Publications

Hydrology for impact: building partnerships, blending knowledge and bracing for climate change

The hydrology community plays a critical role in understanding, communicating and managing hydroclimatic hazards and water security. As climate-related trends and risks emerge, there is an urgent need to help communities and organizations prepare for changes that are already underway and expected to become more severe. There is consensus about the need for transdisciplinary collaboration and participatory research to co-create knowledge to support informed decision-making. However, there is less clarity about how this should be done in practice. Achieving meaningful societal impact through research is not an exact science, and we do not propose a definitive framework or ‘recipe for success’. Instead, we reflect on our collective experiences over the last 20 years and surmise that strong partnerships, open communication and a willingness to embrace uncertainty can accelerate the impact of hydrological research on policy and practice and hence societal preparedness for climate change. We also advocate the development of new metrics—beyond research income and citations—to incentivize academics to plan for, and engage in, more impactful research-into-practice. We further call on government departments, research funders, professional bodies, societies and business associations to support the enabling environments needed to achieve this outcome.

This article is part of the discussion meeting issue ‘Hydrology in the 21st century: challenges in science, to policy and practice’.

Evaluating the Potential of ChatGPT to Support Climate Risk and Adaptation Assessment

Adaptation to climate change is increasingly urgent, as efforts to curb greenhouse gas emissions falter. Scaling up adaptation finance is essential to address climate risks, but no adaptation inventory covers all sectors and regions globally, especially for vulnerable, information-scarce communities. Large language models (LLMs) like ChatGPT could help bridge these gaps through rapid scoping of climate risks, adaptation options, programme costs and potential maladaptation. This paper uses structured conversations with ChatGPT to explore adaptations to climate hazards in the United Kingdom (for a national perspective), Bangladesh (for an education sector) and Ghana (for vulnerable communities). Queries were run multiple times to test consistency of outputs and contextual awareness. Early results are promising when compared with published information and expert insight. Nonetheless, practical steps can be taken for more effective use of LLMs, and these are captured in a checklist for users. Further research is needed to compare ChatGPT with other LLMs in giving reliable, domain-specific information about climate risks and priority adaptations.

Real-Time Mobile Transition Matrix Entropy Based on Eye and Head Movements

A novel second-order entropy-based oculometric, mobile transition matrix entropy (MTME), is presented for use in mobile eye tracking. Our approach calculates the MTME on the spheric gaze transition matrix, which is based on a sphere around each individual divided into equal-size plates (areas-of-interest). This approach allows for the correction of gaze location by head and body movements. Additionally, we demonstrate that the present approach is suitable for the calculation of eye movement entropy in real-time which opens the possibilities for use in human-computer interaction based on users’ attention characteristics. We provide empirical evidence from a collaborative task focused on climate change mitigation, demonstrating that MTME effectively captures collaboration dynamics by differentiating between interaction phases and video viewing. The paper presents the method’s details and discusses the metric’s sensitivity and analytical utility.

Enhancing Climate Information Accessibility: the Influence of Gaze Cues

Climate change data is complex and difficult to interpret, which may hinder public participation in mitigation efforts. This study examines whether gaze cueing can enhance the accessibility of this information by directing visual attention in the climate information- based collaboration task. Twenty participants collaborated in groups of four on a climate-related task while wearing mobile eye trackers. In the experimental condition, participants received gaze cues in an instructional video before performing the task, the purpose of which was to choose the best strategy to mitigate climate change. Statistical analysis using the Levenshtein distance on scanpaths showed that gaze cues fostered attention synchronization. The find- ings suggest that gaze cues in groups effectively guide attention through complex climate information, which is the first step to its comprehension.