The Importance Of Water Data With Peter Gleick & Rohini Nilekani | Dalberg

In the first episode, our guests Peter Gleick from Pacific Institute and Rohini Nilekani from Arghyam, join us to talk about the role and importance of water data and the trends they have observed in the sector through decades of practice. They will also discuss the challenges and gaps in the water data ecosystem and how we can collaborate better, learn from each other and bring about a culture of using water data in decision making.

Transcript:

0:00:05.2 Speaker 1: You’re listening to The Water Data Podcast, produced jointly by Dalberg Advisors and Ashoka Trust for Research in Ecology and the Environment. Your hosts Veena Srinivasan and Nirat Bhatnagar talk to individuals and decision-makers from local and global grassroot organizations, companies, philanthropies, startups, on their journeys and experiences with water data and decision-making in India and globally across agriculture, innovation, water disasters, public health and more.

0:00:38.0 Veena Srinivasan: Hello and welcome to The Water Data Podcast. Today we speak to Rohini Nilekani and Dr. Peter Gleick, on their inspirations and extensive journey in working on water issues. They share with us stories of impact, the evolution and trends in water data use and their hopes going forward.

0:00:56.5 Nirat Bhatnagar: Now, introducing to you our wonderful guests. Rohini Nilekani is the founder chairperson of Arghyam, a foundation she set up for sustainable water and sanitation which funds initiatives across India. She brings in two decades of experience in philanthropy with the focus on water, and also sits on the board of ATREE.

0:01:15.3 VS: Peter is a world-renowned expert, innovator and communicator on water and climate issues. In 1987, he co-founded the Pacific Institute, which he led as President until mid-2016. Peter has been a pioneer in developing work on various concepts. His research contributed one of the first analyses of climate change impacts on water resources, the earliest comprehensive work on water in conflict, as well as the human right to water.

0:01:41.6 NB: So to get us started, tell us about your journey towards working in water, how did it come about, what were your motivations and inspirations, and then when did you seriously start thinking about water data and how has your work in water data evolved?

0:01:55.1 Peter Gleick: Yes, thank you very much. Well, first of all, I’m a huge fan of water data. I’m a scientist by training and as a scientist, of course, data are very important for all of the things that we do. I’ve spent a great deal of time collecting data, evaluating data, using data. I published a book a long time ago in 1993 called Water in Crisis, which was a series of essays about world water challenges, but also hundreds of tables of water-related data, data that at the time was in different documents and different reports and very hard to access, and I thought at the time it would be important to collect water data in one place so that we could look at it, we could try and understand it. But over time, I’ve learned that data is not always exactly the same thing as information, and one of the challenges in any field, certainly for water, is getting good data, but another really important challenge is making sure that those data are in a form that’s useful, that they tell a useful story, but just as an introduction, data has always been a big part of the work that I’ve done that.

0:03:01.0 NB: Thanks Dr. Peter. Rohini, can you walk us through your towards water and also towards water data?

0:03:06.7 Rohini Nilekani: Yes, Namaste and thank you, thank you Nirat, thank you for this podcast. Very honored to be here with Peter. So my journey began because I was trying to find a way, I had started a vehicle for my philanthropy and was looking to do something more strategic with that endowment, and it suddenly came to me that water was the most key resource in India that affected people at large, but also the economy and so many other things in its wake, and that’s how in 2005, Arghyam the foundation decided to focus on water, and I’m glad we did, because at that time we were the only Indian foundation exclusively focused on water.

0:03:48.5 RN: Data came into it pretty quickly, because when we set up the open public resource called the India Water Portal, which was a knowledge platform where people could contribute knowledge, share knowledge, discover knowledge about water and data had a lot to do with it. And one of the first things I remember that we imported onto the India Water Portal was the 100 years metadata on the Indian monsoon, and we tried to present it in a more readable format, we experimented with some of that, and it’s become one of the most important tools for researchers to use even today. So that was our first brush with data, but then we began to do a lot of things, and I come to data from a citizen’s point of view because unfortunately, I’m not a scientist. So I like to look at data and we like to look at data in Arghyam as to how can we use data, especially data as a public good, to serve citizens and society better.

