 Hello everyone. Good morning, good afternoon, and good evening, depending on where you're joining from. My name is Erin Jordan. I am the strategic programs officer at the international water association here in London, United Kingdom. Thank you for joining us today for the IWA Earth observation for water management community practice meeting. On user experiences in Earth observation for water management. So today we have a pretty straightforward agenda. I'll be giving you a welcome and an icebreaker, very short icebreaker. We have presentations for presentations from expert speakers. Moderated by Karen Shank from EOMAP, a Q&A panel discussion as well. Moderated by Karen, a short presentation by Jeff Sawyer about the Sentinel Benefits Study. Later on, and then we wrap up and close. Just a bit of important information. You can use the chat box to just share your comments. You can introduce yourself there as well. And if you would like to ask questions directly to the speakers, then you can raise your hand, come on screen and ask those questions. This is a meeting as mentioned, so please feel free to interact actively. Just a bit of information about the Earth observation community practice. We started, this community practice was launched in 2021 and this was part of the prime water project, the recently concluded prime water project. And it is also a part of the IWA digital water program. We also are working in conjunction with GeoAcoWatch with this community practice. So for the COP, we try to provide platforms much like this meeting for like-minded professionals to come to learn, to share what they've been doing regarding Earth observation for water management. We also try to connect and create inter- and intrasectoral linkages within the water sector. And we try to identify the gaps on how we can address these issues. So just a quick, quick, quick icebreaker so we can know where we are joining from today. My colleague Samuela added a link in the chat, just know where you can, where we can see where you're joining from. I see Jeff has already, Jeff has already added his name. Thank you, Jeff, for your swiftness. I appreciate that. I'm not sure about the rest, but I've managed to have my name. Yes, don't worry. I can see your name and that's good enough. That's good enough for me. So please feel free to add. Samuela has added, somebody has added in Italy. Good to see you. For those of you who are just joining, we're doing just a short icebreaker just to see where our attendees are joining from today. So the link has been added to the chat. I'm sure you can, I believe if you add, if you join afterwards, you should still be able to see the link. Please feel free to just quickly add your name and where you're joining from. I think we have a good spread. Scenes, Europe and the US. Quite a few people in Europe. Just give a few more, a few more minutes before we continue with today's session. All right. I'm not seeing any further additions. So, I think somebody just added. Cedric is joining for Rwanda. Welcome Cedric. Okay. So thanks for participating in this icebreaker. It's good to see that we have a nice spread of attendees. So as I mentioned today, we are having four presentations and the session will be moderated by Karen Shank, who is the head of the Water Quality Department at EOMAP. And the four presentations will be given by Brian Eiler from the Simpson Centre, Sotia Kim from the Mekong River Commission, Secretary at Ilse Rosen from Vito Belgium. She's also representing the Water Force Water Quality Continuum. And Megan Coffer from the National Oceanic Atmospheric Administration at Global Science and Technology Inc. So Karen, without further ado, I will stop sharing my screen and I'll let you continue. Great. Thanks, Erin. Welcome everybody. So, yeah, real quick, my name is Karen, Karen Shank, and I'm working in the field of aquatic remote sensing since now over a decade. I'm leading currently the Water Quality Department at EOMAP, which is a small company specialized in mapping and monitoring. The water environment using all kinds of different Earth observation methods and satellites, drones, airborne. And I will guide you today through the session and because great talks on showcases how Earth observation in water management brings benefits to the stakeholders. And Erin already mentioned this was followed by a Q&A session. So if you have any questions, just type in the chat and also a panel discussion by our speakers. And we end with a presentation on Choff from URSC about the Sentinel Benefit Study. So let's start. The first talk will be held by Brian Eiler about using SAR imagery for smarter water planning and disaster risk reduction. So currently, Brian directed the Southeast Asia Program and the Energy Water and Sustainability Program at the Stimson Center located in Washington, DC currently. And he's an expert on trans-boundary issues in the Mekong region and specialized also in China's economic cooperation within Southeast Asia. And yeah, he's a widely recognized leading voice on environmental energy and water security issues along the whole Mekong River Basin. And he also spent more than 15 years living and working in China. So Brian is also a co-lead of the Mekong Dam Monitor, which is a very nice online open source tool. And he's also the winner of this 2021 S3 Special Achievement in GIS Award. And yeah, so he holds also a Master's degree from the University of California and in San Diego. And I think I stopped and leave Brian the floor. So thanks. Thanks, Karen. And thanks to IWA and Erin for inviting me to speak with you all today. I'm going to share my screen here, which actually takes you to our Mekong Dam Monitor, which I'm going to be speaking about, but I'm going to go to the slide deck where we're going to focus on using synthetic aperture radar imagery for smarter water planning and disaster risk reduction. Much of my talk is going to be on the Mekong Basin and showing you some derived analysis that comes from SAR imagery on reporting results and impacts of reservoir operations throughout the Mekong Basin. And we do this on the Mekong Dam Monitor. What you see here on the right is one of our pages. It's our virtual gauges page where kind of technical folks can land to learn about the state of water throughout the entirety of the Mekong Basin. And this is important because countries, particularly China and Laos, do not provide information about the operations of their large dams. China has two of the largest dams in the world. On the upstream of the Mekong, they hold about 24, 23 cubic kilometers of active storage that can wield tremendous impacts all the way down to Cambodia 2000 kilometers away. So having information which we provide via SAR on a weekly basis on the Mekong Dam Monitor provides governments and communities along the course of the river. And those are interested with information about the impacts of those dams. And it's been a big boon for the region. We launched in 2020. We use a variety of earth observation inputs. I'm going to focus on SAR today. But we do our work with SAR with optical imagery and microwave data inputs as well. Over the last two years, we've now been able to make confirmed use cases by the Mekong River Commission. My friend Satya Kim is here from the Mekong River Commission. And we've established a good informal relationship with the Mekong River Commission where we've learned a lot about turning data into information and communicating it to people who need it. We've got use cases in the governments of Vietnam, Cambodia, Thailand, Laos, NGOs, and research institutions. We provide an early warning service, particularly looking at China's dams for when those dams release water or restrict water enough to change the river level downstream 50 centimeters or more within a 24-hour period. And we've done this 50 times over the last two years. And those alerts hit communities and the people who needed two to five days before those impacts hit, giving them plenty of time to adapt and adjust. We turn our data into information not only on our online platform, but we put it up on social media in seven languages. And that's resulted in 35 million social media hits over the last two years since 2022. Our website is there at the bottom, monitor.mekongwater.org. We get about 15,000 viewers per month on the website. So just to give you a feel for what synthetic aperture radar can do, it can see water from space. And since it's not an optical image, it gives us the opportunity to