Mr Stuart Crane, has been program coordinator at the United Nations Environment Program and its Center for Water and Environment since 2017. Mr Crane has experience in international intergovernmental organizations since 2009 and dedicated large parts of his career to working on environmental issues such as energy, climate change and water. His professional background is in Environmental Quality and resource management, and he received his post graduate degree in International Development. On behalf of UNEP, he coordinates a global SDG 6 fresh water program that supports 193 countries with progressing towards SDG. 6 targets on improving the water governance, ecosystem management and reducing freshwater pollution.
Could you describe your professional career or personal experiences related space technology and water? Where does your interest in freshwater ecology come from? What relates your field to space technologies?
My professional career has always focused on, in, and around ecosystem restoration and on having healthy ecosystems that can function well enough to provide goods and services both, to the people and to the planet. UNEP has a custodian role to support countries with protecting and restoring our freshwater ecosystems, and I focus on supporting countries with freshwater ecosystem protection and restoration. Historically, countries have not done so well in monitoring environmental data, specifically freshwater data, in fact there has been as global dearth. In 2017 freshwater ecosystem data was sparse. For SDG indicator 6.6.1 we sought support with filling global data gaps from space agencies, including NASA and the European Commission's Joint Research Centre, who engages with the European Space Agency and also JAXA, and looked at monitoring freshwater ecosystems from space.
Could you tell us a bit more about your current work, your latest project, or your proudest professional moment?
The launch of an online geospatial data portal named the Freshwater Ecosystem Explorer was a proud moment. We were able to provide information on a range of different ecosystem types across very long time series and could provide that information to the world for the first time. We did not only fill a global data gap for SDG indicator 6.6.1 providing statistical trends validated by countries as never seen, but we have provided that information in a way that allows countries to take action so you can see these long-term statistical trends against different ecosystem types. For example, open water or seasonal water reservoir water, but also inland wetlands, coastal mangroves, and water quality. We provide a very high resolution of data across this large spatial and temporal area so users can use information at a local level.
What are the most important water quality indicators that should be globally observed and why is this so?
There is a two-part answer to that question. On the one hand there are the in-situ water quality measurements, which as per the SDG indicator 6.3.2 core parameters, include: oxygen, salinity, nitrogen, phosphorus, and acidification. But we should add to this the data we can obtain on proxy water quality parameters, specifically turbidity and trophic state, that we’re able to observe using Earth observations and which we have available on the Freshwater Explorer. These two parameters provide a very helpful indication to flag where potential water quality issues have arisen in large water bodies around the world. Trophic state provides a useful indication of where freshwater bodies might be experiencing harmful algal blooms, a common occurrence these days when there is excessive biological matter entering water bodies, including runoff from agricultural land, phosphorus and nitrogen. These harmful algal blooms can be observed from space. And if you really want healthy freshwater ecosystems and good quality water, biodiversity is a very good indicator and should be on the list.
Chlorophyll-A is considered as a proxy for water quality. But an analysis of the actual correlation between chlorophyll A and dissolved phosphorus or nitrogen is often lacking. What are the gaps and potential pathways to solution?
We have confidence in Earth observation data, but we need to better corroborate our global water quality data with in situ data measurements. Some of that work is already underway. To achieve this requires capturing turbidity and chlorophyll-a measurements in situ at the same time as a satellite overpass occurs and correlating the two datasets. This would help ensure space-based data is more closely aligned with what the real measurement is on the ground. Several space agencies are working with countries to try to provide that.
So more in situ data is needed globally to verify the global data and to train models?
Indeed, that's right and we require machine learning approaches that can ingest in-situ data and improve overall data accuracy. We need to take measurements when we are confident there is a high incidence of one of those pollutants occurring because, for example, incidences of high turbidity can come and go relatively fast (within days, sometimes weeks). We actually have to be on site at the right time to be able to get those measurements.