0:04:47.0 VS: Thanks for mentioning that because your data set is something that we as scientists still rely on, because so little of the data is in public domain. Now both of you talk very passionately about how data is so central to your journeys, both with Pacific Institute as well as with Arghyam, and so I was wondering whether you could walk us through why data is important and what role that has played in actually transforming the kind of impact that your respective organizations have had? Why is it so central to the work that you do?

0:05:18.2 PG: Yeah let me make a comment. First of all, Rohini makes a very important point. Data can be useful for science, but if data isn’t useful for the public good, then it’s really, it’s less valuable. It’s gotta be important for the public good and for public policy to be useful. I would also make the point that there are lots of kinds of data, and for the data point of view, there are demographic data on population and changes in where people live and economics, but there’s also hydrologic data on water, there’s climatic data, there’s information on how water is used or what the water quality is, or economics, the price of water, the value of water, the cost of water. There are social and political data. All of those, from my perspective, are critically important for doing better on water, because water is such a big issue. So a long time ago, there was a big debate about whether we should build big dams or little dams. Now, of course, today the conversation is, can we do what we want without building dams at all? So I started collecting data on the environmental impacts of dams, on the water use, on the size of the dam, on the power generated, on the impacts on fisheries, all of those things, and I tried to analyze whether big dams were better or worse than a large number of small dams.

0:06:46.8 PG: Well, it turned out that wasn’t the right question. Once I got the data, it wasn’t really the important question, the important question had to do with impacts on communities, impacts on fisheries, the way the dams were operated from a social and an institutional perspective, and it was a little eye-opening to me as a young scientist, to understand that it wasn’t just the data, but the information we were trying to get out of the data that was important.

0:07:16.1 VS: That’s really interesting. That’s really look at data through a normative lens to say, what do we really care about, only then does the data makes sense.

0:07:24.7 PG: Yes, that’s right. I mean, data without context is just information. Yeah, it’s just numbers.

0:07:32.2 VS: Why was that first thing that [0:07:33.8] ____ data?

0:07:35.3 RN: So we know it is very important for those who are… People like us practitioners, to understand the big data numbers, right? How much rain falls, how much water availability is there, and how much of that is usable, those kind of things are important to understand. How many rivers flow in India, big numbers like that are very important to understand, but they don’t particularly help ordinary citizens. But within a city, you can find such a huge difference between how rich people like us use water every day, up to 400 litres a day per person, and how a person in a slum, not very far from my house may not even get 30 litres per day. Those are the kind of numbers I’m interested in understanding why that is so, and what can be done about it.

0:08:27.8 RN: And I can give you a lot of examples on how, in our work over the last 15-16 years, we have tried to either unpack some of the public government data sets to really be able to arrive at some kind of civil society pathways of action using that data. For example, we know that in the 60s and 70s, there was hardly any use of ground water, right, only about 1%. And that now we are using more ground water in India than US and China together use. And we have some 30, 40, nobody knows exactly how many million bore wells in this country extracting ground water. Now, knowing that was great and knowing that it is such a crisis, but we were able to create data in a participatory… Participatorily designed ground water program where local communities, which some of our hydrogeologist partners like AquaDam, were able to enable local communities to collect data on their own aquifers and then develop social protocols on using that water, which was then understood to be limited, finite.

0:09:46.8 RN: So, some really fascinating examples of better and more sustainable and equitable use of water simply by putting data in the hands of people and giving them agency to understand how to collect it and how to monitor the water resource using simple data tools, data gathering tools. I’ll give you another quick example. We worked with the Karnataka state government on a program very early in the Arghyam days, called Suvarna Jala, where they wanted to put rainwater harvesting times in all the schools of Karnataka, which was a good idea when you thought of it as something, but then when we started collecting real data on the ground, we found, first of all, that many of the schools didn’t need it, or already had rainwater harvesting, and two, that the teachers had no clue what that thing was, which had arrived on the summer holidays when they were not there.

0:10:40.0 RN: And it was not possible for them to use it properly, without adequate training, etcetera, etcetera. So using that data, we went back to the government and they stopped the second part of that program to redesign the whole thing, and they saved a lot of money of the public exchequer in the bargain. So, we try to use data in that manner.