see through clouds as well as look at the Earth anytime during the day, whether the sun is shining it on it or not. And so what we're seeing is a backscatter image processed on Google Earth Engine of the Xiaolan Dam. It's one of those large dams in China. The black is the reservoir. The right image is the Tongling Sap bottleneck where this is the largest lake in Southeast Asia. We're looking at the part of the lake where the lake turns into a river and begins to flow downstream to Panong Pen. What we do with our imagery is we look for mean values along the course of the reservoirs or the river's shoreline. And we take roughly 100 mean values using Google Earth Engine process that we filter out some of the shadows and the bias that comes with SAR imagery. And we generate a mean value for the level of that reservoir. And we translate that mean value into volume. And that allows us to know what the current volume is as well as to track volume changes on a weekly basis. Importantly, we can't do this without optical imagery. So Planet Lab's image archive comes into play for a post-check process. And that helps us reduce the error that comes with SAR data from the European Space Agency. I should mention this. This is from the Sentinel-1 constellation. Reduce error of about five meters to one meter of error through the post-check process. So we really can't do one without the other. You can't do it all with optical imagery, but together we can get within a very, I think, reasonable margin of error. And what this allows us to do is many things. One, we can just picture and provide an image of current inundation in the lower Mekong. And this level of inundation is important because it's what drives and makes the Mekong the world's largest inland fishery. The Mekong is responsible for producing 20% of the world's freshwater fish catch. And much of it comes from that blue that you see through the flood pulse or the expansion of the Tongling Sap Lake, the expansion of water in the Mekong Delta every year. We're able to provide a picture of water. We're able to track on a historical basis where that expansion or the flood pulse is compared to past year. So just this year, the flood pulse is just a bit below normal. And that's related to both climate impacts and dam impacts upstream. And we know that those dam impacts are impacting the Tongling Sap because we can see them with the data. We can see when those large reservoirs are taking a lot of water from the system during the what season and they're going to put it back in during the dry season. We've been able to determine how these dams operate, 55 of them throughout the entirety of the Mekong throughout the course of the year. And many of the large storage dams operate in a rather predictable way based on the amount of water availability. Now we don't just provide these graphs like you can see up in the top right corner but we provide the imagery too for our users. And that helps particularly those who are new to Earth observation data or derived products better understand what they're looking at and to provide evidence that they can see with their own eyes. We can piece together our information into cascade analyses which are helpful for dam optimization purposes. This is a cascade analysis of China's upper cascade of 11 dams. You can see those two large dams represented in the lighter blue and the red and how they fill up during the what season and then release water during the dry season for hydropower production. China's other nine dams are much smaller and they don't show up as much. But this is also useful for drought prediction and flood forecasting. So in the what season of 2022 about a year ago we found that China's dams did not fill up as much as they typically do. Let's say during the previous two years and that was a result of a drought that China was having. If you think back to August of last year you remember those pictures of people in China walking across the Yangtze River or looking like they could because it was so low. But that hit Yunnan province in China as well. And disabled those reservoirs from filling as much as they normally do. When we saw this in December of last year we informed communities that releases in the subsequent dry season which has already passed but at that point it hadn't would be less than normal less than previous years. So what I've done here is shown that our forecast came true. I'm comparing the bottom gauge data that brings in dam releases so we're taking observed flow from a gauge finding the dam release in that observed flow and subtracting it out to create the blue value. The blue value gives us an idea of flow without dam releases and how high or how much water would have been in the river under natural conditions. If we compare 2022 dry season to 2023 we see that the 2023 dry season even with dam releases tracks much more closely to a mean flow line for the river system. Whereas in 2022 look at those March, April and May you're doubling almost tripling flow from those dam releases and this is causing a number of impacts throughout the basin particularly farther downstream in Cambodia 2,000 kilometers away the combined impacts of dam releases during the dry season are killing flooded forests in northern Cambodia. And this is an important habitat for migratory birds now many of which are endangered for fish species for freshwater dolphins and millions of people who rely on these flooded forests in northern Cambodia for their livelihoods. These flooded forests are dying out you can see that in the trees in the middle of the river. We're not only able to show what the impacts of say China's dams are far downstream 2,000 kilometers away but we're able to look at different kind of sections or sub basins of the river system and demonstrate the impacts of dams all the way down to Stuntran. And we're finding unique information such as there's a certain grouping of dams in Laos now that also wields significant impact far downstream that's represented in the green bars for the Stuntran dry season chart there at the bottom artificially raising the level of the river much higher than it should be during the dry season and delivering particularly ecological impacts. Just to wrap up we're taking our toolbox and our knowledge to disaster risk reduction in Nepal by looking at and monitoring and trying to forecast for extreme events and debris floods. So this is a SAR analysis of a massive debris flood that happened in the Malamchi basin in Nepal two years ago. And more recently just a few weeks ago there was a major disaster in Sikkim, India related to a glacial lake outburst flood where we were able to bring in some very high resolution SAR imagery one meter from a private provider Umbra and I should have put their logo up here to see whether there an avalanche effect caused water to rush into this glacial lake and cause a glacial lake outburst flood which then destroyed a dam about 40 kilometers downstream 1.5 billion dollar 1200 megawatt dam and caused unknown amount of deaths something like 40 or 50 people were killed in that incident and the run out of that incident ran out about 100 kilometers. So this is a new area that we are putting our tech to use and happy to have a discussion with all of you here in a bit and thank you for your attention. Thanks very much Brian very enlightened also this kind of trans boundary analysis from space from an objective point of view. Yeah, so we please type your questions into the chat. We will have a look later in the Q&A session and I would like to introduce now our next speaker who was already mentioned Dr. Cecilia Kim from the Mekong River Commission Secretary at so Dr. Kim has over 20 years of working experience with international organizations including the Japanese ODA project the USA supported program also the Mekong River Commission we just heard and is recently working with the regional flood Trout Management Center of the MRC basis in Montpen in Cambodia. So he holds a PhD degree since 2007 in water resource and environmental engineering from the Tokyo University of Architecture and Technology and he will talk about today about flood and trout forecasting and warning systems of the Mekong River Commission based on satellite data. So I'm looking forward to the presentation Cecilia, so the floor is yours. Thank you Karen. Yeah, I think Karen and Brian have already briefed on my bio and also Brian briefing or detailing about Mekong River passing connecting to the China the upper part of the Mekong