 Welcome, everyone. This is Dr. Samuel Aguida. I'm the IWA Strategic Programs and Engagement Manager. So this is a webinar co-organized by the International Water Association and the Horizon 2020 Project Prime Water. And the focus of this webinar is the end user outlooks on Earth observation. So some information about this webinar before we start. The webinar will be recorded and made available on demand on the IWA Connect Plus platform with the presentation slides and other information connected to this session today. The speakers are responsible for securing copyright permission for any work that they will present today, for which they are not the legal copyright holder. And finally, we would like to stress that opinions, hypothesis, conclusion and recommendation containing the presentations and other materials are the sole responsibilities of the speakers and do not reflect the, necessarily reflect the IWA's opinion. So some housekeeping rule. On the bottom of your screen, you'll see a chat function. This is for a general request and the interactive activities. Please feel free to introduce yourself there and let us know where you're from, what's your job and how do you use Earth observation in your everyday job. The chat box is used to send questions to the panelists and we will collect all these questions and answer them during the moderated Q&A. And just to know that we cannot reply to race and so please do not use this function. During the webinar, we will use the collaborative tool group map and my colleague is adding this link into the chat. Please log in now as this will be the key tool that we will use today. And for you to start working with the group map, we have created a very short ice breaker activity. So you should be able to log in in group map and add your name by clicking or where you are based in the world. So I'll give you about two minutes to do this and please do let us know in the chat if you are having any problem with this. And the group map can become a bit crowded so I'll keep moving around. If you cannot exactly click where you are from, please don't. It's just not a problem just for you to see how if you can log in and use this tool. If you have already added your name, you can click on it and then you can share with us your company, your title and also how do you use a heart observation in your work. And I see some of you are really started feeling. So thank you for that. So I'll give you a couple of minutes for that. Okay, I see the map getting busy. We have about 40 seconds to finish this. So over the course of the webinar, we will keep using this tool. You don't actually have to re-click on the link. You can just move you around in the other section of the group map. So just keep this open in your computer because this is all your phone, whatever you are logging in from. And we will keep using this during the session. Okay, so while you keep filling your information, I'll go back to the presentation. So today we have a very busy agenda. Apostolis from MBIS will follow my presentation with a presentation to set the scene. Then Evangelos from MBIS will talk about the prime water operational platform with case studies examples. The panelists will then be involved in a moderated discussion and Q&A where we will answer to any questions that you may have. And then we will do a group map activity and my colleague Jordan will then wrap up the session. So today we are joined by expert panelists who have kindly accepted our invitation to share with us their expertise and knowledge. Roini Ganarkar, senior technologist assistant, Forest Service of India, Ministry of Environment, Forest and Climate Change. Jordi Crosser-Rero, head of innovation at ADASA and president of the Catalan Water Partnership from Spain. Fabian Chang, CEO and funding partner and director of Aquaintel from Ecuador. Evangelos Spiracos, who is the associate professor of biological environmental science at the University of Stirling in Scotland here in UK. P. Somassekar Rao, director of Advanced Centre of Integrated Water Resource Management at MWRD in India. And then finally, Apostoli Simas, managing director of MBIS consultant engineers in Greece and Evangelos Romas, head of the research and development unit also at MBIS. So without further ado, I'll hand the floor to Apostolos who will present the topic of this webinar today and we'll set the scene. So I'll stop sharing and Apostoli Simas, the floor is yours. Hello, on our site. Thank you for happy to be here and sharing our insight and our results from a prime water project in this webinar. I'm going to set, as Samela said, set a little bit the scene about mostly about the demonstration that will follow afterwards from Evangelos Romas and just share a few words about what is prime water, what we've been, prime water is a research innovation project. It's almost, it has almost completed its lifetime and has generated, had produced a lot of interesting results that we will hopefully like to share with you today. The focus today will be mostly on the operational services that came out of this collaborative effort generating platform with tools for hydrological hazard exposure and ability reduction in water. So the focus was mostly on inland water systems and what we've been working all this period is, was to combine satellite data, mostly multispectral derived water quality products with course appropriatory data that were available on the ground to generate forecasts of water quality and quantity of course attributes and then furthermore to go downstream in this chain and repurpose all this information into specific services for the case studies that we've been working with and this is what we would like to share with you today and initiate a discussion around that. Very, very quickly a lot of different components are used in these operational services, different types of models different types of hydrological models different types of earth observation data new techniques have been tested and have been introduced operationally in this system and have at the end of the day a credible multimodal chain that can generate these forecasting forecasted information with aiming in a prediction time of short to medium forecasting period of up to 10 days. A lot of science has been done in these three and a half years as mentioned before testing a lot of different approaches trying to elicit and identify suitable ones for case studies and the applications that we were looking at. So that's a very interesting component but mostly as I said our