0:11:02.7 NB: Thank you Rohini, and thanks Peter for pointing out both the difference between, let’s say, data and intelligence. Data is not knowledge, its not intelligence, and also the need to situate some of this in real use cases, right? And that’s actually my question. So where do you see us right now in terms of maturity, have we become smarter around water decisions over the years, over the decades? And if you had to think about, let’s say, both the supply side and the demand for water data, so on the supply side, what kind of data is now available, what kind of technologies exist, what kind of things are possible in terms of analysis and even serving it in investing ways, and on the demand side, how many stakeholders, let’s say, in the pipe sector, in government, in civil society are asking for that kind of intelligence, how much are end-users asking for this in order to take decisions very differently, let’s say in agriculture, in industry, in even natural ecosystems?

0:12:00.6 PG: I have a few thoughts, perhaps. On the first question, maybe we’ll come back to this, there are still serious problems with water data, and there has definitely been an evolution in water data. We, for a long time, collected a very narrow set of water data. We collected information on rainfall and we put gauges in the rivers and we collected run-off data. We had very basic water quality data when we had water quality data at all, we’d measure the water quality for just a few components. We didn’t look much at water data. What we collected was what engineers wanted in order to build big dams, in order to figure out how to take more water out of the system for human use. They had a set of data that was important to them.

0:12:47.6 PG: And that was the supply of data at the time. In the last few decades, and maybe really in the last few years, I would say there’s been an explosion of interest in water, or there’s been a growing realization of the water crisis and the many different dimensions of the water crisis. There’s been more and more awareness, more and more activities by not just the science community, but by communities, local communities, in trying to figure out how to address… How to understand and address their water problems, and that has pushed, as you’ve described it, the demand side for water data, it’s changed in a positive way. The kinds of water data that we realize we needed to collect in order to address our problems, data about how much water we really need to do certain kinds of things, data on the ecological impacts about water, data on the economics of what water was costing people and related to the human right to water, whether we should be charging money for water at all. That demand side has changed the nature of the data that we collect in a good way, I believe, but it has also highlighted some of the big gaps that we still have in the data that we’re not collecting.

0:14:04.5 PG: Another just one important point here is, there’s also been an evolution in the way we collect it. Rohini mentioned the issue around groundwater. Groundwater over-extraction is a problem in India, but it’s also a terrible problem in the United States and in China and in the Middle East, where we use more groundwater than nature recharges, and that’s simply unsustainable over time, and we knew we were doing that, but in the last few years, we’ve started to launch satellites, Earth Observing Systems that have collected new forms of data that have really brought to light the nature of the groundwater crisis, a series of satellites called The Grace satellites, is one example where we can now see and measure and provide detailed information on the severity of the groundwater overdraft problem and where it is.

0:14:58.2 PG: And that has spurred a whole set of really interesting conversations about what can we do to protect groundwater, to restore groundwater, to cut overdraft of groundwater. So, it’s a good example of an evolution in the way we collect data and the way we evaluate data and what we think is important.

0:15:16.7 NB: Rohini, coming to your vantage point, can you share with us what trends you’ve picked up around water data, both on from the demand and the supply side and also what prompted the shift to the society platform approach for water, so maybe if you just explain that approach as well and the reasons why you felt that was the right thing to do?

0:15:37.5 RN: Right. So when it comes to bazaar or the market, the demand for understanding water and data on water must have skyrocketed because now it has become a key constraint in the supply chain, from manufacturing to software industry, everywhere, right. Because when you don’t have water, you can’t produce anything, even if it doesn’t appear to be related to water. So I know that the market demand for water data has shot up in the last few decades in India, and that’s where some of the differences begin to appear that today markets, corporations can acquire water data for their use, and we don’t even know how they use it. But today, as Peter was pointing out, private satellites can give markets access to data, which the common citizen cannot and the state will not share, because data is an extremely political subject, and especially in India, you have seen where water is both a state and a union subject under the Constitution, and because water sharing is such an important political subject, we have seen how many times there have been state battles, almost, over the sharing of… First of all the sharing of data and then the sharing of the water itself.

