Abstract:The frequency and severity of forest fires, coupled with changes in spatial and temporal precipitation and temperature patterns, are likely to severely affect the characteristics of forest and permafrost patterns in boreal eco-regions. Forest fires, however, are also an ecological factor in how forest ecosystems form and function, as they affect the rate and characteristics of tree recruitment. A better understanding of fire regimes and forest recovery patterns in different environmental and climatic conditions will improve the management of sustainable forests by facilitating the process of forest resilience. Remote sensing has been identified as an effective tool for preventing and monitoring forest fires, as well as being a potential tool for understanding how forest ecosystems respond to them. However, a number of challenges remain before remote sensing practitioners will be able to better understand the effects of forest fires and how vegetation responds afterward. This article attempts to provide a comprehensive review of current research with respect to remotely sensed data and methods used to model post-fire effects and forest recovery patterns in boreal forest regions. The review reveals that remote sensing-based monitoring of post-fire effects and forest recovery patterns in boreal forest regions is not only limited by the gaps in both field data and remotely sensed data, but also the complexity of far-northern fire regimes, climatic conditions and environmental conditions. We expect that the integration of different remotely sensed data coupled with field campaigns can provide an important data source to support the monitoring of post-fire effects and forest recovery patterns. Additionally, the variation and stratification of pre-and post-fire vegetation and environmental conditions should be considered to achieve a reasonable, operational model for monitoring post-fire effects and forest patterns in boreal regions.

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Abstract:In northern regions, river ice-jam flooding can be more severe than open-water flooding causing property and infrastructure damages, loss of human life and adverse impacts on aquatic ecosystems. Very little has been performed to assess the risk induced by ice-related floods because most risk assessments are limited to open-water floods. The specific objective of this study is to incorporate ice-jam numerical modelling tools (e.g. RIVICE, Monte-Carlo simulation) into flood hazard and risk assessment along the Peace River at the Town of Peace River (TPR) in Alberta, Canada. Adequate historical data for different ice-jam and open-water flooding events were available for this study site and were useful in developing ice-affected stage-frequency curves. These curves were then applied to calibrate a numerical hydraulic model, which simulated different ice jams and flood scenarios along the Peace River at the TPR. A Monte-Carlo analysis was then carried out to acquire an ensemble of water level profiles to determine the 1 : 100-year and 1 : 200-year annual exceedance probability flood stages for the TPR. These flood stages were then used to map flood hazard and vulnerability of the TPR. Finally, the flood risk for a 200-year return period was calculated to be an average of $32/ m 2 /a ($/m 2 /a corresponds to a unit of annual expected damages or risk).

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