation is going to be critical for decision making for countries and regional bodies in Africa towards sustainable management of resources so very much looking forward to your presentation Kenneth on understanding different types and applications of Earth observation data. Thanks so much Catherine. Good morning or good afternoon depending on where you're calling from. Welcome to this important workshop from Digital Earth Africa is many greetings, and also showcasing what is available. This platform is here for us in the context of Africa providing almost three terabytes of analysis ready data from open sources Lancet and Sentinel, and we've been working previously using a pilot program for five countries, which was a way back in team, and it has grown now into Digital Earth Africa for the whole continent. So with this analysis ready data, I received a request for many countries of what they wanted to see as continental products. The first one was the world observation from space, which we go developed with our partners in Africa, from partners in Tunisia, Senegal, Niger, Nigeria, and southern countries. And this program actually soon will be hosted by the South African Space Agency just to give a context of our viewers from different parts of the world. So most of the resource research questions that we are addressing is that of national development agendas, including supporting SDGs, SDG to and more specifically for this audience SDG six, in terms of what extent and what a quality and as well would be presented by my colleague type as from CSIRO. So the world observation from space was developed based on that interest, and it's a 30 meter product at the moment, providing way back up to 1980 to see how the continents change in terms of water variability. And we've had actually very interesting use cases based on the researchers from different parts, especially researchers like from Mogavango in Botswana, we have seen the value, for example, the lake in Garmin which has really changed over time. So this is also similar with what people are seeing across the parts of the world. And this is due to climate change and other parts which are beyond our control. So, more specifically of a use case which demonstrates the value of this earth observation data for development, and in the context of water resources for some work in Mogavango, where we worked with Dr. Kilebuki who's a researcher at the University of Botswana, and she mentioned about some areas where she could not be able to get data for like having historical background, since she's able to do more field work and she's been talking to the farmers around who've told her stories which she's not able to quantify, but using earth observation, for example, context of three years we're able to see quite some change, and even this documentary was recently aired by Alzar Zera in Risking It All where they were actually showing how farmers have really, the bushmen have really encountered problems, the lake at the moment is almost muddy, then we have periods when like next year in between the year to be like floods and droughts. So using this to serve those decisions and being part of an integrated water management system is what is really impactful for users across the continent and also learning from other parts of the world. So we also have other examples like in Tanzania, where we're looking at Lake Sulunga, its changes over time, working with the National Bureau of Statistics in Tanzania, and also we worked also with the regional center for mapping and the Kenya Space Agency providing some context of what happened in Lake Baringo, looking at the water extent as well as the water quality from the Sentinel-2. So all this is just from open data, showing the value of what we can actually provide to the end users to provide for decision making. So in the context of the same, we were able to provide support for Lake Baringo, where we had to re-home the giraffes in the middle of Lake Baringo because of lack of pasture. The lake sometimes dries up, sometimes there are occasional floods, and you can see the context of how we can touch their lives, even of their wildlife in terms of conservation, and this was a very good use case, supporting the conservation agencies in the parts of Africa. And also the material from Digital Africa is available for us to make use of free online resources, and also we run lively sessions every Wednesday to keep in touch with our users from the context of Africa. And we are able to communicate in both English and French so that we leave no one behind in this continent. Thank you so much, our viewers. Thank you very much, Kenneth, and yeah, thank you for your presentation. It gives a good overview of the different possibilities that are available with using Earth observation. So we're now going to move to Tapas, I believe. So Tapas Iswas, he was the senior research consultant at the Commonwealth Scientific and Industrial Research Organization, CSIRO, in Australia. He's been involved with natural resources management, water quality, irrigation and climate change research, consultancy, teaching and policy in Australia, and overseas for more than 33 years. He's also a member of the steering committee of this community of practice. So he's going to talk about the development of Earth observation based optimal integrated water quality monitoring and forecasting system for inland and coastal waters. So I will hand over you to you, Tapas, thank you. My topic today aligns very well with the objective of today's meeting and before I start I would like to acknowledge the Australia's first nation people whose lands and water we do our business and I pay my respect to their elders past, present and energy. So to start the context, you know that United Nations Sustainable Development Goal requires provision of clean water under a goal six. Management of water resource is a critical issue for all of Australia, particularly for its agriculture environment and communities. We have a few mega events, for example, fish scales, et cetera, in, in our rivers, as well as in coastal areas, therefore the water quality impacts are of paramount importance. The quantity of available