0:17:00.2 RN: So the data in the public domain in India is very contested. We all know that no state is absolutely waiting to put out absolutely true data on its rivers because these rivers are going to flow into other states, and all of the sharing has to then be talked about to political constituents, which in India’s case, we have even seen terrible riots over any political perception that one state is unfairly giving its water to another state. So we all know how data is packaged and presented when there is this notion of zero sum games, of a resource that cannot be renewed when it needs to be. So that’s a very important thing when it comes to the supply side of data, which is why it’s very important to have civil society or civil society institutions or citizens try their best to ground truth the public data, so that they can make local decisions at least with more accurate information. Often the state’s supply of data may not be at the granularity that is useful to citizens to act on their water problems.

0:18:21.6 RN: So for example, as you both know when it comes to water quality, fluoride or arsenic, which are two of the biggest contaminants in our groundwater here in India, and affect we don’t know exactly how many millions of people, but it’s a large number of people who are seriously affected with serious health concerns due to contamination by fluoride or arsenic. But the point is, if I’m sitting in a taluka or a small zone somewhere in a generally arsenic-affected area, it doesn’t mean that automatically all my water sources necessarily have arsenic. Sometimes like we found out in our work, say in, Balapur Puri in Orissa though there was a lot of contamination, it was not reported in the government data sets, so then our partners had to work with the parliamentary representative and actually get Balapur represented in the MIS system so that they could get the funds to tackle arsenic. So, we would love to see a world where there is data coming from the top, but there’s also ground truthing and data contribution from below. So that data is not always just going from one… In one direction, from bottom to top, or only one narrow direction from top to bottom, but like water flows in multiple directions, and…

0:19:44.3 RN: So, for us, it’s really, really important to see how data can be used as empowerment of the Samaj, of society, because markets can easily empower themselves with data. The state, of course, sometimes has a monopoly over data, but what about citizens? So if citizens have to use data so that they can develop more agency for themselves and their institutions, how do we restructure the idea of data and how do we in this 21st century flip the idea of data as something that either the state or the market uses to something that citizens can empower themselves with? And so we came up with a broad structure, which is a part of what we call societal platform thinking, in which we allow, first of all, for the principle that instead of solving a problem, how can we distribute the ability to solve?

0:20:49.0 NB: The way I think about society platforms Rohini is really, water data as an API, so an API that allows water data to get used in different contexts. It’s almost like the Internet of water data, where if you have certain base data which is described in a certain way, then you actually have different kinds of use cases opening up in all kinds of settings, agriculture, industry. So Peter, the question is, from your vantage point, how is water data different, let’s say from CO2 data, and also what is the importance of having water data get used in non-water settings, in non-water industry settings?

0:21:25.1 PG: Well, I’m not sure of the best way to describe the difference between water data and CO2 data. There are raw data that are just provide numbers about a physical or a geochemical factor, and then there are data that are ultimately useful for informing public policy and community decisions. CO2 data tells us how much carbon is in the atmosphere, but it doesn’t tell us by itself where that carbon comes from, or what the consequences of that carbon will be for climate change, or what the consequences of climate change will be for society, which is what we really care about. And similarly for water data, how much it rains or how much water flows in our rivers. It tells us a physical fact or geochemical fact, if we look at water quality, but again, the things we really care about are implications for the things we wanna use water for or implications for human health. What I’d really like to highlight is really two points that Rohini just made very clearly. The first is that politics is a very important piece of this. And for a long time, and even today, some water data were collected by governments and kept secret. They were considered national security issues and they weren’t shared because of concerns about what neighbors might use those, political neighbors might use those data for, the public was rarely involved in collecting data, and I think we’re slowly seeing a change in that. The internet has certainly facilitated our ability to share information.

0:23:02.3 PG: Satellites launched, produce data that is much more accessible to the public that previously governments were able to keep and hold secret, so the idea that data ought to be open source, which is something I believe in very strongly, is a really important one. And any tool that we can develop that promotes the sharing of data is important for making those data more useful. The other point that Rohini made, which I also wanna agree with completely is this issue of granularity. So yes, we know that hundreds of millions of people are exposed to concentrations of arsenic in certain parts of Asia that are unhealthy. That’s really important from a policy point of view, and for developing strategies for dealing with arsenic, but it’s also really important for me to know if my water has arsenic. It doesn’t matter to me so much that 100 million people have bad water with too much arsenic, I wanna know what my water is like and that requires a different granularity of data, it requires me to be able to test my water, or for someone local to be able to test my water and share that information with me, and then provide the resources to help me deal with that problem.