Do you know if there's a rule of thumb to know what percentage of ground truthing data are necessary for verification of Earth observation based models?
No, I wouldn't say there is a rule of thumb, simply that the more in situ data you can correlate with Earth observation data the better, and more accurate the result, and therefore the more confidence people with have in the data. We must also consider that water quality thresholds are different depending on water body locations in the world, their size, what they are used for, and how many people are accessing and using the water.
What are essential water variables for informed decision making and policy development? Do we already have data on those, and if so, to what extent?
Accurate determination on the cause of the water pollution as well as accurate data on location and severity – decision makers need to know to what extent pollution thresholds are being exceeded to formulate coherent responses. As such reliable, and if possible, near real time water quality data can mean a targeted and impactful response. Generating such data over long time period, however, creates a lot of data, which for many countries simply isn’t feasible due to resource constraints and other priorities. There is an important role for other data to play in informing policy makers. These data can include Earth observations, models, and citizen science. These need to be brought together to express water quality occurrences and responses in meaningful ways to both national and sub-national authorities.
There is also a need to include a missing piece, which is water quantity data. We currently have spatial extent data for different types of ecosystems, such as open water, that can be separated into permanent, seasonal, and reservoir water; plus data on wetland ecosystems. And just to stress that wetlands play a crucial role in water quality and purification of water and the retention and uptake of nutrients, for example. What we don't have globally available is water quantity data. If you want to inform policy, you need to bring those physical and chemical parameters together on water. You need to go a step further and start to look at freshwater biodiversity, an important indicator of freshwater ecosystem health that is very hard to extrapolate globally. You need to look at the connectivity of hydrological systems within river basins and if that connectivity is being split apart by man-made incidents and such as creating dams and reservoirs, for example. Those things are interrelated and affect one another and therefore affect any decision, any recommendation towards water resources management and policy.
How can you best visualize complex interrelations for a decision maker to take the best decision?
You can put the best data out there and it might not lead to anything. To inform management decisions that lead to real action on the ground you need to provide that information in a variety of forms and formats for different users and purposes.
On the freshwater ecosystem explorer for example, we provide statistical information in percentage, in square kilometre change and we also provide long term statistical trends as well as a more in depth level of analysis to allow you to dig into that data and understand the month by month or year by year information. You have to present information visually via maps and charts.
Finally, and perhaps most importantly, the data needs to be demand driven and fit for purpose. This means, from the outset, working closely with the users of the information. This is an area UNEP are working on currently, alongside the Global Water Partnership and United Nations Development Programme International Capacity Development Network for Sustainable Water Management (CAP-NET), taking the SDG 6.6.1 data and making sure that countries understand it and that space-based data also aligns with countries own national data from in situ measurements. This includes securing the political will of governments so that the end product, if this instance ecosystem action plans or a national level management plans, which prioritises certain ecosystems in the country for protection and or restoration, will be implemented.
Seeing change happening, is probably a part of your work that makes you feel good, isn't it?
Change is incremental and ecosystems take a long time to repair, but yes, if you can support change in countries, in people, towards ensuring that freshwater ecosystems provide good quality and quantity of water into the long-term future. That is a worthwhile end goal. To get there, we need to be able to better determine the functional capacity of ecosystems to provide goods and services to our societies and to nature at large. Therefore, you have to be able to identify, if the ecosystem is degraded or being mismanaged, overused or if it is highly polluted. You need to know what state the ecosystem took when it was healthy, and that is why Earth observation data is so helpful. It allows you to look back in time to see a situation that you want to return to. For ecosystems to recover it often takes many years if not decades. Interventions themselves are slow and seeing the success of intervention is also slow. You need to be cognisant of that recovery period of ecosystems.
What is important to be improved in global water quality monitoring?
