How Is Data Science Being Used to Tackle the Global Problem of Clean Water?
“Big data” is the new trend in data science and data analytics which seeks to capture large and diverse datasets in order to inform decision-making and strategic objectives for an organization. Data science approaches have been used in a variety of settings – for example, e-commerce platforms use data science concepts frequently to track consumers’ buying patterns and use this information to set product prices. Sites like Amazon use complicated algorithms to improve customer engagement and optimize the shopping experience for Amazon customers. Data science applications in the world of utilities seek to characterize and quantify power usage in order to optimize power consumption. What type of implications can data science have to tackle the important problem of clean water? Read on to learn more about how big data can help address the urgent global water crisis.
An International Problem: Clean Water
Just as access to consistent, reliable power is a must in today’s world, especially due to the rise of internet and smartphones, access to clean water is fundamentally important, if not more so. Water shortages are a problem both in the developed and developing world. According to the United Nations, 2.1 billion people do not have safe, reliable access to clean water. In the developing world, the water shortage poses a sanitation challenge as well, leaving 4.5 billion who live in poorly managed and dangerous sanitation environments. Water scarcity affects an estimated 4 out of every 10 people around the world, and this problem is only expected to become more of a challenge as the global population continues to grow.
Without clean water, people not only cannot obtain a safe source of hydration, but the local economy is affected as well. For example, without water, farmers cannot grow crops, which can have a devastating effect on a local economy. Basic sanitation offered by toilets and latrines become more of a challenge without water to maintain their normal operations. Unclean water and hazardous sanitation are a leading cause of child mortality as well. Children who lack proper sanitation facilities are at a higher risk for developing dangerous diseases such as cholera, typhoid, infectious hepatitis, polio, among other devastating conditions.
The problem of clean water manifests differently in the developing versus the developed world. In developing countries, lack of access to water is a major problem that contributes to poverty. In Africa, the lack of access to clean drinking water has contributed to a poverty epidemic. Access to water is not only essential but it improves health, education, the economy, and enables communities to lift out of poverty. This is why much attention has been paid to building a self-sustainable water infrastructure in developing nations. For example, many nongovernmental organizations such as The Water Project have sought to build new wells and repair existing ones, install dams, etc.
Without clean water, communities cannot grow food, build houses, stay healthy, become educated, or remain employed. The time invested in collecting water in third world countries can leave citizens unable to do much else. In many poverty stricken countries, water collection poses some physical challenges as well. A typical water collection container weighs 40 lbs., and some women carry up to 70 lbs of water on their backs. This inefficient practice can have severely negative health consequences. Unfortunately, in many nations – Sub-Saharan Africa, for example – this is the daily reality.
Sadly, water shortages exist in the developed world as well, though on a less severe, but just as harmful and disruptive, scale. According to USA Today, 63 million Americans were exposed to poor quality water more than once over the past 10 years. Two examples stand out here. In the United States, California is a state frequently plagued by water shortages and droughts. Famously, the citizens of of Flint, Michigan, learned in 2014 that their water had been poisoned by toxic levels of the compound lead. Lead contamination in water can lead to cancer as well as severe developmental delays in children. The U.S. Environmental Protection Agency has estimated that communities will need to invest upwards of $380 billion in the ensuing decades to keep American water clean.
As illustrated by the examples above, obtaining safe access to clean water is an international problem, affecting not only the third world but Americans as well. While most people in the U.S. can effortlessly turn on their faucet to access this wondrous liquid, others are not so lucky. The problems outlined above signify a call to action to come up with better solutions for clean water. After all, water is necessary for all aspects of life. How can we use the latest and most cutting-edge technology to ensure that everyone in the world can have access to this important molecule?
How is data science currently being used to tackle the clean water problem?
- Smarter water use: Data science can help make better use of existing water resources. Over the past 100 years, the world’s population increased by threefold, while humans’ use of water increased by sixfold. Drinking, cooking, bathing, cleaning, and watering plants are some of the main uses of water by humans. On the commercial side, industries use twice as much water, if not more, than individual households. Gary Wong, one of the world’s foremost experts on water and water management, recently told ZDnet that utilities, which use massive amounts of water to cool down their plants, must be more willing to invest in analytic tools grounded in big data in order to improve efficiency and reduce wasteful water use. Most industrial sites already collect large amounts of data, but do not know how to analyze the data that they have collected; this is where big data has the potential to make the greatest impact. Data science can help utility providers know how much water they are using, and figure out ways to reduce water use in order to lessen their negative impact on the environment, and particularly, the water crisis.
- Real-time monitoring of resources: Water quality can be tracked in real time using data science. This lessens the effort, time, and resources required to determine whether a given water source is of good quality. Real-time monitoring can also be used to ensure that accessible water is indeed clean and safe to drink, which can save communities time, money, and other, less tangible resources, such as human labor.
- Water quality forecasting: Data science principles can be used to analyze water quality trends and make predictions regarding projected water quality as affected by rain, pollution, and other contributing factors.
- Identifying issues with the water supply: Data science can also be used to identify whether there are regional or community-based issues with the water supply. This can be highly significant in terms of helping prevent diseases and epidemics that could be spread through the water system.