region. So here I just would like to present about the flood and trout forecasting and warning system of the Mekong River Commission based on the satellite data. Yes, next please. Yes. You know the Mekong River Commission have been formed in 1997 and based on the four member country of Cambodia, Laopidao, Thailand and Vietnam and now the main office is located in Vientiane of the Laopidao but remaining the flood regional flood and drought management center in Nongpeng, Cambodia and we are doing mostly regarding to the flood and drought prediction and forecasting. Yes, next please. Okay, regarding to the work of the MOC to prediction to predict and focus on the flood and drought for the lower Mekong basin we have signed agreement or the MOU between the four member country of Cambodia, Laopidao, island of Vietnam to share their data availability. At the moment we have received hydrometer data from the four member country about 46 water level and 138 rainfall station all over the lower Mekong basin and because of the limitation of this some of the area they have no data provided by the member country so that's why we try to use the satellite to cover all the lower Mekong basin. Yes, next please. Okay, for the MOC regional flood center we have already mentioned that we are working from Cambodia in Phnom Penh so we have three main activities. First, we are doing on the daily flood forecasting and flood early warning system that we are doing from June to October and this month is the end of our forecasting in Delhi but we still continue to provide a quickly monitoring water level in dry season starting from November to May and also we providing the flood guide system that we have been produced about once hours, three hours, six hours, 24 hours and we issue the bulletin and share to the member country based on our website as well as the sister web page email that have been received from all member country and all the stakeholders and beside the flood guidance system we provide also the flood forecasting flood prediction in weekly Monday and updated based on the NASA satellite data. Yes, next please. Yeah, I didn't show you what type of satellite that they have been used before. You know, since we start the flood for coasting we are using the hydropower model combined with hydrodynamic model which is to put in a two-flat form they call a two-flat form the flood early warning system and we use this S or E that satellite rainfall estimated and GFAS global flood estimated satellite data so we use those data for our input for flood forecasting. However, at the moment starting from 2022 we have working and consulting with the ADPC Asian Disaster Center our preparedness center so we are now trying to use the CHERP GSF we have been trying testing at the moment and also GPM based on our available ground station data so we use GPM by cooperation it's a by us correction so we call GPM by four so this is we can use for instead of S or E and GFAS S or E and GFAS is a product of NOAA but now we are using a product of from GPM and CHERP GSF so we are now on the testing period that we will try to modify and some other simulation based on the hydropower model and ISIS hydrodynamic model apply separately at the most of the modern area and the floodland area which is mainly applied for the hydrodynamic model this is just only a schema how we use the existing tune and the new tune of the platform for our flood forecasting activity yeah exactly yeah for the real flood forecasting activity we produce a daily flood forecasting in in the next five days and we call for the next five days and stay one to day five and we issue a daily bulletin and share to the member countries and the member country will connecting to the sub-national level for sharing information to the provincial level as well as the community level however comes the MOC have been done just only for the main stream flood forecasting activity not focused on the territory because the territory part just part of the mandate for the member country that have been used for the national level and this is also the our bulletin platform we have share to the member country in every day from or during the flood season yes like this yeah for the flood flood guidance system I've already mentioned that we have issued one hour 60 hour six hour 24 hour so we have captured the the aerial of the rainfall and mostly the data we are using from the NOAA also from SRE is a main input for our flood flood flood flood guidance system and we also produce the urban soil moisture and flood flood guidance system during the 24 hours to detect some of the area we have been affected by the rainfall and you know this year is affected strongly in Cambodia in this month that we have been flooded off of the rainfall heavy rainfall and some part of loud video as well as the midnight part like this yeah for the drought of testing as already mentioned that we are using mostly data from NASA and the drop for testing apply the hour of drought index of CDI and SOI so this is we apply many some of the main indicator about the drought of the addition on the methodical drought hydrological drought and hydro control drought and provide this information to the member country in weekly and monthly information but not based on the polluting but we are sharing information based on our web page and you can see our web page of the MOC that will distinguish flood flood flood and drought and it's easy to understand how the drought lifting some of the area in the lower the combustion can be shared to the community level that can be used for our dropping the turn of planning or the growing crop etc yes so now we just mainly describe about what the main activity we have been done at the regional flood and drought management center but we still have more action planning to do for our activity in this year up from this year on for example we would like to improve the quality of both hydrometer data water level and rainfall as well as the water input and based on the QAQC of the water of the data that have been collected from the member country of course the applying of GPM by co-activation is still ongoing and they will produce a report of the evaluation soon after this end of this of flood season getting to the old model that we after all satellite data that we had used and also we need some more that are especially for waiting for that data the member country and of course the information that have been described very prime about the place of water operation or dam operation at upstream is how we need for our input for cloud for testing and of course the plan to provide the flexibility of the cloud for testing for the national level at each member country and also now we are developing the medium and long term for testing for flood control and of course now we are on the testing period but still not yet up in our website so this is that we are working closely with the member country and also with the outside agency like ADPC as I mentioned I DHI as the private consultant and e-water from Australia that have been closely working with MOC and of course we are thankfulness for the member country and order outside partner who been provided assistance for the MOC as a whole and thank you for everyone who are interested for the MOC for thank you thank you very much Susia that was very interesting how to combination of satellite data and modeling approaches can lead to an improved drought and flood forecasting thanks very much so the next speaker is Ilz is Royzen from VITO so Ilz is working for VITO as an independent Flamish research organization in the area of clean tech and sustainable development and she's been working in the remote sensing department since already 2000 so first as a researcher then as project mentor and coordinator so her focus was initially on airborne hyperspectal data and apex but now it's moving towards orientation the use of Sentinel tool Pro-Bavi and Sentinel-3 satellites for monitoring of our water resources we both have been together in a project 10 years ago the FP7 inform project and there are many other projects are coming afterwards like the DCS4COP or the Copernicus Global Land Service this is also a member of the editorial board of the international journal of applied verse observation and geo information and she supervises the oil fire education activities and she's also the contact point of veto for the Copernicus academy and the member of to your aqua watch just as background is received the master of science in