intention today is to share the final outcome of the form of the services that have been produced. So the water quality intelligence suite as we call it has some distinct features and that is to connect all the information that is needed with a very, very central role played here by the earth observations and provide strong let's say monitoring tools to fill in water quality information gaps in time and space and then as mentioned another very clear feature included in this platform is the forecasting services hydrological forecasting services hydrological forecasts water quality forecasts within the lake as well domain and of course finally based on those forecasts specific services targeting specific requirements needs those services are spanning across the whole watershed so we proclaim here the concept of the watershed digital twin starting with meteorology and ending up to a specific downstream service. Part of these services and attributes will be demonstrated later on and hopefully we believe and we hope that we'll trigger beautiful discussion today with all the panel included here is a very quick overview of what is deployed those services and some of those case studies will be presented just immediately after by I hope I provided a very, very quick but comprehensive overview of what is we'll have it either for the next 15 minutes 20 minutes thank you so much for that and I hope you enjoy the presentation that will be given by and happy to have a discussion immediately after. Thank you. Thank you. In the meantime I want to remind all participants to please add their question in the chat box in the sorry in the Q&A and if you are having any problems with the group map or the zoom please let us know in the chat. Good afternoon everybody I think you can see my screen so I will jump into the operational platform of Prime Water you can visit the link provided here in Prime Water we have five case studies in the United States and Australia in Europe and I will demonstrate you the operational services that we have deployed the monitoring and the forecasting model and I will start with the monitoring tool and I will jump into into Melbourne so this is the western water treatment plant in Melbourne you can see here in the screen a large number of small ponds that often feature algebraic events so with this we were able to quantify some critical water quality parameters here on the map you can see an imagery from sending a tool and the parameter is chlorophyll so by clicking on the map we can quantify chlorophyll concentrations in any in any pond we are also using we are using a lot of missions and the platform contains images for five years in the past so you can also explore the variability of its parameter in a selected point in the last years other parameters that we are able to quantify are apart from chlorophyll turbidity in NTU, total suspended matter absorption, sagittites death and heart flagellum indicator which quantifies the presence of cyanobacteria with that observation we are able to have around two images per week combined but this depends on cloud conditions so we can expect around 50 images per year I am now proceeding with forecasting tools that we have developed in flying water and I will jump into Lake Hume in Australia to present you the hydrological forecasting service so this is Lake Hume and these are all the absolute cuts that contribute to this reservoir we have set the hydrological model which uses a methodological focus from ECMWF to provide hydrological variations for our case study by clicking on this caption which contributes directly to the reservoir we can see here the discharge for today and the next 10 days so we are talking about short 10 days focus on the discharge and the temperature we are also able to quantify nutrient loads from the catchments like nitrogen, phosphorus and suspended sediments and these are very useful information for the water quality modeling that we are performing inside the reservoir and last comment about the hydrological model is that what we are looking at right now is the deterministic forecast we have also probabilistic hydrological forecast so 51 different ensemble members and as you can see here we have instead of a single value a set of possible values and you can see that the uncertainty is increasing as the forecasting horizon increases to the this let's say modeling cascade is the reservoir modeling I will now jump into Lake Harsha in the United States and here using the hydrological forecast from high model we have run here in Envis coupled hydrodynamic and water quality model here you can see the chlorophyll A values for today and the next five days by clicking on a point of the map we can see how what is the value of chlorophyll for its point and how this will evolve in the next five to seven days this is a coupled hydrodynamic and water quality model the first thing is to resolve the circulation pattern so to resolve how water moves inside the reservoir and then we run the unification model which provides chlorophyll and also nutrient levels inside the reservoir as I said we are talking about the three-dimensional model so we are also able to quantify parameter concentration of parameters as you can see right here in any given point we can have a profile of how this parameter variates with the depth and also we can have cross sections in the entire let's say modeling domain these models also use are using data simulation techniques whenever an earth observation image or in situ data sets about how the chlorophyll concentrations are available these are assimilated into the models so they are improving the performance of the models and their forecasting here I will state the same reservoir and in the water quality model but this time with another type of modeling which is the data driven, the machine learning model so what we are doing here is that for specific areas of interest in the reservoir some machine learning models that are able to again forecast the chlorophyll values for the next seven days so we are using again methodological forecast hydrological forecast and by using different types of models like random forest or Gaussian process regression we are able to provide a better forecast, so exactly as in the 3D models by clicking on each of the specific points we can have we can have the concentration of chlorophylls for today and the next 10 days the only difference is that we are talking about specific points not the entire reservoir and these points represent only the upper layer of the reservoir