water resources across Australia is monitored through both federal and state programs. However, when it comes to quality, we don't have a single common and comprehensive state program, a national system that delivers timely systematic information such as early warnings to what agencies local communities and commercial water users is to help decision makers to better manage ecosystem health support industry and prevent human or animal health risk. Existing art observation satellites, both the one that are up in the sky or are in the preparation, do not have the requirement particularly for water quality, this is because the current and the plant satellites designed for either ocean, land or atmosphere application and lack the required spatial, spectral and radiometric as well as temporal resolution, for example, our inland river and lakes are mainly small and narrow. Hence the need for an aqua watch mission. The goal is to build a comprehensive national system for 24 seven monitoring and forecasting of water quality from sky and how we will do that will combine the Institute sensor network, satellite data bio hydrologic modeling and advanced analytics to achieve our mission's goal. Here is a kind of cartoon of the system of the technology that the aqua watch Australia mission wants to put together for monitoring both inland and coastal water quality. Starting from denser network of sensor, complimenting existing network that have been run by the state agencies will be adding additional sensors, and then we'll use IOT kind of things to relay the data. And then complimented with the customized Australian satellites aqua set one and two that you can see where my mouse is there. The whole mission is underpinned by rigorous science and in that space we have sensor technologies working in parallel with the satellite design will be using in situ sensor and satellite data integrate them through the aqua watch data integration analytic system platform, which is got both artificial intelligence and special analytics platform that will help us give improved early warning, a remote quantification of species which is not possible by any satellite at this moment of time, and other water quality parameters for example black water, turbidity, etc. So here is an example of an in situ camera that CSIRO my agency organization have developed and this camera has high resolution spectral signature. Reading at every 15 minutes time, so real time data and that when analyzed properly can give you idea of suspended solids, chlorophyll, cyanobacterial pigments and dissolved organic carbon. However, to analyze we need long term deployment to relate in lake water quality parameters to the spectral resolution and then the unique thing in this mission is calibration of the satellite data with real time in situ high resolution time series data that will be collected using on ground sensor. So the total machine is kind of the central one, which is the ideas sort of thing that takes into data from both in situ and satellite, and then turn it with the models. And then at the end of the day, it gives you an algal forecast, both for alert level, as well as early warning. Here is an example of Lake Hum, but I have taken the turbidity as an example. However, we can do the same thing for blue green algae. Everything is important to do a research without having proper collaborators and stakeholders. Here is an example. We have stakeholders and our collaborators at our field site, Lake Tuggernaug in Canberra, Australia. So the benefit are triple bottom line and you can see, once the system is in operational, it will give us economic environmental and social benefit in due course of time. So for over a year, we have spent in developing good understanding of user communities and today is one of them for the system. Here is a list of potential customers. You can see it's spread from local state, national water agency to all the way to tourism and fisheries sector, because it will cover a number of spectral characteristics. This could not only be used for water quality operation for recreation, but also over a variety of parties, those are interested in this water quality monitoring. Of course, it will also help grow Australian space industry, including new business on satellite manufacturing, IoT, ground station, data processing, and so on and so forth. So, where are we today in terms of mission roadmap? The mission itself is at its very early stage and you can see the red dot, red circle where we are today. It is scheduled for official launch this year, middle of this year, and we're hoping in June, part of the plan is now to build number of test sites to test the whole system. And on the top of the arrow and at the bottom of the arrow, you can see list of pilot projects that we will be building very soon. Some of our already built and some will be built sooner. Bottom arrow is all about the satellite precursor. So there will be first satellite that will go 2028, Aquaset 1 followed by Aquaset 2 and then Aquaset 3. Here is the list of those pilots, domestic one, Australian one, we are working closely with number of agencies, and they have different need for this monitoring. And you can see here on the right map how they are spaced across the whole continent. Similarly, here are the international pilot projects both ongoing and upcoming. And you can see they are mostly in Asia and America where algal blooms are common nuisance. Well, we are working with a fairly large number of parties, and I acknowledge them. I also acknowledge IWA for having me today here. And with this, I thank you and conclude my talk. Thank you very much, Tapas. And it's very interesting to see how these approaches are evolving and how they are going to plan to be used in different places across the world. So looking forward to learning more during the discussion. So our next, I'll move on to our next presentation. So our speaker is Dr. Lisa Maria Rebello, who is a principal scientist in Earth observation at the International Water Management Institute in me with 20 years of research experience across African Asia focusing on the provision of spatial information metrics and indicators to inform land