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Emily Read

Publications and source records attributed to Emily Read.

8 recordsLinked to original sources
USGS2025

Using visualization science to inform the design of environmental decision-support tools—A case study of the U.S. Geological Survey Waterwatch

Environmental decision-support tools are increasingly being used to serve both expert and non-expert audiences. Many existing tools are primarily expert-focused, and redesigning them can be challenging because experts and non-experts interact with tools differently, existing users may be resistant to changes, and there is little guidance on how to prioritize redesign efforts and demonstrate their efficacy. In this report, we present a case study of a user-centered redesign of an established environmental decision-support tool—the U.S. Geological Survey WaterWatch. WaterWatch supports flood, drought, and other water resource management decisions through the display of water levels at gages across the United States. Using a participatory process, we identified a functional change (replacing the existing rainbow colormap), created an alternative design, and tested the alternative’s usability through two general public surveys. The results showed that replacing the rainbow colormap with a more intuitive diverging colormap improves usability, regardless of the audience’s subjective preference for the rainbow color scheme. In addition, we demonstrated the importance of using legends to improve the audience’s understanding of the map symbols. This study demonstrates how user-centered design approaches can be used to inform the design of high-profile products and tools.

Scientific Investigations Report↗
USGS2023

The usability gap in water resources open data and actionable science initiatives

The open data movement represents a major advancement for informed water management. Data that are findable, accessible, interoperable, and reusable—or FAIR —are now prerequisite to responsible data stewardship. In contrast to FAIR, accessibility and usability case studies and guidelines designed around human access and understanding are lacking in the literature, especially for water resources. Such decision support guidelines are critical because (i) inherent visual design trade-offs are not best made using intuition or feedback (perceived preference), and (ii) choosing designs requires a nuanced understanding of why and how the design works (revealed effectiveness). Thus, the goal of this commentary is to highlight knowledge gaps and discuss a general usability testing method which can be applied to any water resources decision support product. The user-testing approach includes (i) interviews about visualization goals, audiences, and the uses and decisions made with the data products, (ii) diagnosis of usability challenges, and (iii) redesign of decision support products given best practices and control versus treatment with intended end-user audiences. We illustrate the method using high-profile U.S. Geological Survey water science products. In sum, optimizing and testing for usability and understandability are as central to stakeholder use as FAIR standards are, and warrant being part of the development of data products and geovisualizations.

Journal of the American Water Resources Associatio↗
USGS2023

The water cycle

An illustrated diagram of the water cycle. This is a modern, updated version of the widely used diagram featured on the USGS Water Science School. Notably, this new water cycle diagram depicts humans and major categories of human water use as key components of the water cycle, in addition to the key pools and fluxes of the hydrologic cycle. This product targets an 8th grade audience and is designed to be printed as a poster.

General Information Product↗
USGS2022

Teams, networks, and networks of networks advancing our understanding and conservation of inland waters

Networks are defined as groups of interconnected people and things, and by this definition, networks play a major role in the science of inland waters. In this article, we bring the latest social network research to understand and improve inland waters science and conservation outcomes. What we found is that relationships matter. Different teams and networks have different objectives and lifespans. Consider this: Data collection networks may persist for decades, whereas knowledge-generating teams may exist only for months. The structure of connections in a network determines how easily information or resources can flow or pass through a network, which then influences the ability of the network to accomplish work like creating and applying new knowledge, integrating knowledge across fields, or coordinating collective action. When independent networks designed around different purposes become connected to achieve new goals, a network of networks is formed, where each layer is a unique network defined by social, geographic, and temporal boundaries and distinct types of connections. This structure has a lot of potential for transformative work, but is especially susceptible to failure if one of the cross-network connections fails. From the smallest of inland waters research teams to the largest, multi-institutional, international collaborations, an understanding of how the connections between people are created and maintained can be used to set up conditions for success.

Book chapter↗
USGS2018

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Proceedings of the National Academy of Sciences of↗
USGS2018

Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes

Ecosystem metabolism and the contribution of carbon dioxide from lakes to the atmosphere can be estimated from free-water gas measurements through the use of mass balance models, which rely on a gas transfer coefficient ( k ) to model gas exchange with the atmosphere. Theoretical and empirically based models of k range in complexity from wind-driven power functions to complex surface renewal models; however, model choice is rarely considered in most studies of lake metabolism. This study used high-frequency data from 15 lakes provided by the Global Lake Ecological Observatory Network (GLEON) to study how model choice of k influenced estimates of lake metabolism and gas exchange with the atmosphere. We tested 6 models of k on lakes chosen to span broad gradients in surface area and trophic states; a metabolism model was then fit to all 6 outputs of k data. We found that hourly values for k were substantially different between models and, at an annual scale, resulted in significantly different estimates of lake metabolism and gas exchange with the atmosphere.

Inland Waters↗
USGS2016

Iterative ecological forecasting: Needs, opportunities, and challenges

A fundamental environmental challenge facing humanity in the 21st century and beyond is predicting the impacts of global environmental change. This challenge is complicated by the fact that we live on a non-stationary, unreplicated planet that is rapidly moving outside the envelope of natural variability into an historical non-analog world. In other words, while the past helps inform us about how the world has worked, it may no longer be the relevant frame of reference for management, conservation, and sustainability. In this future world the two questions at the foundation of sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect this trajectory?” These are, at their heart, questions about ecological forecasting.

Conference Paper↗