because they have been trained with F observations to provide only the top layer of the reservoir and another nice feature of this model is that they can provide us with some estimate some confidence level so you can see here the 18th and the 19th confidence level so instead of having similar value for our prediction we are able in this way to quantify the uncertainty of our forecast now moving moving down the next functionality that I am going to present in the same reservoir is the early warning functionality so this functionality actually garners information from all the monitoring and forecasting systems and provides a very quick overview for the reservoir manager of what is the reservoir so here we have three different areas this is an area where water is abstracted from there is also an area of interest this is a swimming area for Lake Hassa and this is the downstream the downstream end of the reservoir so for it all one of these points we can have a very quick overview of what's happening is the reservoir we can have some indicators for example the Fittablancom production indicator which classifies the status of the reservoir depending on some thresholds you can hear we can see here that we are in a moderate let's say status between 12 and 24 milligrams of chlorophyll and also we have some other indicators useful for example in the identification image we can see that the graph of chlorophyll is expected to rise in the next one or two days by bull percent so a very nice tool for the for the manager to see at a quick glance what is happening in the reservoir and of course you can go back to the analytical models to see more details the last functionality the last service I would like to present you is in Sardinia in Lake Mulagia one the special feature of this case study is that we are talking about two interconnected reservoirs so this one on the southeast Mulagia reservoir where water is being abstracted for various uses agricultural potable water industrial water uses etc but there is also another reservoir here on the north where the water managers are able to transfer water from this reservoir to the downstream reservoir so this this transferring is usually happening based on water balance criteria so what are called is usually kept out of the creation but here together with the ANAS which is the water manager of Sardinia Waters we have deployed these water blending optimization tools so with these tools with these tools the water manager is able to set some environmental criteria some water quality thresholds in the reservoirs about chlorophyll nutrient dissolved oxygen etc and here on the left side is what ANAS has the points where ANAS has set its environmental constraints as you can see we have set constraints in both reservoirs both upstream and downstream reservoir and what this tool does is that it examines using the three-dimensional models deployed it examines what happens in the base scenario the base scenario is the scenario where no water is transferred from Pimendoza but also it examines a series of another ten scenarios which has increasing let's say volumes of water transfer from small ones until in the last scenario this is a volume close to the capacity of the tuner so in this tool everything seems to be ok in the base scenario so for the next five days all constraints are met but if I set a constraint a two-straight constraint like I don't want chlorophyll consideration to exceed the five micro constraints literally in the monogym abstraction so then this tool informs that the base scenario so if we don't transfer any water from the upstream reservoir we are going to fail to meet this constraint so the user is prompt to make some water transfer so this is a very useful tool that has been set up with Ennis and allows us to take into consideration water quality criteria in the decision making of complex interconnected reservoirs so that is all for my side I hope we are on time and we can it was a journey a quick journey around all the case studies that we have worked within prime water we've tried to be it was a very fast track let's say journey to communicate a lot of information and mostly to demonstrate what might be the possibilities from using advanced services that are based on remote sensing earth observation but also by using approaches and technologies that are integrating earth observations and forecasting capabilities I think it was a good overview we're done here and the floor is yours some will enter in thank you and even give us for your presentations and the presentation and the demonstration I'm going to ask all the panelists to come on screen so that we can begin their discussion and I'll also remind the attendees that they can ask their questions they can submit their questions in the Q&A section so that we could also bring them into the discussion so again thank you the MBS team for your presentations and I know that in a very short time we've heard a lot we've seen that the prime water operational platform combines a lot of different things so that water managers can really make informed decisions we have different models we have early warning functionality we have the blending optimization tools we have the combination of in situ with satellite data and the models to make sure that the decisions can be close to accurate and reliable as possible so firstly what I would like to ask is any of the panelists can just give your thoughts exactly how do you see the prime water platform how receptive are you to what you've just seen in a demonstration anyone can begin I will begin as an end user it's clear that the use of a satellite with other systems it's improving the control of water quality mainly as we have seen the application in environmental quality it's clear that probably one of the biggest revolutions has been not only satellites, satellites have been using since many years but link satellite image with artificial intelligence and local measurement or local data to be able to generate these forecast that only with satellite years ago was not possible so I think that the use of prime water platform probably we will use more application for the platform in the next years thank you Jordy Fabian I see your hand is up yes thank you very much I think that the use of earth observation platform from prime water it creates value to water authorities and also water managers and industry specifically in agriculture activities offering them actionable data because the access for performing water test analysis in remote areas becomes very