and water management systems. Lisa is also the vice chair of the scientific and technical review panel for the Rams of Convention on wetlands and coordinator of the wetland theme of the Japanese aerospace exploration agencies Kyoto and carbon initiative. So she's going to be talking about earth observations for sustainable water resources management over to you Lisa. Thank you, Catherine. So, and the research that the team, and I undertake it in me focuses very much on addressing key water related information gaps that can be assessed through the year through the use of a variety of earth observation data. So we work across Africa, the MENA region and Asia but I'm going to focus today on an application, which we're developing across the African continent, which builds very much on the presentation of Kenneth and the digital earth Africa resource. While there's a huge variability in the water related issues across the continent. There are a few broadly shared challenges that need better data. And these are summarized here on the slide that you can see. And so our focus is on a few critical underlying challenges that are essential to socio economic development and resilience across the continent that are widespread so they affect multiple countries, where there are significant data gaps, and in particular data gaps which can be addressed through the use of earth observation data, and which would benefit from regional or larger scale approaches. So these are broadly summarized on the left. So we have water scarcity in sufficient water to meet growing and changing needs. We have variability where natural variation is being exacerbated by climate change and other development related challenges. We have water quality issues where water quality is degrading. And then we have productivity issues, where we need to look at how we can get more from the available water. And against all of this, looking at the larger scale and water resources we obviously have the challenge that water resources are often trans boundary in nature so they cut across international borders. It's even more challenging to address some of these issues due to this trans boundary nature. But this is really where earth observation has a huge potential as unlike the in situ and hydromet data availability accessibility and quality and not defined by international borders by national borders. Next slide please. So this in mind, it means been working over the past few years with our partners to develop an earth observation based water accounting framework and application. And this is what you have summarized on the slide in front of you, so this is very much an integrated approach taking many different data sources and trying to put them all together to look at essentially producing what's coming into his water account so water accounts can be thought of similar to a financial account we're trying to summarize what's coming into the system and what are the resources that are coming into the system. How are they being used, once they're in that system so in this case within a river basin, who are the main users and how much is left on an on a certain accounting basis within that domain. We address this through those three main components that you can see. We look at how to integrate data from earth observation satellites. We then put this through various modeling frameworks and finally we output a series of water accounts which summarize a higher level of indicators related to water use, water availability, water that's available for further use within that spatial domain in case they're in a river basin. Next slide please. So looking in a bit more detail at the process. If we start on the right hand side, the approach we would we're doing it, it's very demand driven so it will start with the areas where we have requests for information, the types of decisions where we know we can influence the use of earth observation, where there are currently gaps and where we know the data will be of benefit. So these are related to, for example, the water data, the water data system. So, if you think about your river basin, it's essentially your water balance how much water is in the system. The second one related to water allocation issues. How do we identify how much water is available for further use and how do we do that in a sustainable way. So looking at how much water there is how much is being used, including by the environment for environmental flows how much is committed to downstream uses, which enables us to look at that broader water allocation aspect. So if we're planning, if in a particular basin we're looking at a large scale irrigation investment or a dam or a reservoir, what are the implications likely to be. And finally on system level water productivity. So when we look at the system as a whole how do changes in use and availability of water in one place affect productivity in another place. So we're going to bring in mind those four application and those four areas of questions and applications, which link of course back to the ones we looked at initially around variability scarcity productivity and quality. We then defined this water accounting system. So on the left, you have the data inputs and this is just a selection we use between 20 and 30 different data sets as inputs from global databases. We also have a series of earth observation based data linked to the water flows and fluxes. The obvious ones the precipitation, soil moisture derived ones about the transpiration base flow to run off ratio, but then also linked to quality great water consumption, as well as to large scale ground water changes. We also have a series of data sets, which are key inputs, which related to the landscape conditions because the key aspect of this approach is that we're looking at water use across the entire landscape. So that's related to vegetation, for example, but also then to environmental flows. So the sustainability of the system. Coming back to the point I made earlier. And the key thing about this approach is that because we're using global databases, this is using the same input data for every location. So it doesn't change across international borders which means