Source: Earth’s Future
Coastal landscapes are constantly being reshaped by natural forces, and as climate change causes more frequent storms and sea level rise, that change will only intensify. Because these areas are densely populated with homes, tourist destinations, and industries, understanding how and where the coast will change is a pressing issue. However, reliable predictions that lead to actionable knowledge are rare.
Lentz et al. describe the state of knowledge regarding coastal evolution, highlight gaps in scientists’ understanding, and describe opportunities for integrating information from various models, data sources, and end users.
Current coastal evolution predictions are often focused on too specific a location and are therefore hard to generalize or analyze too large a region and therefore lack detail, the authors say. In addition, it’s challenging for researchers to link the effects of acute events, such as storms, with long-term trends like sea level rise.
Improving these simulations will likely require combining many different types of models, including physics-based numerical models, models based on empirical measurements, and statistical models that include machine learning. To fully understand potential changes, the authors note that it is also essential to consider both coastal processes and human actions.
The researchers recommend several ways to improve consistency and collaboration in the field of coastal change forecasting. First, standardizing approaches and outcomes would make it easier to produce national-scale predictions. Right now, the variety of tools used across different locations makes it difficult for scientists to compare results and communicate effectively. They also emphasize the need for using coordinated research approaches. Stronger transdisciplinary collaboration, accompanied by essential training and support, would also enable scientists to make better predictions, the researchers say.
Comparing predictions to real-world observations of coastal landscape change could also help untangle this multifaceted challenge. By studying how coastlines have already changed, researchers can validate models and choose those that are performing best. Such comparisons require datasets that adequately capture coastal landscape change across both time and space. Remote sensing data and the use of artificial intelligence (AI) for data processing may help provide these improved datasets, the researchers suggest.
Engaging end users during the project planning process is also helpful because only end users truly know what kind of information they need to adapt to landscape change. Knowing how to engage end users can be difficult for physical scientists, but various tools and specialized personnel exist who can help coordinate these interactions, the authors say. (Earth’s Future, https://doi.org/10.1029/2024EF005833, 2026)
—Saima May Sidik (@saimamay.bsky.social), Science Writer
Citation: Sidik, S. M. (2026), How to study coastal evolution, Eos, 107, https://doi.org/10.1029/2026EO260115. Published on 15 April 2026.
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