difficult sometimes so using earth observation techniques can be very useful in accessing to managers reliable data in order to optimize decision making thank you thank you Fabian to the MVIS team I want to ask one of the questions in the Q&A chat so from Sandra Ryan she's asking do water managers need to import already built models into prime water or does it already include pre-loaded systems or does it facilitate model building within the tool how would this apply to locations where environmental data collection is sparse right right technologically wise prime water couples a series a number of different types of models when it comes to the operational components so we have relied mostly in open source modeling for that so most of the models most of the models that we've been using are open sourced models hydrological for hydrology as Fabian has mentioned we're using Hype model has been generated has been constructed and supported by SMHI the Swedish hydrological institute when it comes to the water the in lake water modeling both hydrodynamic and ecological modeling we're using the 3D suites of course there are certain components that are used on a proprietary basis for example a specific remote sensing derived water quality products are produced by a specialized partner in our consortium that is EOMAP EOMAP operates its own let's say processing tools that can actually translate that old data that satellite picture conveys to water quality information so it is groundwater mostly wanted to demonstrate the opportunities that are existing using in many different ways and mostly to against challenging requirements for operational purposes what you have seen as a suite has been constructed to convey this information in the best possible way together with our partners our end user partners that contributed a lot to the final result that you have just seen in terms of how this information is communicated how this information is presented but a lot of the components are based on free and open modeling components I hope this my answer covers the initial question one way or another to come back with more details thank you back to our panelists we have a very diverse panel in the session today so I want to ask and maybe I will point this to Vagelis Spiricus how do you see because you are in Biological Environmental Sciences so how do you see the use of Primwater in your context in research of this platform thank you for the question I am at the Biological Environmental Sciences Department but my background is in physics but I am very much interested in the application indeed also the development of these tools and thank you Vagelis for giving a nice overview of Primwater and the work that you have done in this project for going back to your question as a reflection as well to the overview we have seen and I think it was great to see a simulation of a combination as well of satellite data earth observation data with the modeling part and this is something that it really adds value to the final product in terms of research it opens many many different opportunities to explore the products further put them maybe in the climate context as well to see like long term changes of water quality and how this is associated with the hydrodynamics or other variables that are tested here so this is in terms of the research putting them as well like this opportunity for looking a bit a bigger picture look at other systems as well neighboring systems maybe like why one lake behaves one way and a lake in the same catchment for example behaves in a different way so this really provides the tools to answer some of these questions and also I imagine like further research needed to see how these tools can be transferred to other systems to other occasions to other types of waters Thank you Vargilis so Dr Rohini I want to ask you because you also you work in forestry forest serving so given what you've seen today how do you think this can be applied to forestry Thank you Aryan for the question and thank you Abhis for such a great presentation and other products they have been providing in the forestry sector we basically focus on the forest environment typically of all over India but being a biotechnologist I have few of the base questions I can say because I totally understand that previously it has been said that one lake behaves differently and the other lake behaves differently so I think the microflora is the base component which actually impacts the lake secondly I totally have been developed but I have a query that the simulation modeling they are being providing for the next predictions so are they totally in a positive way sector or they have some sort of drawback kind of thing so I have this mid query because as earth observation has opened one of the dimension in one sector but we can't ignore other parameters like ground validation is one of the important parameter the environmental impact which is totally affect the environment so these are the base questions and the question you have asked that the use of this product in our forestry sector so it will be one of the helpful product I can say to get a rough idea regarding the impact of the forestry in our own forest on that typical environment typical lake or reservoir which is present in that forestry area so that's it I would like to complete my answer thank you thank you Rohini do you have a response to Rohini about her question about the models being used to generate these indices in the operational platform right models there are very very there is a very large number of different types of models well models are trying to represent to describe processes in a physical system models try to represent the end result of a response as a reaction to some triggers there are very very a wide range of models can be used here in our case the selection of the tools that we have worked with has been dictated by the specific let's say challenges that as a project we had to address so the focus in prime water was mostly algae bloom outbreaks phytoplactin outbreaks in freshwater systems so the selection of the tools that we have used has been made so was to let's say pollute in this modeling and assess in this modeling chain those tools that actually can provide us some good information about can describe these processes and provide us with information about the targeted parameters or indicators so for algae bloom events for example we have worked with ecological models that provide information mostly about physical chemical parameters in the water