0:24:17.8 VS: That’s a great point that both of you have just raised, and Rohini, I wanted to ask both Peter and you this question, which is, I know Rohini has thought a lot about trust and legitimacy, and a lot of what you said Rohini is about all of these battles over data, where the battle over water has now turned into a battle over data because the states control the data, and then they often bring conflicting data sets, and then it becomes the battle of the data sets. And then, Peter, you just talked about this idea of people wanna know, “Is my own water, drinking water polluted or maybe is my neighborhood lake polluted?”

0:24:52.2 VS: But what we see, and this is in our local context now in Bangalore, for example, we see a lot of battles over who is allowed to collect samples from lakes, so the state says, “Look, we own the lakes, and so therefore, we’re the only people whose data are truly legitimate.” And so even if you collect the data, it has no standing in a court of law. How do we resolve that issue of granularity, because I can collect my data, but if nobody believes it, unless they’ve collected it themselves, then how do I use it to contest? How do you create systems of trust in public data sets where data is not being collected by only one authority, but everybody can collect data, and then they have ways to signal legitimacy of data. So I was wondering whether either of you wanted to reflect on that?

0:25:40.3 PG: Well, I don’t know, I do think it’s important that data be trusted and verified, but I also believe it’s important that the governments not be the sole arbiters of that, that governments not be the collectors, the only collectors of data, that there be independent verification. That’s a question for different legal systems, who thinks data are legitimate, what data are considered legitimate. I do think we’re entering an era where more and more individuals and more and more citizens are able to collect data and share data, and when those data conflict with official government data, that should raise alarm bells, there has to be a way for there to be independent verification of data for too long.

0:26:28.3 PG: Governments have failed to collect the data that are important, or they’ve collected the data that are important and kept them secret from citizens. The Internet’s helping that, it’s obviously not totally solved that problem, but we are seeing more and more collection of data, there’re more and more widespread tools, our cell phones are becoming instruments for collecting data that if we can figure out how to prevent that from being private data that companies keep and share among themselves, but use it become… Useful tools for citizen action. I think there is a lot to be learned in that area.

0:27:07.3 RN: I mean, sometimes it works well because the capability of… For the government, especially to collect more data is becoming more vast. But in some cases, we must also point out that it works well. For example, post tsunami in India, the government started really focusing on getting the right data, the right prediction, the right modeling to tell us when the next threat is going to come. And we have seen for every next extreme weather event, there has been a very decent early warning system in place, which has actually trickled down to the local disaster management authorities, and we have been able to save thousands, if not hundreds of thousands of lives because of the… Now, the… The really good modeling, the prediction, the data put out in public at the right time for the right people who need to make quick decisions, especially when it comes to floods and cyclones.

0:28:07.6 RN: So in that sense, there has been huge improvement, and I think there has been a lot more data put out in the public domain in the last few years in India. There might be a small trend reversing it. Some of my people in the field have been worried that perhaps there is a trend in the opposite direction, but if we could envision data as water data at the community level as an open public good, for people to discover, share action and report back on what happens with their use of data, I think we could avoid many water conflicts.

0:28:49.3 PG: Yep, so Rohini, let me give you actually two good examples of this of what… Just what you’re talking about. One of them is a water story, and one of them isn’t, but in Flint, Michigan… Flint, Michigan is a big city outside of Detroit in Michigan, the water system changed their source of water and people started to see bad water coming out of their faucets, water that was discoloured, water that tasted bad, but they didn’t know what the problem was. And community groups and university groups and non-profit organizations went in and they started to do water testing and discovered very serious concentrations of lead and other contaminants in the water. Those data were critically important for raising awareness of the problem, and it led to many years’ worth of political fights over the water resources.

0:29:38.9 PG: It led to criminal cases, it led to changes in the way the water utility managed the water, and those data didn’t come from the government. Those data came from individuals and they came from non-profit groups, and that was a good thing. Another really interesting example actually has to do with air quality. It turns out that there are some very inexpensive air quality monitors available now in the United States, and I’m sure elsewhere, that one can buy for one’s home to measure the air quality in your home, and it turns out that thousands of people have bought these devices, and when California and the western United States started to experience very severe wildfires in the last few years, these indoor air quality monitors, which are publicly reporting data, you can actually look up the air quality in somebody’s home around the corner from me… But there are thousands of them, started to produce maps for the entire Western United States of where the air quality was good and bad, and I could see when the air quality was bad. And that told me I need to wear a mask or I need to not go out today, and these crowd-sourced data sets were publicly available, we’re beginning to see more examples of that, and there ought to be more and more of it.

