New Zealand's landscape is a beauty to behold, but it's also a treacherous one. With each bout of extreme rainfall, landslides become an increasingly familiar consequence, threatening lives and infrastructure. The country has always been highly exposed to landslides due to its steep terrain and weak sedimentary rocks, and the removal of protective forest cover has only increased this susceptibility. High rainfall has long been a trigger, and now climate change is compounding the risk.
Climate projections show that extreme rainfall events are likely to intensify as the atmosphere warms, particularly under higher emissions scenarios. Powerful storms once considered rare are expected to occur more often, pushing more vulnerable slopes closer to failure and endangering communities and infrastructure below them. To respond effectively, New Zealand needs a clearer, nationally consistent picture of potential hot-spots for these rainfall-triggered landslides, both today and in the decades ahead.
Scientists are now better placed to untangle the dynamics that cause landslides, thanks to new advances in technology. Powerful statistical methods known as machine learning, a subfield of artificial intelligence, can analyze observations of where landslides have occurred in past storms, alongside the underlying environmental conditions that increase landslide susceptibility. Large datasets required to support machine learning are now widely available, thanks to the rapid growth of satellite imagery and derived products.
This technology has made it easier to map landslide damage immediately after a storm and to measure the underlying environmental conditions, including topography, forest height, and land cover and use across large areas. Machine learning algorithms then learn relationships between these different datasets, allowing us to build models that help us better understand and ultimately anticipate where rainfall-triggered landslides are more likely to occur.
My current research uses these approaches to examine how extreme rainfall interacts with New Zealand's slopes today, and how that relationship may shift under climate change. Preliminary findings suggest that, under higher-emissions climate scenarios with increases in rainfall intensity, the areas of New Zealand susceptible to rainfall-triggered landslides will expand. This relationship appears non-linear, meaning that even modest increases in extreme rainfall can result in much larger increases in susceptible areas.
Tall, established forests can help buffer this risk by strengthening soils and intercepting rainfall. Yet, under the more intense future storms modeled in these scenarios, even forested slopes will become more vulnerable. Limiting further warming remains critical to reducing risk in the long-term.
These insights support more strategic land-use decisions, such as where to increase permanent forest cover and where to limit high-risk activities. It can also help authorities understand the potential long-term costs of maintaining infrastructure in high-risk zones and support difficult but necessary conversations about which places may be too risky to inhabit at all.
New Zealand will always be prone to landslides, but being able to identify where risk is highest and how it is changing means better decisions about where and how we build. For communities in the potential path of future landslides, acting on that information today could help reduce the harm of tomorrow's storms.
