Climate-induced landscape evolution is resulting in changes to biogeochemical and hydrologi- cal cycling. In the Arctic and sub-Arctic permafrost zones, rising air temperatures are warming, and in some regions even thawing, the frozen ground. Permafrost is a carbon sink. The thermal state of the ground therefore has important implications on carbon exchange with the atmo- sphere. Permafrost thaw mobilises previously sequestered carbon stocks, potentially turning these high latitude regions into a net carbon source. Borehole temperature and active layer depth measurements are the traditional means for monitoring permafrost, however these point measurements cannot easily be extrapolated to the landscape-scale; Earth Observation (EO) data may be used for such purposes. It is widely recognised that changes in the thermal state of permafrost may be associated with longterm changes in surface hydrology. As the ground shifts from a frozen to a thawed state, Arctic lakes display changes in surface extent. Therefore, it has become common practice to explore lake dynamics, using these as indicators of permafrost change; dynamics being the keyword. Surface hydrology is a dynamic process. Discharge studies in the Arctic and sub-Arctic regions are associated with flashy hydrographs. Currently, however, remote sensing of permafrost lake change is done on the scale of decades without explicitly taking seasonality and rapid hydrolog- ical phenology into consideration. To examine the seasonal changes in Arctic surface hydrology on the landscape scale high temporal resolution data are necessary. Synthetic aperture radar instruments are exemplary for such a task. The PhD research focuses on establishing operational techniques for mapping open surface water using synthetic aperture radar data, investigating straightforward raster classification methods and exploring their feasibility by undertaking map accuracy and sensitivity studies (chapter 3). The results are then used to justify error propagation when developing an auto- mated procedure that creates temporal composites of water body extent. These temporal water body classifications are the main EO product used to identify and image seasonal surface water change in Arctic permafrost environments (chapter 4). Furthermore, a terrain-based hydrolog- ical study is undertaken to explore the context of the detected changes and possible links to relief and stream channel network (chapter 5). The aim of this PhD is to demonstrate a new method of dynamic monitoring using the Euro- pean Space Agency’s Envisat Advanced Synthetic Aperture Radar, recommending its incorpo- ration in longterm lake change studies. Technical feasibility is explored, the inherent trade-off vii between spatial and temporal resolution discussed. An automated surface water change de- tection algorithm is developed and its applicability to monitoring spring floods is assessed; noting possible modifications to the drainage system given present-day land-use and land- cover changes that are taking place in the study area, the hydrocarbon-rich Yamalo-Nenets Autonomous District in the North of West Siberia (chapter 6). The key significance of this research is to improve the current knowledge of Arctic lake change by including spring flood events and seasonality in the equation. Therefore, it is strongly believed that this research is of benefit to the entire permafrost community.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:633478 |
| Date | January 2014 |
| Creators | Trofaier, Anna Maria |
| Publisher | University of Cambridge |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://www.repository.cam.ac.uk/handle/1810/246466 |
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