physics and a PhD in physics and from the university of Louisville and I'm now looking forward to listen to her talk about the potential and uptake of earth observation for inland water quality monitoring and reporting please else thank you Karin I want to share my screen okay so thank you Karin for the introduction the kind introduction and thank you IWA for the invitation this presentation is about potential and uptake of earth observation or inland water quality monitoring and reporting and it is based on the AOMores another European project white paper and on contributions from many other partners from the water force project another European project so it was my pleasure to witness at the UN water conference in New York this year that the value of satellite data is is recognized so and I cite that remote sensing and satellite imagery holds great potential for transforming how data and information are generated and accessed and used for monitoring reporting on water bodies and at field observations will remain essential for ground that route so in Europe so with the Copernicus earth observation program and also with its Sentinel satellites and with the new Copernicus data space ecosystem the Copernicus data is openly and freely available and the nice thing is that there is a guarantee of Sentinel until at least 2030 so the Sentinel-2 sensor that is often used for water quality is the Sentinel-2 and you will see some examples of this in my presentation so with Sentinel-2 we have a revisit time of five days with the two satellites and we have 13 spectral bands and the spatial resolution from 10 to 20 to 60 meter so there is complementary value in these optical water quality observations which are relevant for the European water framework directive with respect to the surface water so and in this water framework directive they want to achieve good ecological status and ecological status is as is based on three elements on biological elements on physical chemical elements and on hydro morphology elements and for these ecological status there are five classes defined from high quality up to bad quality so but we see from the water force project that there is a need to align the in situ and the satellite remote sensing data to achieve the highest complementary value of both and also a need to integrate satellite and in situ observations into policy frameworks but there is good news as you can see on the right that this is an extract from a proposal for a amendment of the European directives related to water and this is citing that earth observation Copernicus services can be data can be used so member states that should be allowed to use data of these services earth observation so that's very good news and in the monocle project another European project in a survey the participants were asked which are the water quality variables that are most relevant for you and in blue we see the variables where in situ observations are essential and in green the ones where remote sensing can play a role a complementary role so and in green we see chlorophyll temperature and the total suspendance matter and then in another in the in the Eomores European project there was a publication a white paper publication that looked at the satellite based opportunities through a water framework directive lens and many of the examples I showed today are based on this white paper and what is in this white paper there is there was an analysis of the water framework directive and on the left side you see the elements the biological elements that are required for the water framework directive reporting so there is abundance of biomass there is frequency of blooms macrophytes transparency and then on the right column you see the satellite derived proxies that could be considered to address these these elements so we see in this right column we see chlorophyll we see trophic state index phycocyanin area of floating vegeta- aerial cover of floating vegetation we see also seagrass density and we see turbidity suspended particulate matter are for transparency and temperature so optical satellite observations can be considered in seven biological and physical chemical elements that are mentioned in the water framework directive and major improvements are expected for a frequency of blooms because this requires high spatial and temporal cover this white paper is accessible on Xenodo and so it's publicly available so then in Estonia they compared satellite based chlorophyll with in-situ chlorophyll and then the temporal data coverage is 10 times higher by using the satellite data and the validation is good on the basis of the water framework directive classes which you see here in on the right figure with indicated by these colors so yellow is bad quality and more purple blue wishes is good quality and then on the right side a map of the that is P90 percentile for the summer season or for the whole season then in Finland they are clearly ahead in using satellite observations for the water framework directive reporting as they already use satellite products in the last two reporting periods and they have also a good correspondence between the satellite data and the in-situ data they have set up also and a web-based application called TARCA and yeah I think that's also publicly available so then I go to Italy where they used Sentinel-2 and Sentinel-3 data for chlorophyll A so you see spatial very variation variability and this is used also to select new locations for in-situ measurements and you see also the temporal changes during the season and then this satellite-based chlorophyll A results compare also well with the in-situ total phosphorus which cannot be measured directly with with satellites there is a paper on this so I invite you to this one for more details and then in Italy they have been producing maps of submerged macrophytes in the light green you see the sparse-routed macrophytes and in dark green the dense-routed macrophytes and blue is spare sediment and then you see under the graph on the right the area they discovered by each of these cover classes and also in yellow the floating macrophytes so over the season France another example of seagrass mapping where they have the total area observed rather than average percentage cover in quadrats and then in Ireland ecological status assessment based on Sentinel-2 was tested for one catchment this catchment contains 44 lakes and ponds of which only three are monitored by traditional methods with boats and sampling and this model was an applied to Sentinel-2 data and they were able to do predictions of ecological status for 16 lakes so it helped them to monitor lakes which are currently go unchecked and then the Sentinel-2 based ecological status was compared to the one based on field measurements and they found that results were within one ecological class for this test catchment and then I go to Flanders, Belgium where I live so there we developed for the Flanders Environment Agency the water monitor it's a near real-time service based near real-time service for chlorophyll A and integrated also the in-situ chlorophyll A provided by the Flanders Environment Agency and so you can select water body on the left then you get the chlorophyll map you can select the dates you can watch the time series of the Sentinel-2 based chlorophyll for the water body or for another region of interest and also the in-situ chlorophyll and then the color code you see the water framework directive classes and colors which are added also this was a customized viewer and there is an exceedance alert whenever a chlorophyll concentration exceeds a certain threshold for a certain class of water body then another example in Belgium we have at VITO also the Terrasco platform that's the Belgian Copernicus collaborative platform and there we provide also suspended particulate matter and turbidity for Belgium and a part of the Netherlands then in the Netherlands there is Lake Marken and there because of the silt dynamics the growth of plants and and muscle population decreased and they used silt to create Marken-Wadden islands and here you see the Sentinel-Lansat images and also Sentinel images that can be used to monitor the sediment dynamics the spatial variation the and the temporal variation and also very nicely the building the creation of these islands and then I move from Europe to Vietnam there is this is ExploreVN that's a cloud-based Sentinel-2 based platform for water quality for Vietnam that was developed for the Institute