0:31:01.2 RN: And I guess we really need, Peter, something like the air quality monitoring device, which is not so expensive to buy. If we could get something similar for water, I know a lot of people are working on this, where you could take something and just test your water. And then you should be able to put that data out and you will be able to get these massive pictures of the quality of water around any community or any nation or any state. We are still waiting for the technologists and the scientists like yourself, to give us something very simple with which we can measure not just bacteria, but at least eight to 10 indicators of water quality.

0:31:41.2 PG: That would be a wonderful… That would be a wonderful tool. We’ve been waiting for that for a long time…

0:31:45.1 RN: We’ve been waiting for too long.

0:31:47.7 PG: And of course, water is a more complicated thing to…

0:31:49.8 RN: More complicated, more complicated.

0:31:50.9 PG: But there is more and more community measurement of some of these things, and when governments fail to do it, citizens should be able to step in.

0:32:00.8 RN: And Veena knows this better than others. In Bangalore, for example, our lakes are a source of pride for us. They used to be a source of sustainable irrigation water in the previous days, but now Bangalore is a megalopolis and we mostly use our lakes, I think mostly to walk around and throw our sewage in. But, citizens have got very excited about lakes in the last decade, and they themselves are going around collecting data and often coming up against the civic bodies, saying “You said there’s no sewage, but excuse me, here’s proof there is sewage coming into my lake.” When the quality of demand rises in the public, there is no system that can withstand that pressure and will have to yield. So, if we keep building the quality of demand for the data, for real, verifiable, maybe triangulated ground truth data on water, there is no system that cannot start to yield and either share or figure out solutions together with the community, so that’s kind of a theory of change that we have to help prove out in the coming days, because it really… There are so many questions, right?

0:33:14.2 RN: One is the quality of the data, the other is data standards. I mean, there seem to be so much confusion about how to collect data, and what are the standards by which we measure something like quality, quantity, accessibility, whatever. And then the interoperability of that data, because you have your data set and I have mine, and if the twain will never meet, then we can’t do the big picture analysis at all. And we’re stuck between this lack of trusted, quality of data, lack of common data standards, and lack of interoperability of data, right? So working more and more towards getting that done, and in some ways, in some scenarios, at least, can water data be an exhaust of common activity rather than us having to constantly spend resources, human and financial, to collect data?

0:34:05.7 NB: This is absolutely fascinating, Peter and Rohini. I found also the three case studies, the Flint Machine example, the California Air example, the citizens almost complaining about the lake water quality, and I’m wondering if you think about the next five to 10 years, right? What role do you think different people should be playing, different stakeholders? What is the role of government around water data? What’s the role of, let’s say, the private sector? What’s the role of research and academia? What’s the role of civil society? And what’s the role of even crowds, right?

0:34:36.1 PG: I do think there’s a difference in the role of different kinds of communities. I think it’s the responsibility of governments to spend the money to build, for example, extensive remote sensing systems, satellite systems, to collect large-scale data that the public cannot collect. And I think it’s the role of governments in general, to collect those data and make them available to the public and to the scientific community, and to the academic community, and to the public service community to use those data the way they think it’s important. And at the other extreme, I think it’s the role of communities to increasingly be clear about what’s really important to communities and local community groups, to help define what data ought to be collected, and then to help drive forward to collect those data.

0:35:27.4 NB: What do you think is the rule for, let’s say, global organizations? You talked about the satellite, the Grace satellite remote sensings. So do you think if those things really, really improve, and the density of that data improves, should then it not become like a global public group, where you have the countries who can make those investments, exchanging those kind of datasets with countries that can’t make those investments. But the reality is that there are many, many countries, let’s say, in Asia, in Africa, Latin America, which may not have the budgets to implement sophisticated water data projects, right? So how does one solve for that?