we can, we can apply the same approach and derive the same indicators on a regular and consistent basis for every location that we're working. Additionally, when we look at other water accounting approaches based on national level statistics or hydrological models, you can do or constrained across borders. So these data integrated into the middle sections, which is the analysis modeling framework, and this is open source, all of the data open access the the modeling tools are open source, and currently we're building it in parallel to the African framework and architecture on Amazon web services hosted in Cape Town. So everything is publicly available there. And then we have a series of outputs, some of which are statistical, some of which are the indicators these produced on a seasonal and annual basis and summarized through a series of water accounts. Next slide please. But because the data are spatial, even though the water accounts summarized for a basin or sub-basin or a catchment on an annual and seasonal scale, we can also view the data spatially. So we derive pixel based water balance across the entire landscape. So this is just to give you an example for a particular use case, a bit one particular river basin. Well, what we have on the left is a summary of the mean annual water balance and on the right, we have a summary of the mean dry season, the key parameters, key water balance parameters. So if you look on the left, we have summarized the amount of rainfall this entering the system that's the blue arrow, the P, so you can see what's coming in in terms of the volume, and on the bottom left you have the outflow so what leaves the system. And then in between we can look at how much water is actually being consumed, how much of that water that comes in is being used, and we partition that into the source of the water. So whether that's blue water sources, so from rain from rain, sorry, from surface water, or is it from additional water sources and incremental source of water. So we split it into green and blue evaporation processes. So that enables us to look at where the irrigation what's been consumed through processes such as irrigation what's been consumed through for example landscape processes. And then we do on the same on the right for the dry season. This is an annual dry season. Sorry I should have said over a 10 year period so both of these mean annual and mean dry season over a 10 year period, the recent 10 years 2010 to 2021. So that enables you to look at what is the average conditions in the dry season as well. And then I have two parameters on the slide, which go one step further, and are taken from the water accounts which is the total available resource so what is actually available for use within the basin and what is utilizable so that utilizable parameter is a very important one in the water accounts, because what it refers to is the quantity the volume of water which is available for further use. So once we've taken into account all of the existing uses within the basin and the environmental flows and any downstream commitments, so that utilizable indicator shows you how much water is available for further application for the allocation for the development within the basin So if you were to see for this particular basin, you would have there's a small portion available on average on an annual basis, and then even small even smaller portion during the dry season. So in terms of looking at sustainable development strategies around groundwater resources management, something needs to change for this particular base. So I think that's it my slides I just want to finish by saying where we're going next with this process. We need to move from that single base and case study to making it more operational. And we're doing that by building on existing platforms such as digital earth Africa, where we can ingest data, data sources from different locations along with the analysis ready data that already exists, and build this at the continental scale, so that we can provide this level of information on the water accounts for anywhere on the African continent. So I'll stop there and turn back to Catherine. I actually said it was really interesting to see how this. This can be applied and I can see how the visualization and the information would be essential and very useful for for basin planning processes. As you mentioned, especially at the trans boundary level. So if you have a few questions and please continue to put your, your questions in the chat so the first question we have is for tapas from Arjun. He's asking, can this technology indicate precise levels of organic and inorganic contaminants at micrograms per leach and does it identify any microbial contaminants contaminants or is it restricted to only a few so tapas. Can you please answer that question. Yes, I did put that on the chat itself. Catherine but, but for for those who haven't had a chance to read. So the system that I have presented at the moment is able to detect dissolved organic carbon cyanobacteria, and we are thinking of including species. So that is kind of in the in the visible world, but we are also in CSR working with sensor technology. There's a group working with dissolve constituents, but therefore the future. Thank you very much for that response. So we have a couple of questions I realized that. Yeah, so there's one that was asked to Kenneth and I realized that you did answer it in the chat but maybe so everyone else can hear it. The question is, what kind of data is being is Dr. Moondizi collecting in the Okavango because there is a struggle in getting ecological aquatic health historical data in this area so can you give some insights into the type of data that is being collected there. Thank you so much Catherine. So the platform provided an observation means also the end user is collecting some in situ data for validation. For example, we were looking at the water levels at different times, based on what was presented as a product for them showing the analysis over time. And also interviewing the farmers around the region, what has happened, and also collaborating with the Botswana meteorological agencies so it's quite