Climate History Controls Future Landslide Hazard
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Geosciences
Abstract
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.
Planned Impact
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.
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.
Organisations
People |
ORCID iD |
Simon Mudd (Principal Investigator) |
Publications
Grieve S
(2016)
How does grid-resolution modulate the topographic expression of geomorphic processes?
in Earth Surface Dynamics
Grieve S
(2016)
How long is a hillslope?
in Earth Surface Processes and Landforms
Hales T
(2018)
Modelling biome-scale root reinforcement and slope stability
in Earth Surface Processes and Landforms
Clubb F
(2014)
Objective extraction of channel heads from high-resolution topographic data
in Water Resources Research
Mudd S
(2016)
The CAIRN method: automated, reproducible calculation of catchment-averaged denudation rates from cosmogenic nuclide concentrations
in Earth Surface Dynamics
Clubb F
(2016)
The relationship between drainage density, erosion rate, and hilltop curvature: Implications for sediment transport processes CLUBB ET AL: DRAINAGE DENSITY
in Journal of Geophysical Research: Earth Surface
Description | We have developed several new tool for quantifying change in upland landscapes using high resolution digital topography. The first of these tools detects channel steepness which can be used to infer erosion rates. This process is not trivial: small channels will tend to be steeper than channels in large basins so our technique normalises for drainage area and allows comparison between rivers of different sizes. This allows detection of parts of the landscape that are eroding more quickly, possibly due to tectonic activity or land use change. We have also developed a technique to detect the upstream limit of drainage networks (sometimes called channel heads). The spacing and location of channel heads controls flood response to rainfall and pollutant and sediment transport. In addition the transition from channels to hillslopes is the point in the landscape where most landslides occur, so we will be further developing this tool in the future to look for landslide-prone terrain. |
Exploitation Route | Our software is already in use to both extract drainage networks and find areas of increased channel erosion. |
Sectors | Education,Environment |
URL | http://csdms.colorado.edu/wiki/Model:Chi_analysis_tools |
Description | This grant has supported the development of 2 new software tools. One of these is used to detect areas of increased channel erosion and the other used to find the upstream limit of channel networks (which controls flood response, amongst other processes). This software has been used independently in research looking at channel incision along gorges in France, and is currently being employed by the United States Geological Survey to detect fault activity in California. The software tool have been downloaded >100 times from a community model website (http://csdms.colorado.edu/wiki/Model:Chi_analysis_tools). |
First Year Of Impact | 2014 |
Sector | Education,Environment |
Impact Types | Policy & public services |
Title | Calculation of erosion rates from cosmogenic nuclides (CAIRN) |
Description | This software calculates the long term erosion rate of catchments based on the concentration of cosmogenic nuclides. |
Type Of Technology | Software |
Year Produced | 2016 |
Open Source License? | Yes |
Impact | A number of organisations are now using this software to calculate long-term erosion rates (I am aware of the United States Geological Survey, for example, using the software) |
URL | http://www.earth-surf-dynam.net/4/655/2016/ |
Title | Chi analysis tools |
Description | Software for detecting changing erosion rates in bedrock channels. |
Type Of Technology | Software |
Year Produced | 2014 |
Open Source License? | Yes |
Impact | This software has been downloaded >90 times and is being used by a number of independent groups, including the United States Geological Survey. |
URL | http://csdms.colorado.edu/wiki/Model:Chi_analysis_tools |
Title | Dreich algorithm for finding channel heads |
Description | This software uses high resolution digital topography to detect channel heads. |
Type Of Technology | Software |
Year Produced | 2014 |
Open Source License? | Yes |
Impact | This software is used to detect channel heads and has been downloaded 17 times as of Nov. 2014 (posted in May) |
URL | http://csdms.colorado.edu/wiki/Model:DrEICH_algorithm |
Title | Hillslope length calculation |
Description | This software calculates relief and lengths of hillslopes across landscapes, in order to detect changes in erosion processes and for tetecting erosion or tectonic transience. |
Type Of Technology | Software |
Year Produced | 2015 |
Open Source License? | Yes |
Impact | This program has allowed us to test a relationship between topographic gradient and sediment flux that will be used in erosion modelling in the future. |
URL | http://csdms.colorado.edu/wiki/Model:Hilltop_flow_routing |
Title | LSDChannelExtraction v 1.0 |
Description | Software for extracting channel networks from topographic data |
Type Of Technology | Software |
Year Produced | 2017 |
Open Source License? | Yes |
Impact | This software has been used to extract channel information for scientific papers, and also within a collaboration with SEPA (the Scottish environmental Protection Agency). The following statement was provided by Roberto Martinez at SEPA: "Thanks to the data produced using your tools/knowledge we have generated a complete new method for classifying river water bodies at national scale in Scotland. The water bodies were split into different reaches and a river type (cascade, plane riffle, meandering, etc.) was allocated to them. The allocation was based on an new algorithm for which you produced one of the inputs. The typology is used to classify the morphological status in Scotland which is reported in an annual basis using MImAS (Morphological Impact Assessment System)." |
URL | https://zenodo.org/record/824198#.Wi_ssFVl-Uk |
Title | LSDTopoTools2 v0.5 |
Description | Topographic analysis software |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | Topographic analysis software that has been widely used for research publications and by various national and regional agencies such as SEPA, the British Geological Survey, the United States Geological Survey, the Kentucky and West Virginia Geological Surveys, and a number of university-affiliated research groups. |
URL | https://github.com/LSDtopotools/LSDTopoTools2 |
Title | MuddPILE the Parsimonious Integrated Landscape Evolution Model |
Description | A simple landscape evolution model |
Type Of Technology | Software |
Year Produced | 2017 |
Open Source License? | Yes |
Impact | This model has been used in support of several scientific papers. |
URL | https://zenodo.org/record/997407#.Wi_uOlVl-Uk |
Title | Space-based Services to support resillient and sustainable Critical Infrastructure - Feasibility study |
Description | A pure python implementation of the elliptical Fourier analysis method described by Kuhl and Giardina (1982). This package is designed to allow the rapid analysis of spatial data stored as ESRI shapefiles, handling all of the geometric conversions. The resulting data can be written back to shapefiles to allow analysis with other spatial data or can be plotted using matplotlib. The code is built upon the pyefd module and it is hoped that this package will allow more geoscientists to apply this technique to analyze spatial data using the elliptical Fourier descriptor technique as there is no longer a data conversion barrier to entry. This package is also more feature rich than previous implementations, providing calculations of Fourier power and spatial averaging of collections of ellipses. |
Type Of Technology | Software |
Year Produced | 2017 |
Open Source License? | Yes |
Impact | This software has been cited four times, including in the transportation literature. |
URL | https://spatial-efd.readthedocs.io/en/latest/ |