Characterization of permafrost and terrain conditions for informed decision making

Permafrost is an important feature of the Northern Canadian landscape that has impacts on the natural and socio-economic environments. Permafrost and its associated ground ice can influence ecosystems through its influence on drainage patterns and ground stability as well as present challenges to northern development. Permafrost may warm and thaw in response to climate warming or disturbance to the ground surface such as that due to clearance of vegetation associated with development or natural processes such as fire. Thawing of permafrost can lead to landscape instability, thermokarst development and ground subsidence which have important implications for northern infrastructure, hydrological processes, ecosystems and northern lifestyles. Knowledge of permafrost conditions, including thermal state and ground ice conditions, and their spatial and temporal variations is critical for engineering design of infrastructure in northern Canada, the assessment of environmental impacts and the characterization of the impacts of climate change. Ongoing monitoring of permafrost conditions is essential to understand how these conditions may change over time, to assess impacts on natural and human systems, to develop strategies to mitigate these changes and to improve predictions of future conditions. Utilization of observations of permafrost thermal conditions, soil properties, climatic conditions and other environmental parameters along with analysis and modeling techniques has facilitated an improved characterization and explanation of the spatial variation in permafrost conditions across the Canadian north and quantification of the rate of increase in permafrost temperatures over the past two to three decades. A key achievement has been the enhancement of the permafrost thermal monitoring network to provide information for areas where little recent information was available. An improved baseline is now available against which change can be measured. This is essential for environmental management programs associated with northern development as a baseline is required against which project impacts can be calibrated. A major regional component is the Mackenzie Valley where key baseline and science gaps related to proposed hydrocarbon development are being addressed. Analysis of data collected through permafrost and terrain monitoring over the last 25 years along the existing Norman Wells to Zama pipeline corridor has been utilized to assess the impacts of pipeline construction and operation on the permafrost environment including characterization of changes in thaw depth and associated surface settlement. Integration of modeling techniques to investigate the source of the observed changes in the ground thermal regime have led to a better understanding of the relative influence of climate change and environmental disturbance. These results can be utilized to improve the assessment of environmental impacts and provide guidance for development of environmental monitoring and management programs for development projects. Knowledge has been generated that has informed decisions, environmental management and engineering design, including most notably a transfer of research results to the regulatory-environmental assessment process for the Mackenzie Gas Project. Research results have also been an important contribution to national and international climate change assessments. However, a number of knowledge gaps still exist. Significant areas (e.g. potential mineral resource development areas, arctic communities) still exist where there is insufficient information on permafrost thermal state and subsurface conditions to adequately characterize terrain sensitivity. An improved understanding of the interaction of processes in dynamic environments (e.g. Mackenzie Delta) is required to better attribute causes of environmental change. Improved understanding of feedbacks associated with changes in biophysical environment that accompany changes in permafrost conditions are required in order to reduce uncertainty in prediction of future conditions.

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