Data Science Concepts Can Be Harnessed to Have a Greater Impact on Clean Water
While much work has been done to utilize big data applications in the water industry, there are many areas which could benefit from advanced analytic tools grounded in data science. This potential has not gone unnoticed – organizations such as the University of Berkeley and even NASA have sought to harness the full potential of data analytics to help ensure that more global citizens can enjoy the many benefits of clean water.
In California, a state with a significant water drought, civic ‘hackathons’ seek to bring together smart programmers to develop analytic tools which can: 1) improve water quality reporting; 2) improve drinking water quality standards, 3) identify areas of severe drought and water contamination; 3) evaluate the harmful growth of organisms such as algal blooms in freshwater; 4) locate and track contaminated water sources; and 5) investigate water distribution among California’s large population. Despite living in the United States, a highly developed and technologically advanced country, over 350,000 Californians lack access to safe drinking water. Therefore, novel solutions – likely powered by big data – are required to improve water quality in California.
Such hackathons represent opportunities for ‘citizen science’ – a new trend in research which utilizes the collective effort of members of the general public who wish to use their expertise in science, technology, engineering, and mathematics (STEM) to address significant social problems. Citizen scientists – for example, in the water sphere, expert computer programmers and coders who may not have a dedicated water or utilities background — typically collaborate with professional scientists who can provide access to the data. Citizen science can allow individual citizens to dedicate their technical expertise to help solve complex technical problems and make the world a better place.
Terra, a NASA project focused on studying the link between Earth’s “atmosphere, land, snow and ice, ocean, and energy balance,” is tasked with understanding our planet’s climate change patterns, and how they are affected by both human activity and natural disasters. Citizen scientists can contribute meaningfully to NASA Terra, both by collecting and analyzing data. Terra encourages citizen scientists to monitor water quality in local streams, lakes, and rivers. This can help identify potential sources of pollution that can help inform government agencies’ response to better control and minimize the level of pollutants that are found in drinking water. A group of citizen scientists could theoretically help observe and monitor an entire local water ecosystem, looking for sources of contamination. More advanced tools available to NASA Terra citizen scientists include the integration of satellite data with local observations. Local water quality observations can be tied to more broad regional ecological trends and changes. This concerted effort by citizen scientists working independently could have significant cascading implications for the entire ecosystem.
Thanks to the rapidly expanding interest in big data and complex computational approaches to some of the world’s most pressing problems, the future of big data in the water sphere looks promising. Citizen scientists are at the forefront of this effort to improve water quality, while utilities providers have already incorporated many data science tools in their day-to-day operations.
Case Studies Indicate that Big Data Can Help Solve the Water Crisis
Case studies indicate that big data can be incredibly powerful as a source of insights for local governments. Chicago, for example, is utilizing data science concepts in order to make their beach water more safe. Farmers in Arkansas are also using big data to reduce their water usage and save on utilities costs.
Case Study #1: Cleaning Up the Chicago Waterfront
A number of promising case studies indicate that big data could potentially contribute greatly towards better water management in major cities around the world. For example, the City of Chicago utilized a big data solution when they were faced with a crisis regarding the quality of their beach water. Being cognizant of the major impacts of citizen science, Chicago enlisted the help of civic hackers to work with the Chicago Department of Innovation and Technology. The civic hackers developed a predictive model which can tell the city which beaches should close due to high levels of the dangerous bacteria E. coli. From 2015 to 2017, the civic hackers developed and tested four models of software which pulled data from Chicago beach inspections as well as externally available data from the National Oceanic and Atmospheric Administration (NOAA). The City also decided to begin to conduct E. coli testing at its beaches during this time. The combination of analytics and E. coli testing helped Chicago develop a rapid-detection program for the detection of E. coli which involved direct E. coli testing at a few sites, supplemented by analytics everywhere. This combined method, which was instituted in 2017, helps the city save money as E. coli testing is very expensive. Therefore, Chicago’s investment in big data will likely save the windy city millions of dollars in the ensuing decades.
Case Study #2: Using the Internet of Things to Save Water in Agriculture
Agriculture uses the majority of the world’s water; unfortunately, a significant portion of that water is wasted due to leaky irrigation systems. There is an opportunity for the agriculture industry to embrace big data in order to optimize agricultural systems. Rice, for example, is one crop that requires a significant amount of water, some of which will be lost due to waste, poor irrigation methods, etc. An alternative to keeping a four-inch level of water on the rice crop is called Alternative Wetting and Drying (AWD). AWD requires farmers to keep track of water levels on all areas of their land, which can be a challenge as it requires the collection and analysis of a lot of data. Farmers at Whitaker Farms in Arkansas have partnered with AT&T to install pumps and sensors on their farms so that they can monitor the amount of water that they provide to their rice crops. This enables 24-hour monitoring and provides farmers with a wealth of data related to water management. The installation of water sensors has reduced Whitaker Farms’ water usage by 60%, and pump energy usage has decreased by about 25%.
What’s the future of big data in the clean water domain?
As computational power continues to improve, this will be more amenable to analyzing the vast amounts of data generated at our water utility sites; such advanced computational tools can also be applied in the third world to improve water usage and monitor and predict water quality. While this work is not done by any means, the help of large-scale philanthropic efforts by leaders in the tech sector, such as Bill Gates, will undoubtedly continue to break new ground at the intersection of this humanitarian problem and technical challenge.