targeting chlorophyll A for example using these parameters mostly as a proxy indicators to describe or associate with possible phytoplactin events and try to work around those concepts and elaborate those concepts a lot because although there might be tools and models that can be available around going further down the description of the physical systems into more detail however models need a lot of data as well to work well so the availability also of data that can be used to train or to validate a model also is a very important consideration that influences the selection of the tools in a case study so all those parameters have been taken into consideration in order to reach to the specific let's say composition specific let's say selection of the tools that have been used in framework Thank you Apostolis we received a few questions some other questions from the audience but as Samuela mentioned at the beginning we will compile a Q&A report for the questions that we were not able to answer during this discussion and now we will move on to the group my activity which I have heard which I've heard that is going really well so we will continue the discussion there I'll let Samuela share her screen Thank you Erin, I'll just keep sharing the screen just a reminder to all the attendees to add your input into the group map one of the questions from the group map how are these data accessible well yes they are open access but is there any cost related to the operational platform this is for the mbis team the use of the operational platform Apostolis, oh okay Hello, can you hear us? Yes I can hear you No I can't That's okay I can hear you Yes I can see you You mentioned about the cost Yeah are there any costs related to the primary platform? Well yeah the operational services right now have a commercial branch can be used in some cases for targeting operational requirements so in that case there are costs associated mostly with the development of credible modeling so models do not work on their own so let's say one cost center is related to calibrate to validate depending on the tools that are used and of course there are also costs associated with the earth observation data for water quality also as has been described the source of this information comes from the Copernicus program also the NASA services Sentinel and Landsat satellites the primary the raw data that are free of charge need further post processing with specific algorithms in order to be translated to the necessary information whether this is chlorophyll temperature or whatever else parameter can be extracted from this information there are some cost centers that are associated with those aspects I've just mentioned when it comes when prime water services comes as a service to an end user okay so then my question and this is a question also to the panelists because that is that apostles just broke down for us give us a bit of detail how the primary platform has been developed including the cost of other things do you see this as a barrier or is this or do you think that this is a misconception for implementing or using or tools and services would you consider these costs as a barrier for the uptake of the services that anyone can answer but I would like to hear from the panelists on this if it's for research yes you know I don't think research or academia is one of the targeted end users in this project that's understandable Jordi I think it depends on the application because for example if you want to monitor a dam reservoir and you have to make analyzing a lot of points this is not cheap if thanks to a system you can a health observation system you can take one sample to validate the health observation with local data and then you can use your system to extrapolate or to model the evolution of the contamination this is cheaper of course it depends on the application probably one of the main limitations of health observation techniques is real time they have which has commented that they have two images per week in some applications this is not enough in some applications this is much enough so according to the application I think cost is not a problem okay thank you Jordi and this right always there is a cost concern around innovation innovative or new applications and I fully agree with Jordi this is really associated with the particular application and the needs around that so there are cases where water quality issues are becoming very very critical in water supply systems or in other water related industries and therefore being proactive being in a position to act before early enough before these biological let's say outbreaks evolve fully trying to mitigate in this way the impact out of these events really makes not only environmental good sense but also very very good sense in terms of the economics around that we had the chance to work quite in detail on those aspects together with our end users trying to understand how whether of course in a first level and how they could actually see any value out of those services in their everyday let's say operations a lot of this information will be published and will be available also in our project reports but just a very quick sharing a very quick let's say overview I'll bring an example for the recreational industry where let's say the swimming areas are really their commercial use for visitors are really impeded by water quality issues here in these cases there are really important issues related to public health since algae blooms harmful algae blooms they produce toxins can affect visitors, streamers recreation people and those costs are really associated with health costs so running a very very thorough economic analysis there somebody can see significant benefits for acting early enough warning people early enough banning the use of water early enough so beyond let's say conserving environment beyond protecting public health also ensuring cost efficiency in this particular let's say industry or let's say activity well similar approaches and similar let's say cost efficient opportunity windows exist in many other water related and water dependent industries or water activities beyond let's say the obvious environmental or public health benefits that can be observed or can be seen in these systems but again it's very true depends on the particular case and the severity of the problem that an area faces when it comes to water quality thank you for that again to the panelists I hear in the risks section I see cybersecurity as listed and with the growing digital