of Geography of the Vietnam Academy of Science and Technology there is a web application and what is new here and that there is a client system a credit system that can be used for resource accounting like how many credits have already been used how many are left what tiles are already processed and it's this ExploreVN will be officially hand over to VAST in in about two weeks so one of my colleagues is going there to celebrate 30 years of the Institute of Geography in VAST and then that will be an official hand over of this ExploreVN tool and some functionalities you can choose chlorophyll A suspended those suspended matter turbidity trophic state index you can select statistics the statistical indicators and and water quality indicators and then look at the time series of these parameters you can download a region of interest or you can also there's some automatic processing for a number of tiles but you can also do an on-demand processing for for other tiles and then I end with saying that water force is working on developing a roadmap for the water component of the Copernicus services and the draft roadmap was presented a few weeks ago but it is still open for feedback so everybody who wants to get involved and and and provide feedback on on this roadmap I invite you to go to the waterforce.eu website and then here are my contact details thanks very much Ils for this let's say worldwide coverage showing different kind of products which can be used for the in and water quality monitoring we are a little bit behind but I think it's still okay and then we just quickly move to the next and last speaker before the panel and Q&A session this is Megan Koffer with her talk on leveraging a range of both observation satellites for aquatic applications and Megan has a PhD and is a research scientist for the coast watch application teams in NOAA Center for application satellite application research and her research focuses on satellite analysis for coastal and also inland water quality and with a particular focus on monitoring cyanobacteria blooms in inland lakes and reservoirs she's using freely available satellite data but also commercial ones also for mapping sea cross extends along the coast and she also served as a leader for the T.O. Akerwatch technical working group and vice chair of the T.O. Akerwatch early career society so Megan the floor is yours so we see you thank you so much great yeah I haven't done the screen control before sorry about that I was trying to move the cameras but that's okay I don't need to see the whole slides but yeah thank you so much for the introduction and for having me here today again my name is Megan Koffer I'm a research scientist at NOAA and global science and technology and given the audience today I just wanted to present a few examples of satellite platforms and what types of water quality management and monitoring tools we can derive from those different platforms so as mentioned I'm part of the NOAA Coastwatch applications team so we're a group that sits within NOAA's center for satellite applications and research and we have several offices across the United States we have central operations where we're providing help in accessing satellite remote sensing data we have links and data portals for getting data and then also software development to continue to progress tools for being able to access and analyze the imagery and we also have training and outreach so our group does a lot of different workshops both virtual and in person for trying to increase awareness and flexibility and comfort with using the satellite data and being able to help users get the results that they want out of the satellite products that they're using we also have applications and research which is where I sit and within this group we use our satellite data products to look at different environmental questions both at the request of stakeholders and also just through our own curiosity and filling gaps in the literature that we find as we're working with this data and as I mentioned we have offices across the U.S. and these include both regional node offices and then also offices that are focused on more specific applications such as our polar watch group and our water watch group and today I'll be sharing just from a few satellites that I've used pretty heavily in water quality monitoring and these can be split into two broad groups the first being commercial high spatial resolution satellite platforms so these include Maxar's WorldView2 and WorldView3 satellite platforms each of which have a spatial resolution of two meters which is extremely fine spatial resolution and is really useful for mapping small scale heterogeneous features and then also the planet scope satellites from planet labs which have a spatial resolution of five meters and each of these platforms have different trade-offs as far as how frequently they're revisiting a spot how much data they're collecting across the electromagnetic spectrum and things like that and with these platforms typically you do have to pay for access to the imagery because we're federal government here in the U.S. we do get access to these at no cost to us so it's been really helpful for us to be able to develop processing protocols especially over aquatic environments because many of these sensors are designed for land not for water so understanding some of those kind of data quality nuances and trying to make improvements for commercial sensors moving forward specific to aquatic applications has been a focus of our research with that ability to access the data as well and then the other group of satellites are most likely more common to you these are the freely available and open access satellite platforms and this includes Landsat 8 which as it says in the name is also typically a land sensor but has really high quality data and has been used a lot for water quality and Landsat 8 is part of this longer Landsat legacy that has decades of satellite data observations one of the studies that all present on in a few slides we were able to look at 40 years of change in a certain location using the Landsat legacy and then we also have Sentinel-2 and Sentinel-3 and they have they're off by just a number but off quite a bit in spatial scale and other characteristics as well so they have really unique advantages in different water quality monitoring scenarios Sentinel-2 offers between 10 and 60 meter spatial resolution but most of the spectral bands that I use in my research are 20 meter spatial resolution and then Sentinel-3 is quite a bit coarser but has other advantages with a spatial resolution of 300 meters first I'll show a few studies I've done with some of the commercial data and products that we can derive using this the first is seagrass mapping so that's been a big part of my research so far we're able to use this high spatial resolution data to map the really fine scale features of seagrass and be able to differentiate relatively small seagrass patches from nearby sand and rocks and corals and things like that and with the worldview two and three data this is showing just a single example a back sound which is located in North Carolina in the United States and in the top row is a worldview two image with field data overlaid and shades of orange indicating both patchy and continuous seagrass beds and in the bottom row is our worldview two image classification which we use machine learning classifier to be able to separate pixels into seagrass and other classes and as part of this project we developed the first reproducible and semi-automated workflow for being able to use the Maxar worldview two and three data for aquatic applications again this was typically designed for land and there were some data quality issues over aquatic targets but we were able to produce a usable product for being able to get categorical variables such as seagrass presence and absence out of the commercial data and in our current efforts we're also looking at expanding this on the left here is a map looking at the United States where I'm showing some of the areas we've been meaning areas that we have successfully mapped done statistical comparisons with field data and feel confident about our results that we're presenting for these areas and all in the United States but they represent a broad range of optical water types climate conditions seagrass species and that includes all the way from Alaska down to California the Gulf of Mexico as well as the United States East Coast and New