Droughts, Floods, and Famine are a useful metaphor for understanding the importance of water data management. Too little or too much data, like water, have downstream effects. While it is self-evident that lack of water data (i.e. drought) leads to insufficient water information for consumption by water resource managers (i.e. famine), it is somewhat counterintuitive that too much water data (i.e. flood) can also result in information famine. The premise of this part of the metaphor is that an increase in data, without commensurate increase in capacity for data management, reduces the value of the data. Data are mere seeds that must be cultivated into useful information by data management. Without careful cultivation, seeds are blown away by the wind and weeds are likely to thrive and spoil the entire crop.

Water is a shared resource. Historically, civilizations have thrived wherever water quality is excellent and water quantity is abundant. However, migration to discover new sources of freshwater to exploit is no longer an option. The old assumption that ‘sharing’ means using as much water as you need, with complete disregard for the quality and quantity returned to the environment, is fundamentally unsustainable. In the modern era, ‘sharing’ means using a ‘fair’ amount that leaves enough water—of sufficient quality—for the sum of downstream uses. Allocating and enforcing ‘fair’ amounts of a shared water resource requires shared and trusted water information. Without adequate water information ‘fair’ is an impossible objective resulting in water overuse, misuse and abuse.

A feedback mechanism is proposed whereby improving water data management can sustain, and even increase, funding for water monitoring. The premise is based on the principle of ‘use-it or lose-it’ whereby if data is reliably transformed into trusted and useful information the value of the underlying water data collection activities will be recognized and supported with sustainable funding. Unsustainable funding for water monitoring is inevitable if the data are either unavailable or left in a cryptic, unusable state for want of reliable data management.

The rapid adoption of new sensing technologies is resulting in many new sources of water data without a corresponding increase in investments in data management. The result is that the sheer volume of data is overwhelming our ability to make sense of it. Eventually, we may transcend to a ‘data about everything, everywhere, all-the-time’ status that can be mined by artificial intelligence to answer every relevant water question. In the meantime, while the speed of adoption of new sensing technologies is far greater than the rate of upgrade of data management systems, the information coming from the data can be confusing and even contradictory.

Timely, trusted, reliable water information is needed now more than ever. Water monitoring agencies must adapt and respond to the growing need for modern data management systems that are capable of managing a flood of data and preventing data droughts. Raw data is not good enough. To be useful, water data must be turned into meaningful, actionable, context-rich, information that is instantly accessible to a diverse community of stakeholders. Making the most of our data investment is the best way to ensure that we make the most of our shared water resource.