| Summary: | The lower boundary of alpine permafrost extent is considered to be especially sensitive to climate change. Ice loss within permanently frozen debris and bedrock as a consequence of rising temperature is expected to increase the magnitude and frequency of potentially hazardous mass wasting processes such as debris flows. Previous research in this field has been generally limited by an insufficient understanding of the controls on debris flow formation. A particular area of uncertainty is the role of environmental preconditioning factors in the spatial and temporal distribution of debris flow initiation in high-alpine areas. This thesis aims to contribute by investigating the influence of permafrost and intensive frost weathering on debris flow activity in the New Zealand Southern Alps. By analysing a range of potential factors, this study explores whether debris flow systems subjected to periglacial influence are more active than systems outside of the periglacial domain. A comprehensive debris flow inventory was established for thirteen study areas in the Southern Alps. The inventory comprises 1534 debris flow systems and 404 regolith-supplying contribution areas. Analysis of historical aerial photographs, spanning six decades, identified 240 debris flow events. Frequency ratios and logistic regression models were used to explore the influence of preconditioning factors on the distribution of debris flows as well as their effect on sediment reaccumulation in supply-limited systems. The preconditioning factors considered included slope, aspect, altitude, lithology, Quaternary sediment presence, neo-tectonic uplift rates (as a proxy for bedrock fracturing), permafrost occurrence, and frost-weathering intensity. Topographic and geologic information was available in the form of published datasets or was derived from digital elevation models. The potential extent of contemporary permafrost in the Southern Alps was estimated based on the statistical evaluation of 280 rock glaciers in the Canterbury region. Statistical ...
|
|---|