a collaboration of end user and the champions on the ground. And I know there's a challenge of people sharing data, and also people working in silos, and it's a great opportunity to be part of these important workshop to see how we can work together closely. Thank you. Thank you very much for that response so I have another question for Lisa on data storage and how is this analyzed. My understanding of this question, it's asking basically how are you, how are you undergoing data cleaning filtering and targeting their appropriate data and how are you able to do this in the time in very quick time scales. Thanks Catherine. So, all of the data that we use comes from existing global data sets and databases which have, which are all already in analysis ready data formats. So they've already been clean they've already been filtered. So the thematic products in that list that I showed, they've already been validated they have a level of uncertainty associated with them. So that's the attractiveness of the approaches that we're integrating from existing analysis ready or thematic data set so we do not undertake the cleaning and filtering that you mentioned. What you need to do, however, is bias correction and calibration for things like the precipitation data which will vary from location to location because it's quite context specific so for certain key data sets where we know that there are landscape that we do do bias correction and validation. We also integrate outflows for each basin that we work and that's what enables us to assign the uncertainty in our water balance parameters at the basin scale. Yeah, your points on the filtering and the cleaning are luckily not an issue for us in this approach. In terms of the storage we don't, I'm not sure what the reference to the milliseconds is, but we produce annual accounts. So it's processed over a year. It's not near real time data because you don't do that for the water accounts you produce a water account at the end of the calendar year. And as well the seasonal water accounts because you close the water balance once the season has finished and you want to look at the changes in storage over that entire accounting period. So yeah, for us it's not, it's not a case of instantaneous computations. One point though related to that is we're able to process these really large amounts of data because we're using Amazon Web Services and cloud-based processing. Yeah, thanks. Okay, thank you. Right, so I also have a few more questions. So perhaps at least another question for you is just following on what you were saying, how can we ensure increased acceptance of Earth observation data is obviously evolved considerably in the past few years but sometimes there is questions about uncertainty and reliability. What strategies do you have in place for that? Thanks, Catherine. I think this is a really important question because like you say over the past few years, our access to the type of data that's available from Earth observation satellites, particularly within water cycle science has really changed and revolutionized what we can do with it and levels of uncertainty have become increasingly more acceptable. But there is always a certain mistrust or just not understanding what those certainties are don't exist outside of the community. And it's really important when we present the approach to our users that we're very transparent and clear about what the data can be used for and what it can't be used for. So, for example, with this type of approach we're very clear it's applicable to establish baselines at the basin scale or the sub basin scale, not at a small catchment scale because the uncertainties outweigh the benefits that you would get for decision making at that level. So to me it's really about being transparent about the scale of application and use. But also somewhat against that is for many of the basins in which we work which are engaged basins, no information is available. So even with large levels of uncertainty, we're still able to constrain some of the decision making with this type of analysis. So we always need to be cognizant of the levels of uncertainty that come with the use of the Earth observation data to be very transparent and clear about those from the start. I think we also need to bear in mind that for many places, particularly where we work, even with large levels of uncertainty, it still helps with decision making in the absence of any other data. Yeah, thank you. Thank you very much for that response. See, I think that's very important. It's, it's opened up many opportunities for places that have don't have much access to data. So we only have a couple of minutes left. We have a question on sensors that tackles will answer, which is looking is asking about calibration and how they have to be customized. So if you can wrap us perhaps you can answer that question. Thank you Catherine and and Arjun. This is one of the question that we're trying to address in our project and I do fully agree that the water in northern hemisphere, different than the water we have in southern hemisphere in Australia. So, absolutely correct geographically, you know the amount of suspended collards for example for us. It is the aluminum silicates from very old continent. Most of the rivers in the Maradarling basin, they have this marquee water throughout the year, not as you see in Amazon or probably Nile river. So you're right. And for this particular reason, many satellite based observation data that people are trying to promote or sale. And I mentioned there are a number of companies are trying to say, oh, I can tell you what is the current status of Blue Green algae, for example, and how they're going to look in in future. Many of them, I believe, please correct me, those who are present here are not properly calibrated and this is what I think this mission Australia coach mission is is trying to do is to. set up pilot projects and I have shared that in my presentations throughout the world, not not Europe. I don't think elegies a big problem there. So, we would like to ground truth, our above water sensor, and then we would like to calibrate the satellite. And hence, you are right, it