0:36:01.2 PG: Oh yes. So, I think that’s relatively easy. In the United States we launch a tremendous number, now, of satellites that are remote-sensing platforms that keep an eye on all sorts of aspects of the hydrologic cycle, all sorts of hydrologic data, and climatological data. Those satellites are paid for with public money. They’re launched by NASA, the Space Agency in the United States. And all of those data are in the public domain. Anyone can go to the NASA websites and download the raw data or download the processed data. Those data are public. They’re paid for with public money, and they’re publicly available. Not all governments do that, but in the United States, that’s the principal. And that’s the way it ought to be in general.

0:36:44.3 NB: And Rohini and Veena, given that you work so much with communities and also, let’s say, crowdsource reporting of data, have you seen any patterns around which… In which settings are communities relatively good at doing these kind of things, water data collection, complaining to the government? And where are communities failing to do this well? And what needs to shift for that?

0:37:08.8 RN: Communities would love to be able to crowdsource data to create patterns so that they could complain about inefficiency or inadequacy of water. I don’t think we are there yet, but it’s beginning in some things like water quality, and lake water, and some small water bodies around communities. But I agree with Peter on a lot of things he said. The government has an obligation to put out a lot of data that other people can use for various… Both for research and for action on the ground. As we look at climate change, right, just imagine how critical water data is going to be for people and government, local governments who have to act when crises, water-driven crises, are coming to hit us, right? So it’s going be so important to have, as I said, open, public, trusted, verifiable, interoperable, discoverable data, for decision-making quickly, rapidly, in a fast-changing water scenario, right? So that’s really important. And we forget about our oceans, the state of our oceans. That data is global public goods. And some people are working on that, how do we create global data sets on the state of the world’s oceans, and also… And I’m completely not an expert on this, so anything I say comes really from the Samaj side, is carbon… People are talking about carbon markets, carbon funds. They’re talking about cap, and trade, and tax, and whatnot.

0:38:41.4 RN: I mean at some point, they’re going to have to start to think of water. And I’m not trying to commoditized water or any such thing, but we may have no choice but to look at innovative instruments of financial policy to look at water as well. I think they’re going to have to do some innovation even in the market space and the pricing of water at some level to be able to manage it better. And you know, I come from a people perspective first, but if we look at what’s happening to climate change… For example, data and modeling is going be so important even in the building of public infrastructure in a country like ours, where we haven’t finished building out our public infra, right? Now, if you’re going to build coastal roads, what if there were some data available to you, or some modeling available to you to say, “Excuse me, don’t spend 10,000 crores, rupees on one road near the coast because in 30 years it’s going to be a stranded asset.” I mean that kind of data to be used to be able to make good decisions, especially when a poor, or a relatively, well, not a very developed country like ours, economically, has to make tough choices on public infra. Having good water data, climate change data, modeling, at least, would go such a long way in helping us make smarter decisions.

0:40:07.9 PG: You know, there’s another actor here that we haven’t really discussed very much, and that’s the private sector. And there is a growing interest in water sustainability in the corporate sector, there are good companies in this area, and there are bad companies in this area, but a tremendous amount of water is used by the private sector to produce the goods and services that all of us demand, and Veena and I worked on this many years ago, we looked at commercial and industrial water use in California. We understood then that very little data were publicly available about how much water different sectors use, how it’s used, whether it’s used sustainably, what the water quality that’s then discharged is. The good news in this area is that there is a set of companies that are trying to be somewhat more responsible in the CSR space, the corporate sustainability space, and understanding what their own water use is and working with local communities to make sure that they are efficient and that they’re not hurting the local communities in which they work, but the more effort that’s pushed in that area as well, that will also help a piece of this problem, and many corporations still use a tremendous amount of water and do not report or do not measure what their own water use is and that continues to be a challenge.

0:41:30.4 RN: Yeah, I entirely agree if we would have much more data collected at various levels on how much water is used for every unit of production of anything, and if… And many companies are now setting their own goals that we will keep reducing this in the whole supply chain, year on year, not just because they have suddenly become enlightened, but also because it is a strategic… Absolutely strategic sort of imperative to use less of a scarce resource, scarce and costly resource like water. So we are seeing a lot of innovation in that in India and the globe, and maybe there should be much more sharing across the market sector as to how to increase water efficiency down the line.