In situ monitoring still needs improving in many countries and there are resource and capacity considerations to do that point. Meanwhile it is also a good idea to bring different data on water quality together, and EO has such a promising role to play here. But the EO data itself needs improving, too. Currently the water quality data that we have on the global Freshwater Ecosystem Explorer includes very large lakes (300x300m). We cover around 4300 lakes globally with two parameters (turbidity and trophic state), but we need to go further than this and have water quality data on significantly more water bodies globally. Ideally, we would also move towards more predictive analysis, to support early country interventions and act upon ecosystem degradation sooner rather than later.
With the use of in situ data we can also improve the data sets we can derive from space, aren’t they interlinked?
Certainly, with space-based technologies you are able to cover the world, and that is great. That is resource efficient and hopefully we’ll soon move in the direction of increasing resolution and to have many more water bodies included in the EO data. In situ on the ground measurement is more accurate, has more ownership but is more resource intensive as countries need to manage monitoring stations and programs which are unlikely to cover the same spatial and temporal monitoring as Earth observations. The answer of course, is that you need both in-situ and EO and preferably citizen science input as well. Each data source can help improve the other.
What spatial resolution is necessary in the open domain to get a clearer picture about smaller lakes?
As I understand it, the COPERNICUS lake water quality data has a 30m resolution and selects only water bodies that are 300x300 meters or larger. There were discussions around advancing this to include 100m water bodies though I think there is a concern this could reduce some aspect of the quality of the data.
Could you expand on the difference characteristics and observation methods for water quality in lakes and rivers?
Monitoring moving water bodies (i.e., rivers compared to lakes) from space is not without its challenges. In a large slow-moving river with high levels of pollution, it is possible to pick up turbidity. And if this were a recurring situation where you frequently saw that same occurrence at that same point in the river maybe there is a management intervention that could accompany that problem. If it is more of an ad hoc observation the intervention might be harder. Where pollution in lakes, tends to stick around for longer. In lakes you can more easily observe poor water quality from space. In rivers, by the time you got to that point of instance, the problem might have disappeared.
Being able to take action on river-based water quality using space-based data sources would require looking at datasets that contribute as drivers and pressures to the poor state of rivers. Approaching the problem at a river basin scale would be practical, and considering analysing land use cover and change, urbanization and other global datasets that are available at that same spatial scale that you can start to overlay with water quality data.
On a global level, do have sufficient data on rivers?
No, we don't. There are some data sets and new approaches being developed, such as the Global Hydrological Model, but we need to check if these tools produce data at a global scale and be meaningful for countries.
So global water quality in rivers is something to be done by all the researchers out there?
How can we best assess gaps, which is a very sensitive topic, or identify user needs? Is there a way of getting gap assessments data from other actors who are specialized on this? How can you best do it, let's say if you're a small NGO or company who wants to be part of the solution?
It depends so much on different stakeholders, but looking at the process, we typically work from problem, to tools and response, to action.
- First and foremost you need to have an identification of the problem, a measure of state, which requires detailed assessment, and analysis. Information about a problem can be found at data portals, but ultimately, if you are working in a country, if you are a national stakeholder interested in national or subnational level problems, data is found in the country. It's not easily found elsewhere.
- The second part, is the capacity gaps. Who's going to address the problem? Are there capacity gaps that might exist to address that problem? That depends on what the problem is and on, who, which country it is in, what is the scale of the problem. Is it a water body problem, a national level system, a systemic problem or a financial resource problem? There is no a generic answer, but you need to have tools, methods and approaches that help countries plan for and respond to that problem, and within that planning and response comes a range of capacity measures, such as institutional strengthening, technical strengthening, or the provision for translation of data, or of science into policy. Moving that knowledge from a very technical perspective into one that is very easy to understand that all is capacity building. Enabling people and institutions to better address and respond to the problem that you have identified. This includes tools, planning and your response.
- The third part of the process is the action-based part: go out and do it. The implementation of action might require new laws, a physical restoration or remediation of water bodies to restore them back into a healthier condition, to protect them, for example. A whole different suite of stakeholders might be interested in that action-orientated aspect compared to the capacity-based towards planning and the response-based part of that process.
