الفهرس 
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Abstract
Mining of oil sands results in huge disturbances to the natural ecosystem as soil and overburden materials are removed and stockpiled to provide access to mined materials. The mining process is followed by land reclamation, whereby disturbed landscapes are recovered with the intent to replicate the performance of natural watersheds. Modeling hydrological processes for reclaimed landscapes is essential for assessing the performance of different reclamation strategies and their evolution over time, and requires a reliable continuous source of input data. In pursuit of simulating various hydrological processes, such as soil moisture and actual evapotranspiration, a lumped generic system dynamics watershed (GSDW) model is developed. The validity of the proposed model is assessed thorough its capability in reproducing the hydrological behaviour of the reconstructed and natural watersheds. Availability of data is a major challenge that constrains not only the type of models used but also their predictive ability and accuracy. This study evaluated the utility of precipitation and temperature data from the North American Regional Reanalysis (NARR) for the hydrological modeling versus conventional platform (e.g., meteorological station). The results showed that the NARR was a good alternative to local weather station data for simulating soil moisture patterns and evapotranspiration fluxes despite the high complexity in simulating soil moisture dynamics and evapotranspiration flux. Subsequently, the calibrated/validated GSDW model is used along with the available historical meteorological records, from both Environment Canada and NARR, to estimate the maximum soil moisture deficit and annual evapotranspiration fluxes. A probabilistic framework was adopted; consequently, frequency curves of the maximum annual moisture deficit values are constructed and used to assess the probability of various reconstructed and natural watersheds can provide the desired moisture demands. The study showed a tendency for the reconstructed watersheds to provide less moisture for evapotranspiration than natural systems. The probabilistic framework was found to be useful for integrating information gained from mature natural watersheds and transfer the results to the new reconstructed system.Finally, this study has sought to develop a generalized understanding of the sensitivity of soil moisture patterns to changes in the projected precipitation and air temperature in the 21st century. Climate scenarios generated using daily, statistically downscaled, precipitation and air temperature outputs from global climate models (CGCM3), under A2 and B1 SRES, to simulate the corresponding soil moisture patterns using the GSDW model. The study suggests a decrease in the maximum annual moisture deficit due to the expected increase in annual precipitation and air temperature patterns, though actual evapotranspiration and runoff are likely to increase.