0:42:19.0 VS: I think what I got out of this is, there are the two themes, right, Peter, you talked about data used by companies for better decision-making, and then Rohini talked about public data used for better infrastructure development, and I think in our own experience working with all of the different stakeholders, we have worked with ATREE as well, and what we found is that when data is used for private decision-making, there’s a very good incentive to collect better data and use. Well, and even farmers are very excited to participate because they wanna know how much water they have in their well, because they wanna know if they’re gonna have enough to get to the end of the cropping season.

0:42:57.9 VS: Even though they’re doing it as a part of a participatory groundwater monitoring program, their interest in it is primarily for their own private decision-making and not because, well, is the common pool resource is going to survive or not? And that was also the basis of the AP Farms Program in Andhra Pradesh where they had farmers collect the data, but then they were using the data primarily for farmers to learn if their own crop was going to survive because it was a common pool resource. And I think this is bringing me to our next question, which is, at the end of the day, we live in an age of information, we’re collecting more and more data and we are still… If you look at the aggregate water indicators, they’re still going in the opposite direction, and so I guess it asks the question if we’re collecting more data, but it is not getting to better decision-making, what is it going to get us to get to better decision-making, especially in that common pool public infrastructure context, and what’s it going to take to change the culture of how data is used in decision-making?

0:44:01.2 PG: Rohini? If you take the long view, which as I get older, I’m forced to take, more data are available, more water data are available, more communities are demanding certain kinds of water data and producing water data. The amount of good information that’s available today is much greater than it was 20 years ago in the water world. We know more, and I believe those information are having an effect on public policy. I think we’re slowly making a transition from the old way of thinking about water to a new path for water, as I’ve described it elsewhere, and I think that’s partly because we have better data and better information about both the nature of the problem, but also the success of certain kinds of solutions.

0:44:49.0 PG: I don’t mean to over-exaggerate this. There are certainly enormous data gaps and we haven’t talked that much about that. There’s still a tremendous… There’s a tremendous amount of information that we don’t collect that we need to collect in basic hydrology of water stocks and flows, in water quality that we have talked about already… In the economics and in the cost to communities of certain kinds of impacts or the cost of water or the nature of bad subsidies, I think there, there are lots of places where I would love to see improvements in the collection of water data, but I do think we’re slowly moving in the right direction, and the trick is how can we move faster to collect the right kinds of information we need, and to make sure that information is used by politicians and policy makers?

0:45:37.5 NB: Yeah, no, that’s a great sort of segue into the final question, what is your wish… One wish for the entire water data ecosystem, to get us to a better way of doing things?

0:45:49.3 RN: Well, I think we do have in India, more data out in the public domain, how can we push for a more open public sharing of more relevant data that is relevant for communities to act upon? So it needs to be at the right granularity, it needs to be more trustworthy, and there should be more enabling policy to allow different sets of factors to collect and share data. So, basically, more open sharing of water data, and it should not flow in only one direction. Water data needs to flow in many directions.

0:46:28.1 PG: Yeah, so of course, I agree completely with what Rohini has said. I would just add, my wish is first, not a data wish, my first wish is that we have a better sense of what a truly sustainable water system looks like, what it really means to provide safe water and sanitation for every human on the planet, what it really means to support ecosystems and protect the natural environment and the water that the natural environment requires as well, that we have a sense of the proper role of economics in allocating and in managing water, but the context of economics and in the human right to water, and what that means, and if we put all these things together and we have a vision of what a sustainable water system is, then the kinds of data and information that we need to manage that system, to protect that system, to run that system will be clearer, and that will help us figure out what data we need to collect, how we need to share those data, and how we need to use those data to influence public policy.

0:47:36.0 RN: Yeah, Peter, I really like that, and this conversation has forced us to put data in the center of the conversation, but actually data for what? Data so that we can all have sustainable equitable water for all living systems on this planet.

0:47:53.2 PG: Very good. Water for people and the planet.

0:47:56.2 VS: Love that.

0:47:57.0 NB: Yeah, absolutely.

0:47:58.0 VS: Thank you so much, Peter and Rohini. That was a truly inspiring conversation. Thank you so much for agreeing to speak to us and also for kicking off this podcast series on water data.

0:48:15.0 S1: Thank you for listening to The Water Data podcast. To learn more about the guests and our work, do check out the show notes, and don’t forget to tune in to the other episodes.