transformation of the water sector how do you see EO playing a role in this maybe how do you see this as a risk or maybe how it can help to change the minds of what professionals who might be hesitant to adopt these technologies because of this sure Jordy you can go ahead cybersecurity I would say an issue or a problem in all digital systems not only health observation system my feeling is that in this particular case it's not an additional risk from my experience probably there's more problem in local sensor or local measuring systems than not in digital platform providing the image and the service it's a risk of course but I would say different from all the cybersecurity issues in all digital systems understood I want to point Eves just very quick remark on there I mean water is a critical infrastructure so it is goes hand-in-hand with certain specifications on cybersecurity or other on digital systems I agree it's not mostly systems integrated systems like this one that we are presented they need to comply with general cybersecurity requirements that of course again they're user specific so each organization has its own framework its own requirements in respect of that so that becomes a strong requirement as it is considered as a digital system so most of those integrated systems has to comply with internal requirements in this domain to be accepted by a user or a specialist so Fabian I have a question here in the risks section I see someone has mentioned that low income countries especially with vast land areas hoping to rely on EO rather than local data collection and in your opinion how do you think or how do you see it for low middle income countries the prospect of using EO to also help with water management and resource management on a whole well that's a very interesting question from my experience in Ecuador implementing earth observation tools for water leak detection we have to be very smart in describing the current cost of the traditional methodology and the benefits and opportunities using new technologies such as earth observation as you can see and productivity increases so the return on investment of using new technologies supersedes the traditional methodologies so on from this perspective costs from low income countries cannot be an absolute barrier to the development of these types of projects thank you and I also want to ask the panellists from India so Dr Rohini and Dr Rao you can give your opinion on the use of EO in low middle income countries I can say that it totally depends on what sort of objective we have for a particular what is your base objective for using any application so there are many of the free softwares also GIS or remote sensing softwares also that can be helpful but at the same time I will again repeat that it totally depends on what sort of objective you have because your objective decides the type of model you have to develop and the type of data you have to in this so I totally straight focus on the use of the free softwares that we can explore more and more because day by day there are more of the apps being developed considering the large number of researchers along with the low income countries so free softwares are available so I can say that much of our demands can be fulfilled using these softwares so I will complete the answer with this thank you both Rohini and Fabian on your inputs and I think just adding to what Rohini mentioned here in the barriers someone had mentioned advertisement of the service and I think that also ties into capacity building because not everybody knows what is available out there that can be used and not everybody fully understands and somebody also mentioned that there are not many people in the water sector who are interested in having to learn how to let's say run a platform or run a model they just want the answers so how then do we translate what has been developed in this prime water model how do we get it how do you get platforms like this similar to the platform to the operational platform how do we get it to the members to the users who could benefit from it how do you suggest we break this one particular barrier of getting that information out there and and possibly just increasing capacity of any users for this I think the answer here in my perspective is continuous development, continuous capacity building because that really will train will train users towards against new technologies, new approaches there are a lot of very good tools available there are very good there is a lot of information nowadays available so continuous development and continuous capacity building it's a key component in let's say reaching out to the point of moving towards more integrated more complex more elaborated systems so I think at least this is the way that we have seen that a lot of our clients a lot of the people that we work together not only commercial but also in research a lot of the users this is how they're taking this digital journey they take it step by step they try to gain one step at a time trying to define very well and very clearly their objectives their needs and this is our understanding about our experience from all the discussions that we're having with possible users the way that they're trying to reach these goals, these digitalization let's say evolution within their organizations so a lot of different steps need to be taken each one has its own challenges but it becomes a very very large challenge when somebody tries to let's say make significant jumps towards more complex, more integrated more demanding systems both technological but also in terms of costs Thanks Apostolis this discussion about capacity building and access to platforms like this also brings me to the point here where somebody has mentioned that policymakers require highly confident EO products and we held a webinar last year about transforming science to policy and it was mentioned that sometimes the policymakers are not fully aware of what is being done the results all these results are formed are created, generated and how they can actually use this and exactly what would help them implement this be more encouraged to implement this from the panelists do you have any thoughts on how we can encourage policymakers to implement these the use of these tools and services because as we can see they are beneficial they give an all round view of water resources so how can we convince them that this can also be used to address the global water challenges Jordy and then Vargilis you are muted Jordy sorry my fault just a quick