Climate History Controls Future Landslide Hazard

The intense precipitation associated with large storms can initiate thousands of landslides and debris flows, endangering lives and cause significant damage to infrastructure. Changes to the frequency and/or intensity of storms is a predicted consequence of anthropogenically-driven climate change (Rosenzweig et al., 2007), thus predictive models of landsliding are essential for mitigating these effects. Shallow landslides that initiate in soil are particularly destructive as they often initiate rapidly moving debris flows. Physically-based shallow landslide hazard models usually estimate landsliding a function of modern hydrologic, ecologic, and soil mechanical properties (Montgomery and Dietrich, 1994; Pack et al., 2001). The flaw in this approach is that it does not account for the "memory" of previous landslides in a catchment, where landslides are unlikely to occur twice in the same location within the short window of time (<1000 years). When landslide "memory" is considered, we hypothesise two possible effects on future landsliding: (1) the likelihood that extreme rainfall will create a large landslide event is dependent on the number of large storms that have recently occurred in a catchment, and (2) storms that initiate a 1000's of landslides may have a resonance within a landscape that causes landslides to cluster in time. Accounting for the combined role of precipitation and landscape resonance is of immediate concern as we begin to make predict hazards associated with climate change. The proposed research will quantify whether landslides are clustered in time, through the collection of a novel, large, millennial-scale dataset of landslide frequency. We will analyse landslide frequency using radiocarbon found at the base of 75 hollows (local depocentres located 10's of metres above channel heads) where shallow landslides initiate. These data, in conjunction with high resolution LiDAR topographic data, will drive the creation of a unique, probabilistic, landslide hazard model that estimates landslide hazard based on both recent precipitation and the potential resonance imparted by previous storms. Our novel landslide dataset and landslide hazard model will significantly improve our ability to predict the risks posed by landslides in current and future climate scenarios.

Who will benefit from this research?
This proposal models the debris flow hazard potential as a function of climate. Debris flows are a global hazard, affecting soil-mantled landscapes of high relief and precipitation. The primary beneficiaries of this exercise are the disaster management industry (particularly the insurance industry) and policy-makers from local and regional governments. Facilitating informed decision-making is therefore the key focus of our impact plan. We have identified two key groups that will benefit: (1) Our specific focus on North Carolina will benefit the policy-makers and insurance in this area, particularly as they make decision regarding proposed steep slope legislation. (2) The probabilistic basis of our model can be applied to any mountain range that is affected by debris flows, making this study of general interest to companies and policy-makers in debris flow-prone regions (e.g. Scottish regional governments, Swiss government).

How will they benefit from this research?
The key benefit from this research for both governmental and industrial partners is the ability to make decisions that are better informed by data. The advance provided by the modelling approach enables users of the model to explore how debris flow potential varies with different climate scenarios. Governmental organisations will be able to make informed decisions about the type of zoning and landuse restrictions that can occur in mountainous catchments. The insurance industry can use the model output to decide how best to insure infrastructure and property in areas prone to debris flows. The uniqueness of the model means that while it is of use within a British context, it can be exported to other countries and to Bristish industries working in these countries.