How big data can save our depleting water supply
The projected status of the world’s water supply and quality in the next decade looks bleak: widespread shortages, difficulties growing food for a booming global population and billions exposed to diseases caused by poor sanitation. These anticipated outcomes result from the combination of wasted freshwater in agriculture and worsening water conditions caused by the increased use of pesticides and fertilizers, among other things.
By 2050 the world’s population will reach 9.7 billion and 11.2 billion by 2100, according to the United Nations. Unfortunately, only 3% of the world’s water is fresh and two-thirds of that small percentage is not accessible. With an already dwindling water supply, and food shortages in developing countries, it has become essential to investigate how current water and agricultural infrastructure can be enhanced to accommodate the world’s growing population.
Currently, 1.1 billion people lack access to water and 2.7 billion find water scarce for at least one month of the year. It is important to note that all freshwater is drinkable. With increased use of water pollutants and poor water treatment in developing countries, 2.4 billion people are exposed to disease such as cholera and typhoid fever, and two million people, mostly children, die every year from diarrheal diseases alone, according to the World Wildlife Fund. Those numbers aren’t expected to become more favorable. At our current consumption rate, the World Wildlife Fund expects two-thirds of the world’s population will face water shortages by 2025.
Big data, along with other advances in technology including GIS, LiDAR, drones and even social media, are helping increase the amount of available water, while ensuring it doesn’t leak or get contaminated before reaching the end-user. Big data, according to Gartner, is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making and process automation. Data gathering and processing has become increasingly important in enhancing visibility for nearly every industry, though water management has been particularly slow to take advantage of its benefits.
The challenges: Fragmentation and incentive
The proper management of one of the very few essential elements of life has become a challenge due to human self-interest and a lack of leadership among stakeholders.
The world is in dire need of a way to maximize the amount of water that be safely collected, transported and purified. The majority of groundwater sources are being depleted more rapidly than they are recharged, and there is very little opportunity to manage water supplies in storage when compared to the scale of current water use. Rivers, lakes and aquifers are drying up or becoming too polluted to use, and more than half the world’s wetlands have disappeared, according to a report from the 2015 Aspen-Nicholas Water Forum.
Global and local government officials are not investing the necessary effort into water management. There is a lack of political will to fund data collection, particularly at the federal level. This means direct stakeholders will need to advocate for increased funding for data-gathering and data synthesizing efforts, especially in agriculture.
Agriculture is, by far, the biggest user (and waster) of water in the world. Farmers use 70% of the world’s freshwater, but 60% of it is wasted due to leaky irrigation systems, inefficient applications methods and the cultivation of thirsty crops, according to the World Wildlife Fund.
Farmers do collect enormous amounts of data about water usage on their fields, but they refuse to make such data available for broader use due to lack of trust with the government, which they believe will initiate enforcement actions against them. This results in gaps in knowledge of how much water is available, how much water is needed and used and how those quantities are changing over time making it difficult to determine how to allocate water among competing needs, according to the Aspen-Nicholas forum.
Here are a few more challenges of collecting and analyzing data in water management outlined in the 2015 Aspen-Nicholas Water Forum report, Data intelligence for 21st century water management:
Lack of transparency around water data – more incentive to not share data
No order to data collection – no standards or continuity
Government – Lack of interest on a federal and state level
Monetary distractions: lack of sensors, data gathering tools – other interests competing for money.
Leadership: need for strong stakeholder and government leadership
What big data could mean for water management
All of the necessary technology exists to expand water resources and ensure its delivery to end-users. Data acquisition has expanded dramatically in recent years with low-cost sensors and widespread adoption of geospatial analysis. These new technologies have increased our ability to find and monitor water stores. And infrastructure implemented to existing sensors allows for cloud computing and increased visibility of data across systems. Those wide-deployment technologies combined with unstructured data like social media, web content, and crowdsourcing, increases visibility and the amount of useable, useful water data.
Big data analytics can continue to optimizing the balance between performance and reliability when it comes to farming. It may also prevent man‐made disasters, such as sudden drops in water quality, which may not be detected until after the full affects are realized, according to Rijksdienst voor Ondernemend, a Dutch enterprise agency.
Big data such as these can help water utilities understand trends in land use and climate that will influence key decisions about planning an adaptive and responsive water system. Big data and modeling can also help water utilities and land use planners collaborate to assess what amount of water will be needed and is available for different city growth scenarios.
How to get there, from now until then
The technology is in place, and is continually being optimized and made more affordable for use in farming. In fact, a lot of data has already been gathered. Still, there are barriers that need to be broken for the data we have and will continue to gather to be put to good use.
Incentives for data sharing, such as financial gain that is actionable beyond regulatory enforcement may help unlock sources of data.
As a first step, a baseline set of water standards, indicators and measurements should be defined that reflect the core data on the state of our water system. Data standardization will enable integration of data collected for different purposes, from satellite data to data collected for local water management, according to the Aspen-Nichols document. Here are more key findings from the forum:
- The rise of big data and new measurement technologies can transform the way that water is managed in the coming decades.
- However, water data must be synthesized more rapidly than government agencies’ current pace of analysis.
- A national water data policy is needed that standardizes data integration and storage for more effective water management across sectors.
- Overcoming privacy constraints would help to maximize the potential of water data.
- Accurate assessments of private sector water risk require better matched data sources and data analytics across industry