England and then here on the right is a map centered over the Indo-Pacific looking at where we're going so these are some of the sites that we've been working on classifying currently including Hawaii, Indonesia the Philippines and Western Australia Indonesia and Philippines partnerships have been particularly prominent for us recently as they're hoping to generate country-scale maps of blue carbon storage that's currently being held in seagrass ecosystems so those are some of our current efforts within the NOAA Coastwatch group so as I mentioned carbon storage is something that we can get at with the satellite data this is slightly less refined than our seagrass classification approach we're still a bit in the development phase here just because it can differ so much based on location and it's also really different generating categorical versus continuous data products we typically have slightly higher requirements for accuracy when we're looking at continuous data versus when it can be kind of lumped into different categories so currently we're looking at using the commercial earth observing platforms to look at carbon storage based on our seagrass classification maps and this is showing just a single example at St. Joseph Bay in Florida also in the U.S. We're on the left is our classification of seagrass presence and absence and then on the right we were able to use one of the spectral bands on the world view too sensor to estimate how much carbon storage was stored in the seagrass ecosystem and for 2010 we estimated that seagrasses in this bay held about 1600 metric tons of carbon which is equivalent to carbon dioxide emissions generated from four million gallons of gasoline so again this is slightly less refined and we haven't tested this at many other sites aside from here another limiting factor is getting field data for us to be able to validate the results that we're generating from the satellite products so something that we're working on and hoping to have a better idea of moving forward and then next all show some of the applications with our freely available and open access satellite platforms including the Landsat Legacy and the Sentinel two and three satellite series so recently we've looked at this is an image of Cape Cod in Massachusetts in the United States we've been able to look at water clarity for about 200 ponds across the Cape so the Cape is extremely susceptible to water quality changes and has itself almost a thousand ponds across the across just this relatively small area and we were able to use the Landsat dating back about 40 years to be able to look at changes in water clarity which can be really important for understanding kind of baseline trends over time and also for targeting management approaches and increased field sampling for future field sampling efforts across the Cape so for the most part we found that Cape Cod ponds that we studied were improving in long-term water clarity which is like the result of several management practices that have been in place for several decades across this area and only a few ponds were deteriorating in water clarity across these 40 years but those are particularly important moving forward for research prioritization we can also look at sign of bacterial blooms so this is an image I generated that shows each of the states across the U.S. where each state is represented by a hexagon just so that they're consistent in size and each one of these hexagons is also a pie chart that shows the percentage of water surface area that it was experiencing sign of bacterial blooms for the year 2019 and this can be really helpful for us understanding national scale patterns across space and time so this is just showing a single year but we're able to generate these maps from 2016 to 2023 and plan to continue doing this moving forward and this analysis is based on over 2,000 lakes across the U.S. so even though Sentinel-3 which is the the satellite we were using to generate this product Sentinel-3 has a spatial resolution of 300 meters but there's still thousands of lakes across the country that we're able to observe with that spatial resolution and with this we can identify states that have relatively higher temporal frequency of sign of bacterial blooms including Maryland, Florida and Oregon some of these are well known to have frequent sign of bacterial blooms such as Florida and Oregon but others including Maryland and North Carolina were relatively surprising and then looking at the state state scales results we can see which ponds are experiencing frequent sign of bacterial blooms contributing to these higher state scale averages we can also look at Sentinel-2 with the Sentinel-3 work we've been able to take that product to operational use where we're generating Sentinel-3 sign of bacteria measurements on a daily basis and releasing that to the public and it's used by many states for decision making and resource prioritization but the question we keep getting asked is for finer spatial resolution data so the finer spatial resolution data has a couple benefits first of all we're able to look at more lakes so instead of 2,000 lakes which we can observe with Sentinel-3 we have over 150,000 lakes and reservoirs across the U.S. that we can observe with Sentinel-3 and that's a pretty conservative estimate it's likely many more than that that we're able to look at but additionally we're able to see more of the shoreline and also more of the narrow reaches of lakes with finer resolution data so this lake here on the left is Lake Anna in Virginia in the U.S. and the product that's being shown as the maximum chlorophyll index which is giving us an idea of how much chlorophyll is in the water column and with Sentinel-3 we are able to observe this lake but we're only able to look at the more central and larger portions of the lake and we're not getting any information on these narrow arms and reaches of the lake nor of the area closer to the shoreline and both of these areas can be problem areas where cyanobacterial blooms or algal blooms more generally tend to accumulate so this additional product is really useful for being able to collect more information about blooms at more lakes and within lakes that were observable previously and I just want to leave you all with this which is just kind of the capabilities of the NOAA Coastwatch team where we're able to provide streamlined source for users to access and interpret satellite data so just looking up NOAA Coastwatch can get you a lot of information and there's also a lot of training courses that are offered that can be really helpful for helping users understand the data that they're getting and also how to generate their own products for their own areas moving forward and we look at both coasts or not both but we look at coastal inland and also ocean applications so we're across a large gradient of water quality observations and we also have a really large group with a lot of different expertise so a great group and a great resource for accessing Earth observation data great great thanks thanks Mack and it was very impressive what you all do with the different kinds of satellite systems in your work so yeah I look at the time that we had overspend a little bit but anyway I would like to thank all the speakers for explaining all the background and also showing some real world application of the satellite data in the field of water management so we now move to the Q&A session and panel discussion and we have one question from the audience so from Joff to Brian directly so first of all of course he thanks you and then he asks could you please expand a bit on what actions and decisions are being taken as a result for the better understanding of the water levels and flows great thanks Jeff great question well a few impacts one the the biggest impact is our goal is to have China particularly but also all countries of the Mekong to share their dam operations data in near real-time so we think with more transparency more light shining on these reservoirs more socialization of the data it becomes normalized and and much more acceptable and less controversial to share that data and today it has been very controversial to to share data particularly from China even though the downstream countries have asked for decades so in September the Mekong River Commission and perhaps Zotia can speak more to this had a meeting in Beijing with their counterpart organization there the Lanshan Mekong cooperation mechanism where the result of that