Underwater landslides are a destructive force, putting vital submarine infrastructure at serious risk and can even generate damaging tsunamis. By analyzing research completed from 2000 to 2025, scientists tracked this phenomenon to better understand what triggers the landslides, how they move and generate tsunamis, and the dangers they pose.

After reviewing the data, researchers determined three recommendations for submarine landslide research going forward. The results of this review were published in Ocean on 6 March.

“Given the rapid growth of global marine development, studying the mechanisms of triggering, movement, and disaster impacts behind submarine landslides has become increasingly urgent. More than 25% of global oil and gas production currently originates offshore, with projections indicating substantial growth in marine energy, including oil, gas, and wind energy, activities by 2040”, said Prof. Fawu Wang, a researcher at Tongji University in Shanghai, China.

Marine environments are complex, and landslides are caused by interacting factors. They are most often caused by earthquakes, but longer-term processes like rapid sedimentation, material like magma and mud settling in the ocean, and erosion also contribute to submarine landslides. Shaking caused by earthquakes increases sliding force, reduces the strength of the soil, and starts liquefaction, which is when loosely packed sediments weaken. Even even small earthquakes can trigger large submarine landslides.

Hydrodynamic forces are a more easily monitored cause of submarine landslides. “Waves, tides, bottom currents, and internal waves can trigger submarine landslides by increasing bottom shear stress, decreasing the shear strength of sediments, and causing dynamic changes in pore water pressure. These processes interact with the sediment structure, compromising its stability and potentially resulting in slope failure, particularly in regions with steep slopes or loose unconsolidated sediments”, said Prof. Wang. While scientists have been able to monitor the seafloor for the conditions leading to landslides, more research is needed to make the models more accurate.

There have been multiple studies to better understand how submarine landslides move using different techniques. They have used experimental devices and numerical simulations and physical models, but both methods are limited by the complexity of marine conditions. Researchers suggested that future research should look at modeling frameworks that incorporate machine learning, observation, and numerical models.

Finally, the review focused on research into how submarine landslides can cause a tsunami. Most tsunamis are caused by earthquakes, and those caused by submarine landslides are usually smaller in strength and scale. Even so, these tsunamis can be destructive, affecting coastal regions and engineering infrastructure that is right off the coast. Though these tsunamis are generally weaker, the initial wave can often be much higher than an earthquake-generated tsunami and cause significant damage.

Researchers also focused on specific offshore infrastructure, which is only increasing because of renewable energy developments. “Submarine landslides can result in catastrophic consequences, including pipeline suspension and rupture, platform overturning, and erosion of wind turbine foundations. As human activities extend into deeper seas, interactions between submarine landslides and marine engineering infrastructure are becoming more frequent, highlighting the urgent need to systematically uncover the disaster mechanisms associated with these events”, said Prof. Wang.

Looking ahead, researchers developed three conclusions that give guidance for future research into submarine landslides. First, they suggested that future research focus on understanding how different triggering factors interact and establishing metrics for predicting dangerous landslides. Second, they suggested improving numerical simulations to better reflect actual underwater environments. And third, they recommended improving modeling to incorporate machine learning and probabilistic analysis, along with incorporating coastal vulnerability for better tsunami risk assessment.

Other contributors include Youqian Feng and Ye Chen of Tongji University and Kongming Yan of University of Cambridge.

The Fundamental Research Funds of China for the Central Universities and the Interdisciplinary Collaborative Research Demonstration Project at Tongji University supported this research.

DOI Link:

https://doi.org/10.26599/OCEAN.2025.9470014

About Ocean

Ocean is an international peer-reviewed journal that offers open access and serves as a multidisciplinary platform for the state-of-the-art research and practice in the domains of ocean science, technology, and engineering. The journal is dedicated to publishing articles, reviews and perspectives in these areas, with the goal of promptly disseminating and promoting theoretical, numerical, site-based, and experimental advancements in the context of global sustainability.