As we celebrate RTI’s 60th anniversary and the launch of the new RTI Center for Water Resources website, we are drawn to reflect on the incredible amount of progress that has occurred in the field of water resources over the past several years. One particularly striking evolution is the growing availability of large datasets, which have surged onto the scene with accelerating developments in computing power, data storage, satellites, drones, and other remote sensing technology. More information about water resources is available than ever before. This begs the question, is our ability to make good use of that information keeping pace with the rate it’s becoming available?
The era of information
We live in a time with endless information at our fingertips, at every moment of the day. Social media, email, news feeds, podcasts, blogs, etc. are spilling massive quantities of data into our lives at breakneck speed. Some argue that as a society, we are showing signs of information overload, contending we are unable to process the information and extract value at the pace we are ingesting it. In short, our brains cannot keep up.
So, are we truly better off with the constant flow of information? The growing trend toward ‘disconnecting’ is perhaps a sign that people are recognizing that information itself is not intrinsically valuable. Instead, value is created only when we make good use of the information.
Are we making good use of data in water resources science?
What about in science? Is more information always better? Is it intrinsically valuable? And most importantly, are we making good use of all the data we now have access to, or are we becoming overloaded?
The rise of large datasets represents a wealth of potential information to better understand, manage, and protect our most vital resource. Satellites, continental-scale models, and reanalysis initiatives are generating hydrologic variables in high resolution across the globe for past, current, and future water resources conditions. These and similar breakthroughs over the last several years represent incredible opportunities, and challenges, for water resources professionals to extract the value in the data, and truly take advantage of it, to help us combat water-related issues across the globe.
As engineers and scientists, our instinct is to argue that more data is always better. The more total data available, the greater likelihood that the information to address a specific problem or decision will be embedded within the data. We rarely question it. We have spent decades developing sophisticated decision support systems (DSS’s) to translate large and often complex datasets into meaningful information to guide decision makers. While this is a critical step to create value from data, a DSS does not inherently quantify the value. Notably, across the water resources community, attempts to quantify the value of information have emerged relatively recently and remain uncommon. Why is this? Should this not be the most fundamental question – i.e. “is the information worth the investment?”
The challenge of the question
Quantifying the value of information is a very difficult task and, we believe, one that engineers and scientists are not well-equipped to tackle alone. Determining if information is worth the investment is inherently a multidisciplinary question that draws upon economics and sociology, as well as water and other natural resources sciences.
For several decades, economists have been developing techniques to measure the value of public goods that are not traded in markets, such as improvements in environmental quality. To overcome the lack of price data to determine value, economists often rely on observations about how human behavior responds to variations or changes in public goods. For example, by modeling how differences in water quality across sites affect where fishermen choose to fish, we can infer how much they value water quality improvements.
The same logic can be applied to assess values for information about water resources, such as water quality advisories or flood warnings. In this case, it requires developing models about how human behavior is affected by the information. Therefore, one of the main challenges in assigning a value to information is being able to systematically predict how humans would behave both with and without that information, for past and, more importantly, future scenarios.
A second challenge is finding the optimal approach to communicate the information to end-users and decision makers. In some cases, relatively small investments in improved communication could generate enormous and otherwise untapped value for end-users. Without those investments, there may be a wide gulf between the potential value and actual value of information. Ultimately, information only provides value if it helps users make better decisions to improve their well-being or the well-being of their community or organization.
Are we there yet?
What does this tell us about information overload for water resources? Is it possible we have more information than we can put to good use, or are we getting a good return on the investment? That question will no doubt always be difficult to generalize. However, there may be lessons we can learn from similar endeavors in other areas of science.
Researchers at RTI are turning to their past successes in economic valuation of health and risk information to find parallels for water resources information. If we can build upon these parallels to create a well-designed, multidisciplinary framework to quantify the value of different types of water resources information, it could go a long way to steer us clear from overload toward good information investments. We may find there is much value to be gained by developing new strategies to unlock the full potential of information in hand.
In other words, as the ‘disconnecting’ trend in other facets of life signifies, perhaps we just need to take a moment, process what we have ingested, and let our collective brain catch up.