answer to the previous question I think that one important thing we have to have clear about the tools is that for being a user of a tool you don't need to know how it's been done that means probably most of the attendants are especially seeing water quality but probably none of us want to know how this tool is made inside we just want to be users and I think we don't need to make training about artificial intelligence to use the tool I think there are two different elements one is the person who makes the tool that they have to be expertizing in artificial intelligence and health observation and the other one is the user we just want to get the results and all that the tool is working and it helps in our work that is water management and then answering the current questions I think for the important thing I think is not policies is users of the tools I think the only question is if this tool is helpful for users of water quality control to make them work if it's really a decision support tool that helps us to work in this field if it helps us to make the forecast of algae blooms in a reservoir on a lake etc because at the end policies probably their only use will be if they make some grants to use the tool or things like that but at the end they will just ask the end users are you using the tool if it's useful for you or not okay and Vagelis I actually want to come back to you Jordi on that but Vagelis I will give you the floor just a quick remark on that I want to bring an example here with our policy maker the Scottish Environment Protection Agency in Scotland that they are now using an Earth observation based service for monitoring lakes and logs in Scotland and this happened was like a long journey we co-developed with them the products that were really involved in the production and the development of the products we had people from the Scottish Environment Protection Agency joining us at the university and spending a lot of time here with us learning about the tools and also involved as I said in the development of the products but also building this confidence to the tools allow comparisons with the traditional methods compare the products the satellite products with the ground data and showing that the satellite products are of high confidence but also showing that what additional value cannot that you cannot you can go you can have information about the entire system not only one point that you typically sample once every year so this is just a comment to as an example the journey we had here with the Scottish Environment Protection Agency that ended up with them using satellite based products. Thank you Vargilis Jordi I think Vargilis actually given example of what I wanted to come back to you on because not every end user is a private end user so sometimes when government agencies want to well I guess from a scientific perspective when scientists are trying to get government agencies to adopt their technologies to just show them that okay this can actually help you manage your resources better getting legislators and policy makers helps for this so I completely understand your standpoint in that maybe from a private sector perspective policy is not that important but in terms of government run resources sometimes it's very important to get policy makers on board if I could just mention that here Dr Rohini, your hand is up Actually Arina I totally agree with the points you have made actually because being in a government sector I totally agree that yeah okay the tools are helpful for us but parallely we have to be dependent on the other parameters also and also we can't publicize what sort of parameter we are using to the public domain so it's like a combination of different things I can say it's not a totally earth observation thing or the other parameters we use it's a total combination of the work that we present in the public domain but there are some hidden things that we don't expose to the public domain so I would like to complete my answer thank you yes that also plays a role and maybe let's take it to a positive light and I actually see quite a few benefits here how do you see the future of maybe I will point this to Envis and then the panellists can also jump in here because how technology is going is constantly evolving is constantly changing and Apostolis and Evangelis we actually receive the question about how the platform will develop in the future so do you intend to include more parameters so like heavy metals especially for countries who have water quality issues well for the effects of mining and different operations how do you plan to help the program to evolve to assess these as well right yeah in prime water we have a very clear mandate around phytoplactin water quality aspects obviously this is not the only water quality concern around the globe and certainly might not be the most let's say important many other cases as you mentioned very very strong concerns about specific chemicals, about specific heavy metals or other substances however the starting point of prime water was also how to utilize earth observations and earth observations they do come together with certain limitations and the certain limitations when it comes to monitoring the surface water quality in water and this limitation goes together is associated with the optical signature of those particular pollutants that we believe so this is a very this is an intrinsic limitation of this technology it needs to read a signature and translate the signature into an actual measurement so when certain contaminants do not leave this type of signatures it's very hard to use remote sensing to actually measure those modeling of course they do have it has a lot of opportunities there and the modeling is used in actually in understanding the dynamics of those in many cases of those particular and very specific chemicals so there are opportunities there and of course prime water as a project has concluded it's a lifetime but has generated a lot of let's say good ideas that certainly can be the basis for transforming and expanding those concepts to many other domains so the answer in few words is yes there are a lot of opportunities scientifically to explore when it comes to cross cutting scientific applications and to the research as we are coming to kind of the close of this discussion I want to pose this well this question to M.V.I.S. and then I would ask all the panelists to give their just final remarks about the whole session how do you see and this was a question from the Q&A but I think it