meeting was a pledge to share dam operations data by the end of the year and we haven't heard any details I'm not sure if any details are known other than a pledge but we're you know we're patiently waiting for that day when the data is shared and then we'll think about what what we do and what our role is in this so that's been I think that will be the greatest impact but others are China has increased its data sharing for river gauges as a result of our early warning efforts to hourly reporting not just once a day but now twice a day and that's important for again providing enough time for downstreams to adapt downstream communities to adapt to changes around them the the Mekong River Commission has published our data in a study on low flows and now it's become part of the official discourse that both dam impacts and climate change are impacting the flood pulse or the monsoon effect of the Mekong and or of the river system so dam impacts during the wet season are bringing the river level down climate change is bringing less water into the system as well and so that that now is part of the official discourse and we think we've played a role in that but just to provide a criticism I think that's true of the the wet season but in the dry season those increased river levels that we're seeing throughout the basin as a result of dam releases those aren't related to climate change that's just that's entirely driven by dam releases and it's having a major effect on local ecologies and communities and we're going to be shifting our efforts to trying to impact the discourse and planning on on this area particularly because Cambodia is now committed to conserving and preserving those flooded forests even as they're dying and that can't be done without greater transboundary cooperation great great thanks thanks Brian for elaborating on this maybe Sosia from Cambodia you have anything to add here I don't know what actions are taking for example for the currently existing high flood season in Cambodia maybe you can say a few words here yeah I think Brian had already been concerned about the data sharing information especially from the upper part country of the Mekong river especially from China but not only concerned from China but also now the lower Mekong basin especially from Laos, Cambodia, Thailand Cambodia and Vietnam also concerned about the many high flood power that have been constructed in the military as well as the mainstream especially in Laos now we have proposed for three that are new than one more than there is concern in the future of not natural flow anymore but have been concerned about the high flood power dam packed for the river of the Mekong thank you thank you Sosia let me see if if there are more questions I have another question to Ilz so we have seen a few examples you show very nicely from different countries where Earth observation based water quality products are finding its way to monitoring and reporting so what are to your opinion the greatest barriers to start using these EO based projects in real world yes this is so during one of the water force webinars we organized a survey and according so we were asking the participants about what their opinion was related to this so so according to the according to the participants the largest barriers that they recognized were coming from the missing legal framework missing technical skills then limited trust and not aware of satellite observations so with respect to the legal framework as I presented in Europe crucial steps are already taken to include Copernicus and remote sensing in future directives so and with respect to technical skills I think more capacity building and hands-on training is required um not only access to data but also access to tools um yeah and one example is the the telescope to the Belgium platform that I showed where you can access data and products but also tools like users can ask for a virtual machine their example Jupiter notebooks that they can build their own workflows with open EO which is an ESA initiative but which will also be implemented in the future Copernicus data space ecosystem the new Copernicus platform so there are steps already taken then with respect to limited trust I think that is work or R&D efforts are needed to provide uncertainty measures and with with the satellites base products and also there is a need for more in situ data for validation of the satellite-based products and and also in situ data covering different optical water types different geographical regions and then with the respect to to raising the awareness I think initiatives like what the IW the IWA is doing right now here which is very much appreciated but also the UNESCO or the not UNESCO the UNEP World Water Quality Alliance is doing Geo-Aqua Watch is doing so these are all great great initiatives that will help us overcome these barriers so great and that that was a great summary which I can only yeah what's knowledge and then support here so we have another question for to Megan so to your presentation so what trade-offs do you consider when deciding whether to use a commercial or freely available satellite platform yeah so our preference is always the freely available just because it's so much easier for stakeholders and partners to be able to access the imagery and for the most part those are the operational products that we're defining but with some scenarios and some ecosystems that we're monitoring the coarser spatial resolution of the freely available satellites just isn't sufficient for what we're trying to do and as you saw one of the biggest examples of that is with our our seagrass work so the seagrass beds are just so small that even some of them aren't captured in the two meter data and so to be able to try and use kind of 10 or even higher resolution data it's certainly been done in larger and more dense seagrass beds but to be able to capture so the some of the smaller heterogeneous areas and really capture the edge of seagrass beds we have to use some of the finer scale data and then even within that looking at the temporal resolution is also really important so with the freely available data that's collected continuously and consistently over time but with for example with the Maxar worldview two and three platforms those are what are referred to as point and shoot sensors meaning that data is not collected continuously and that's because of data storage and transmission limitations so we kind of have to hope that there's an image where we want it in the archive or we have to task the satellite for a future image and so there's not kind of this consistent retrospective data set for us to be able to look at over time and with seagrass beds generally they're slower changing than things such as cyanobacterial blooms in the water column so it's not as much of an issue but these are the different things that we have to weigh in trying to decide which of the platforms we want to use and always stakeholder uses in mind and at the forefront of our decision making but in some scenario in some situations it's just not feasible for us to be able to use course of resolution and free data as we have to find other avenues for accessing finer spatial resolution commercial products Yeah thanks Megan I also think that we need to have like this yeah the whole picture we can only serve with different kinds of satellite systems we also can use this SAR or the optical data to supporting the water environment monitoring yeah so very interesting I think we can close that say this question answer session thanks for all the valuable insights and if there are any further question just get in touch with one of us to the speakers I think you have all the email addresses in the presentations or just contact the IWA in case you don't reach out to anybody of us so then we can move to the final topic of our agenda today which is a presentation by Charles Sawyer from Ursk so he will present today about the Sentinel benefit study short steps which I can warmly recommend because we have been part in one of the reports dealing with the water quality management here in Germany and it's supporting us really in highlighting the benefits of using the Earth observation data so really appreciated this and just the short words to Charles so during his long and varied career Charles has held senior management positions in the space industry like Astrium, EADS or Airbus as well as numerous representative positions in the UK and also in Europe and he was previously a