will be geographical based calibration algorithm that will be using of course will be able to do each and every water bodies. If that makes sense. Thank you. Great. Thank you very much. And we don't have any time. I'm going to ask one final question to Kenneth, but then we need to move on. We're going to have a breakout room so there'll be lots of chance to discuss in more detail. The final question for you, Kenneth is. So, how do you see our thoughts of observation information being used to support development in the context of water resources, especially at the local level. Thank you very much Catherine as earlier alluded to is that the platform is quite big and not most people are aware about it, and the few people know it our champions. So for example in Tanzania, we are working with the National Bureau of Statistics, a person who has an observation background, and is trying to support the SDG process and they went to a specific leg to show how this can actually be impactful and such people are the ones who are working with the National Development Agenda as a tool which can be used. The other example of a Kavango was working with the first to put so on a person to help policymakers to develop an integrated watershed plan. So as much as we have the earth observation. It's for us to engage with the policymakers as well as the scientists who are between us and the policymakers to make it very easy for them to see this platform is not a threat, but it's a useful tool for them to use and integrate. So we preserve the resources for sustainable development. For example, if some of these lakes are not looked after, they will be dried up as we heard the case, some parts of lecture. So lecture we are looking at it using our colleagues in agreement in Asia, who are looking at four countries, and this is a matter of a course. So it's quite a process and it's a dialogue and we are grateful for these first meeting and looking forward to many, many more. Thank you very much and I have a key point there that we can use earth observation data as part of the dialogue to figure out how better to manage our water resources so I'll hand back to Aaron, and we'll move to the breakout rooms. Catherine, and thank you to all the speakers for such insightful presentations, as well as the question and answer. So now we will have the opportunity to discuss in a smaller format and get some more, you know, discussion flowing. So now, randomly place you in breakout rooms, where we will be able to discuss two main things. Our speakers will be moderators as well as we will have repertoires, they're just making notes of the main points of our discussion. So first part of the breakout room, we would like you, our attendees to share with us the moderators and repertoires, just about your experiences and experiences on projects and initiatives related to today's topic. So anything that you could relate to from the presentations that you saw, or something that you didn't see mentioned today and that you think is important to also be mentioned. And then the second part, we would like to hear from you, your thoughts about this community of practice and just about how you think you can participate. So just without any further discussion, maybe we could already start the breakout rooms. Okay, so let's continue. At this time, we will ask the moderators from the breakout room sessions to just give a short recap, just just to, you know, summarize what was discussed in in each breakout room. Tapas, would you like to go first? Sure. Would you like to wait for all to join or you have everyone in the room now. Get all back again, Tapas. Okay, wonderful. So we had a spectrum of discussions and there are six, seven, including the villa in our group and had wide variety of experiences that they shared with us. There are a few things that of highlight and they are, for example, in terms of observation data, we need to be mindful that we don't claim that all data quote analysis ready unquote because because for what a quality particularly many data may not be ground truth so ground truth came also into the conversation ground truth. So I think it's very important and one of the participants have mentioned that very clearly. So second one is about advantage of observation which universally accepted that it can give you information for those countries who do not have a good set of information. And particularly for water resources, you can have them from the sky, even though the country doesn't have good ground data. So it is, it is kind of a good tool that was discussed. And in the background of climate change, water security, sort of things that are observation will play a greater role. So the other conversation was about conflict, international water conflicts, where particular country doesn't want to provide data. So these are the things that were discussed and also application of observation for downwater planning, wastewater management, water resources management, some things came up. Thank you. Sounds like a nice discussion. Kenneth. Thank you so much, Elaine. For us, it was more of the group met for the first time and they were so excited to know what everyone is doing. So there was a question of what else is there that IW can make possible like like a knowledge base where we can actually know where everyone is or what everyone is doing. So we had persons from ground station space in the Netherlands who are doing quite useful stuff. And also they were looking at various programs, working with Copenhagen's and some of the projects that they're doing and how they can actually connect with more persons in this webinar, like opportunities which are there. Then we had a colleague from South Africa working in actually a water quality department, whom they might lack data. So sometimes they have to go physically to the ground to collect data. So those are the pains and points of getting the data versus what they can use from the space. So the support they can get from, like in the context where she is you can get the support from South Africa space agency to get an assessment of some of these areas whom we are supporting through digital at Africa. And also partners like