Within the SDGs and Agenda 2030 we focused on getting data where there has been none. Now we have data and need to make sure it is used. Data uptake is notoriously difficult, you don't necessarily know if the data is being used or influencing any decision-making process, unless you are in a country working with those decision makers and see the output of the decisions. That's where all the focus needs to get to. This is a country by country and ecosystem by ecosystem process. You cannot just come and say that this is one same problem for all countries, because the drivers and the pressures that change the state of ecosystems demand different responses in different countries at different scales. You have to be able to work at both local and national contexts to address those capacity and implementation needs.
What are links between sustainable water management and climate change? What will be key climate change challenges related to water in the future, and how can we mitigate them?
That's a big question - a good one for a PhD thesis and not one I could offer a simple answer to. Climate change manifests itself through water. Water is one of the immediate means of experiencing how our climate is changing. We are already experiencing those changes as we witness parts of the world are becoming dryer and other parts are becoming much wetter. Parts of the world will observe rapid melting of permafrost and glaciers, directly impacting water resources. In other locations we’ll see drying up of permanent water bodies or of wetlands. The loss of water bodies can cause forced migration. The issues surrounding water and climate change are intrinsically linked and are already an underlying cause of water or food security for many people around the world. The solutions are complex and are context specific.
What do you think is poorly understood or unresolved at the nexus of water and other important fields? And why is it so?
You can't look at water in isolation. Water is a foundational resource that connects development actions across sectors. If you try to address water issues in isolation, you are unlikely to succeed for long. We have already changed a majority of the natural landscape through deforestation and conversion to agricultural land. We are urbanising large areas of land too. These changes impact hydrological processes and the provision of fresh water at sufficient quantity and quality. At the same time, the needs of increasing numbers of people upon water resources have to be accounted for. We need to bridge the gap between changes in water, climate, population, and land use. The policy response must account for all drivers and pressures impacts the state of water. That response might well require both immediate and longer-term solutions, and data is needed to inform both. There is quite a lot of progress needed in bringing various data together in this regard. In addition, freshwater changes need to be understood at a local, water body or river basin, scale. Local context is so important.
Do you have ideas for improving international cooperation between countries on the use of space-based data for sustainable water management?
Space technologies for measuring water are really gaining ground offering unprecedented temporal and spatial coverage. The data enable countries to look back in time and also gives the means to predict future trends. In contrast, many national governments struggle to generate the same output themselves using non satellite data. Space technologies can produce data that is accurate and readily available at high resolution. There is some degree of neutrality inherent in satellite data and if governments trust the data production methodologies it offers a real opportunity to collectively understand water changes occurring across national boundaries and therefore to facilitate transboundary cooperation and to build international consensus behind taking action on regional and global trends.
There are intergovernmental processes and frameworks which are looking to improve the natural environment (including water). I think that it is important to identify where data needs to feed into these policy discussions. To do that you need to have trust in the data. It is absolutely critical if you bring two parties together who might have disagreement over transboundary water body and you are using remote sensing data to paint a picture of how a state of an ecosystem might be changing. Trust in that information is fundamental.
I think you need to have increased capacity in countries, so they are able to perform analysis by themselves. It shouldn’t always come from an external body or organization all the time; that doesn't necessarily build trust. It might actually take trust away. You need to have the institutional and technological capacity, and the resources to be able to access satellite data and perform analysis of water resources in this broader context within countries. That will ultimately lead to good actions that protect our resources in the future. Many developed nations have that capacity, but if you look at where environmental changes are most prolific, it is not always in a developed country context, and we need to be able to focus on those hot spots in the world and make sure that capacity exists there.
What's your favourite aggregate state of water?
I'll go with the fluid stuff that I drink in my glass every day, because it keeps me alive.