direct job for Ursk for over 12 years and he has now served on many EU consultancies and industry representative groups he also spent three years working for the European Commission where he was responsible for supporting space policy and also in particular the creation of the GMS now Copernicus initiative we are benefit now from so please Charles the floor is yours thank you very much Karin you hear me okay good okay so thank you very much for the opportunity just to present a little bit on what we're doing today I'm as Karin has said I was the Secretary General of Ursk and as Ursk we developed this project with the European Space Agency and indirectly the European Commission called CEPS which is looking at the benefits of the data coming from the Sentinel satellites and my introduction here is always well there are always these big cost-benefit analyses which are very much top-down analyses and the politicians bought those arguments but I would not have done I'm very glad they did buy them but so we talked about doing a bottom up where we look at the value created by a single product or service and we look along a value chain in order to evaluate what's going on and to understand how that's benefiting the users the secondary users and society and as part of that we've done now 25 plus cases we've moved beyond just looking at economics I'll explain a little bit more everyone's interest in the numbers but I think we had an excellent example just now of the benefits which are not economic and we found in many cases the ability to have a wide synoptic view from satellite data leads to data sharing leads to breaking down barriers between organizations and the creation of new platforms and as Brian explained just now that's very much an objective of the work they're doing and as part of this we've done some cases on water quality management and I just wanted to highlight one or two of those today so there is the a picture of the different cases that we've been done almost all in Europe one or two outside we are interested in Europe and one of the reasons I wanted to be here today was to explain about the possibility of new cases and if people have cases that we could look at so there are two pillars to our work one is the value chain so clearly we start off with the service provider then we have a primary user and this is the key actor in this because what they are doing is fundamental to be exploiting the service that's being generated and being used and one of our conditions is that this is operational so that there is an understanding of what's going on and how the data is being used and how downstream further organizations are benefiting from the work the primary user is doing and then citizen society are benefiting as well so this is one of the values this is the example of the value chain then we found out that although everyone as I said is interested in the numbers there are soft benefits which in some cases are maybe even more important than the economic benefits so we divine this methodology where we have six dimensions of value so the first one is the economic which is basically those that can be monetized where we can put a number on it and then environmental benefits regulatory benefits innovation and creation new business entrepreneurship or changing organizations advancements in science and technology research and then the societal benefits so now what we do is we take each of those tiers in turn and we try to understand what's going on and allocate or understand benefits in relation to each of these six dimensions so I mentioned we've done a number of cases linked to water quality the first one was in in Germany in Baden-Vortenburg and here in fact Karen's company EOMAP is the service provider and we worked with EOMAP in doing this and the second case was in Finland which Ilse mentioned earlier and the Tarker service which has been put in place so in each of those and monitoring lakes but as I think most people here would appreciate the wide area coverage of the satellite data enables much many more lakes to be monitored even if the in-situ data is not replicable so this is complementary to in-situ data in Germany the the budget allows monitoring about 15 out of 270 lakes this is in Baden-Vortenburg sorry not in Germany and in in Finland there are some many thousands of lakes and only a few of those are monitored using in-situ analysis so you're replacing the precision of the measurement with a much much more frequent measurement and over a much wider scale so in Germany we looked at this and we were puzzled why the agency the environmental agency was using the satellite data when it wasn't helping them in their daily work as Ilse has mentioned the water framework directive did not recognize the use of satellite data and whilst Finland have adopted its use based on their expert experience in Germany they follow very much the regulation but they were still doing this work anyway and the result we identified because it benefits the agency itself so they're willing to put budget to this monitoring to the benefit of the agency and keeping the citizens more accurately better informed in Finland the problem is much greater there are many more many more lakes and inland waters so again the benefit is higher it's being used in the reporting of the water framework directive so here along the bottom you see the benefit in monetary terms and also our assessed scale of the benefit in each of the other dimensions now we'll shortly be publishing a third case on this from the Netherlands but what we've gone on to do is to look across the cases so the fact that we've got three cases we've got other cases which are to do with water and I'm really interested to move on to water management rather than just water quality but a transverse analysis so looking at what we learned from across these cases extending that as far as we can to other EU countries and understanding what are the similarities and differences between what the countries are doing why is the uptake in some countries and not others what are the factors determining that the geography is clearly one we were discussing yesterday in the Netherlands the the lakes are much shallower so they get warmer but turbidity is more of a problem high intensity agriculture means there's a lot of a lot of runoff a lot of issues to be dealt with the government structures in the countries the legislation the cultural factors and of course the socioeconomic factors what what are they used to so we're currently working on on that and if you have any further questions please don't hesitate to contact me findings are available on the website and if you have cases we're very interested to to hear about and to discuss this further with with people if they're interested thank you Karen thank you very much as I said I highly recommend this also it's a very nice way to wrap up the project and the benefits of the earth observation yeah so I think we are now coming to an end there's one question from the audience from Cetric here to Megan maybe you can interact via email so yeah or do you want to say something we quick Megan if you are still here he stepped out ah she stepped out okay so then thanks again so we have seen different kind of applications like large-scale cyanobacteria monitoring or small-scale sequence mapping in the US supporting regulation monitoring nice web applications and also how the satellite data we serve for disaster risk reductions in the MECOM person so this really underpins the benefits of what you can bring and from a very objective and transboundary point of view we also discuss the obstacles to fully exploit and make use of the benefits but we all know that in combination also with different data sources like modeling and environmental knowledge can be really supportive in delivering the valuable insights so I want to close here the thematic session I will pass over to Erin if she wants to say some final words about upcoming events so thank you all for your attendance on my side yes thank you everybody for joining I won't keep you much longer again I just want to say thanks to all these speakers Karen thank you for your moderation and for all the attendees and your questions and just trying to decision we really appreciate it we hope to see you engaged with the community I practice some more in the future so once again thanks for joining and please do continue to enjoy your days and your week bye everyone bye bye have a nice day thank you bye everyone thank you bye