Debris flows are key drivers of erosion and sediment transport in mountainous areas, as well as significant natural hazards to both human populations and infrastructure. A large proportion of the death toll during natural disasters, such as major storms or earthquakes, is due to debris flows and debris avalanches in mountainous terrain. For example, a series of debris flows along a 50km coastal strip in Venezuela in 1999 caused the death of 15,000 people, the destruction of 23,000 houses and the severe damage of 65,000 more. This resulted in economic losses of more than US$ 2 billion (Jakob and Hungr, 2005). Furthermore, debris flow processes have been shown to play an important role in setting the length of valley networks and contributing to landscape denudation in high-relief settings.
However, our ability to understand debris flow hazard is severely limited by our poor understanding of where they occur, and what controls that spatial domain. Debris flow domains are difficult to accurately identify on a landscape scape, and we currently lack a reliable topographic metric for detecting areas of the landscape which have been affected. This is a major issue for quantifying hazard and making reasonable estimates of debris-flow risk to exposed populations and infrastructure. For example, debris flows after the 2015 Gorkha earthquake in Nepal have caused repeated disruption to road networks and loss of life, but we remain unable to anticipate which areas will continue to be affected by debris flows in future, and why. It also hinders attempts to predict reliable flow paths from mountainous regions, which is essential for assessing downslope areas at risk. Furthermore, our lack of knowledge on the spatial extent of these processes means that it is currently impossible to appraise how much erosion and sediment transport are carried out by debris flows over both short and long time scales. Until this is resolved, we cannot understand the full impact of mass wasting processes on the topography of mountain ranges.
In the past few decades, the amount of high-resolution topographic data available throughout the globe has increased exponentially, providing a revolution in our ability to identify geomorphic processes across the scale of whole landscapes and orogens. This project will aim to develop new techniques for mapping debris flow process domains from these high-resolution topographic data, by building on existing methods for extracting fluvial channel networks (Clubb et al., 2014). The student will combine the identification of debris flow domains from topographic data with extensive field work in Oregon, California, and Washington to validate the results of the remote sensing techniques.
The project will then explore how the spatial extent of the debris flow domain varies in different climatic, tectonic, and vegetation regimes on a landscape to orogenic scale. The student will use these new techniques to map the location of debris flow domains across sites in the western United States, where there are significant gradients in both climate and vegetation. They will explore how the length, width, and density of debris flow channels vary with these parameters by combining topographic analysis with remote sensing datasets. The outcome of this project will be a new technique for mapping a significant natural hazard which can be used as a community resource, as well as a better understanding of the long-term feedbacks between debris flow processes, climate, and vegetation.
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Figure 1: Debris flows in Kedarnath, India, after a heavy rainfall event, AGU Landslide Blog: https://blogs.agu.org/landslideblog/2013/10/26/kedarnath-photo/
The student will develop new techniques for mapping debris flow channels, by building upon existing methods of extracting valley and fluvial channel networks (Passalacqua et al., 2010, Clubb et al., 2014) implemented in LSDTopoTools, an open-source software package for topographic analysis. This will involve working with researchers at the University of Edinburgh, University of Glasgow, and Queen Mary University of London as part of a collaborative development effort. Experience in one or more programming languages (preferably Python/C++) is desirable, although training will be provided as part of this PhD project. The student will work primarily with high-resolution topographic data derived from lidar point clouds. As part of the project they will learn how to produce digital elevation models (DEMs) from point cloud data and how to analyse digital topography to understand geomorphic process.
The student will combine topographic analysis with field mapping of debris flow regimes and analysis of the channel morphology. This will involve at least two field seasons across sites with varying climate and vegetation characteristics, where we will map the location of debris flow channels and quantify their morphology. This may potentially involve the collection of high-resolution topographic data from a select number of debris flow channels using unmanned aerial vehicles (UAVs) and structure from motion techniques. Training will be provided during this project or by attendance at a workshop, such as a NERC Advanced Training Short Course (https://nerc.ukri.org/funding/available/postgrad/advanced/atsc/).
The student will then combine this analysis of the spatial extent and morphology of debris flow channels with remote sensing datasets in order to investigate the impact of climate, vegetation, and tectonics on debris flow processes. The student will process and analyse satellite-based datasets such as precipitation metrics (TRMM), vegetation estimates (NDVI), as well as global lithology datasets (e.g., GLiM; Haartman and Moorsdorf, 2012).
Literature review, training in programming and topographic analysis and initial software development, field mapping of debris flow processes, collection of high-resolution topographic datasets from mountainous regions in different climate zones.
Further development and finalisation of new debris flow mapping techniques, validation with field mapping datasets, training in use of climate remote sensing datasets, presentation of new techniques at conferences.
Application of mapping techniques to determine the distribution of debris flows across varying climatic regimes, presentation of results at conferences, writing up of main results.
Finalising results, writing up and presentation of final thesis, preparation of papers for publication.
During this project the student will receive training in programming with Python and potentially C++, as well as the analysis of large environmental datasets. They will also learn how to obtain, process, and analyse high-resolution topographic datasets both from UAVs and from airborne lidar sources. They will learn how to move beyond traditional desktop-based GIS software in the analysis of topography and become comfortable with performing analyses in a Linux environment on supercomputing clusters.
The student will also conduct two field seasons during which they will learn how to identify and quantify the morphology of debris flow channels. They will also be trained in the analysis of remote sensing datasets such as the Global Precipitation Measurement (GPM) mission and normalised difference vegetation index (NDVI), and global lithology datasets.
As part of this project the student will also present their results at both international and national conferences, where they will further develop their skills in presenting and communicating scientific research. The student is also encouraged to apply for small grants through the Durham Institute of Hazard, Risk and Resilience (https://www.dur.ac.uk/ihrr/) which will allow them to gain experience with writing funding proposals.
References & further reading
Clubb, F. J., Mudd, S. M., Milodowski, D. T., Hurst, M. D., & Slater, L. J. (2014). Objective extraction of channel heads from highâ€resolution topographic data. Water Resources Research, 50(5), 4283-4304.
Hartmann, J., & Moosdorf, N. (2012). The new global lithological map database GLiM: A representation of rock properties at the Earth surface. Geochemistry, Geophysics, Geosystems, 13(12).
Jakob, M., & Hungr, O. (2005). Debris-flow hazards and related phenomena. Berlin: Springer.
Passalacqua, P., Do Trung, T., Foufoula-Georgiou, E., Sapiro, G., & Dietrich, W. E. (2010). A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths. Journal of Geophysical Research: Earth Surface, 115(F1).
Stock, J., & Dietrich, W. E. (2003). Valley incision by debris flows: Evidence of a topographic signature. Water Resources Research, 39(4).
Open source software for topographic analysis: https://lsdtopotools.github.io/
For more information please contact Fiona Clubb: e-mail: firstname.lastname@example.org, phone: +44191 334 1852