CNS are developing some new tools and projects. So the new tools can be very useful to inform water quality and also what libraries are there which are open source. So these are some of the questions which were there. So like I've posted the information about the ground space, then opportunities for moving forward. There were suggestions about incorporating these technical and commercial specification in terms of procurement. It was quite initially discussed. Then a call to action is how to connect the work we do with policy makers. How are we communicating with them. We are very technical with the 50 PowerPoint slides or a thousand manuscripts or is it possible to have policy briefs which can really inform policy. And how are we able to work with the people on the ground in terms of citizen science impact stories. And also moving forward opportunities for frequent meetings, maybe that we can actually have more information, perhaps some of the persons wanted to be in this group breakout soon, breakout group they were not able to actually connect more. So the ball is yours IWA. Thank you. Thank you very much. And Lisa, Lisa Maria. So we only had two participants in in our meeting room, in addition to the moderate and wrap it all. So I'll just summarize very briefly two key highlights of the discussion. And one was really around the challenges that we still face in use using of observation data within the water sector. And an aspect of that was still in particular in relation to water quality assessments, the need for a lot of in situ and climatic variables and I think it's a really important point that sometimes gets gets a bit lost is that we are still for some applications very much dependent on the amount and quality of the in situ data. So some applications are still very much context specific, but then related to that also came how we can through the community of practice and bring together people working in different locations on the same issues who have access to different sets of data. And either through data sharing or experience sharing work together on similar thematic areas. Yeah, thanks. Thank you and Eunice. So we were in breakout for and I was with Erin. I think we had a really nice discussion that we had about seven participants from different countries. I think they're really the take home message from our group was that the fact that everyone is kind of on a different level in terms of their journey from moving from traditional monitoring water quality to that observation or for our artificial intelligence, whatever you'd like to brand it as. So it was nice for us to then share the kinds of challenges that we are facing as we are trying to move more to earth observation for water quality monitoring. I think our dream brought up a nice topic around data management, which is not only for earth observation but it's for a lot of the water work that we're doing what do we do with the data how do we clean it up effectively. What do we delete but then at the same time we had Jordy from Spain, who have been doing a lot of traditional monitoring they have years and years of data and does that make it easier than to leapfrog into using earth observation technology so there was a really nice discussion around data management and also just encouraging each other in terms of what we can take from each other to make sure then that are we're not repeating the same mistakes that other groups have made as they move from your traditional monitoring more to your earth observation then they're also in terms of projects that are starting I know as he's from Finland she mentioned the fact that they are developing an app in South Africa to we also have a sign or links app that looks at each vacation at our different dams so I think maybe IWA has to find a way to collate some of these kinds of technologies that are coming up that people can try on their own, you know, or maybe use it in their utilities as well I think also there was a little bit of it didn't come out clearly but a little bit of differences in terms of challenges around what utilities will face and what people are focusing on when it comes to research and academia. So you do find that the research and academia is a little bit ahead whilst utilities we're still trying to drag them along to to to use some of the stuff that we verified during our research processes yeah I think Aaron that's the sum of it I don't know whether you have any addition. You sounded it very well. Thank you very much Eunice and just to close I will hand over to Catherine to sum it up as best as she can. Catherine. Okay, thank you Aaron and thank you everyone for participating today. I think it was a really good discussion. Also like to thank the speakers for providing your perspectives and setting the scene. I think it's a good base for future discussions. I think the point that we heard about sharing our journeys of monitoring forecasting in a water management context could be, you know, for different uses, and how Earth observation has been part of that is important to really learn from each other. I think secondly the point about understanding the challenges that are being faced. And how in situ data can work together with Earth observation data. Then thirdly, I thought there was a very good point about connecting this with policymakers. There's a lot of laws that are in different parts of the world, water resource laws that are being under reform and there's an opportunity to integrate this type of these types of approaches in the these amendments and also bring this to the notice of policymakers. And then finally, yeah, the need for a knowledge base. IWA is a good platform to share information. So we encourage you all to join if you have not already the community of practice, which is on IWA connect and put forth your ideas for for future discussions or future outputs that the community of practice can facilitate and get in touch with Aaron and Sam Weller and they would be happy to put together ideas for future events and for the conversation. So I think I will wrap up there. Thank you again everyone for your participation today and hope to talk to you all again in the future. So thank you.