helps to wrap up the discussion also and it brings like it kind of is based on the rationale of what we are trying to do here today as well the co-design process and this was from Mary Beth in the Q&A and she asked do you have a comment on the value of the co-design process with the stakeholder from the user perspective of the process so how do you see the value of getting and use of feedback while you continue to improve the system what does that mean for you? I think it's the most important part of let's say developing an application that makes sense so if this part is missing a lot of work can be scientifically valid and viable however when it comes to addressing actual needs on the ground these let's say distance this gap needs to be filled in and there the perspective of people that they do operate they do work they do intend to use those kind of systems they need such tools because their existing practices cannot or cannot support any more decision making or they need further information to support information decision making those people in their perspectives are becoming important and very critical in developing an actual system that can be used for specific purposes so it has been in prime water it has been a primary goal to include our let's say partners in the project from the very first day in this co-development journey with a lot of iterations with a lot of discussions that actually influenced also the scientific components of the project because science was also tried to address specific challenges some of them very very very ambitious so it was a very strong incentive not only for how to actually present a commercial to develop a commercial sense but also how to streamline scientific effort trying to address in some cases very as I said ambitious requirements in certain cases so it is a very important process when it comes to completing the development of such such scientific workflows thank you can I ask the attendees as we are closing well as quickly as you can just to share your final remarks about today's session maybe I could get your final remarks yes thank you and thanks again to the Apostolis and Vangelis for the presentation and everyone in the panel for the very interesting discussion I think it's crystal clear the benefits to decision making that these tools can these methodologies can have and on the other hand it generates a lot of questions and I see challenges as well when you develop products that are specific to the needs of the sector and how you can tailor this and the cost involved after for tailoring these tools for the needs of a different sector or a different user from experience it's great to see that the products have gone outside Europe with examples from the US and Australia and have examples as well that sometimes countries they want the products to be developed by by local companies by someone that they feel closer to them not so much in the private sector but in the public sector seen examples in South America they want to have the capacity rather than being handed the products over so this is something of interest and specifically when I imagine when you develop a product with a view to sell them commercially and as a last point I think capacity building is mentioned a lot it's very important there are initiatives we have people here maybe as well from AquaWords but WWQA and other global institutions organisations with global reach try to build capacity especially for lower income countries and capacity sometimes means that that you get this trust as well by the users but I will stop here because I can go for hours but thanks again and well done for a great job to prime water thank you any other panelists would like to give any closing remarks from their side yes, Jordi just adding to what Bagalisa say I think that there's a high evolution or revolution in the last years thanks to adding artificial intelligence to health information it's clear that health information does not solve all the problems but join it with other techniques like local monitoring weather forecast etc will help water quality control to improve the coverage and somebody has said that in low income countries could help not could help but you cannot believe that without local data you will get all the information but with some local data you can get a lot of information and it's clear that in the following years more applications oriented to the end user will appear thank you Jordi hi I just wanted to add a few comments first these Earth observation tools can be also useful for insurance industry you can reduce and mitigate risks with an effective tool for the economic impact of preventing risks so it can be useful to add into the field of water related events other industries that are not usually related to water management also the in the short time midterm there is a big opportunity for satellite industry I mean this expansion of the activity of satellite industry will reduce the price and cost for accessing satellite data so it can help low income countries to get access to high reliable information from Earth observation thank you thank you so much Fabian I will hand over to my colleague just to close everything thank you to all the attendees and panelists for joining the session today I will share my screen for one more quick minute so if you are still in the group map please do complete our feedback survey I have moved you all to this screen so you will be able to see some questions if you have time to complete this the group map will stay on until even after the session so do take some time to fill that so just some upcoming IWA webinars and events we have webinar on safely managed sanitation on June 6 and of course you can learn more about upcoming water and development congress and exhibition in December if you are still not an IWA member we can share with you a discount code you will see here in the screen but also my colleague put it in the chat this is valid until the end of the year so please do take this opportunity to join other water professionals in our network and with this I think we can close the session once again thank you so much for joining and contributing to the discussion I think it was a very interesting and helpful discussion that nicely wraps up the prime water webinars so thank you all and you will receive communication from us about the recording the Q&A where we will reply to questions that were not answered during the session and the presentation of this session so thank you and have a nice rest of the day thank you everyone