Mines have an inherent risk of geotechnical failure in both rock excavations and tailings storage facilities. Geotechnical failure occurs when there is a combination of exceptionally large forces acting on a structure and/or low material strength resulting in the structure not withstanding a designed service load. The excavation of rocks can cause unintended rock mass movements. If the movement is monitored promptly, accidents, loss of ore reserves and equipment, loss of lives, and closure of the mine can be prevented. Mining companies routinely use deformation monitoring to manage the geotechnical risk associated with the mining process. The aim of this dissertation is to review the geotechnical risk management process to optimize the geotechnical risk management analysis. In order to perform a proper analysis of slope instability, understanding the importance as well as the limitations of any monitoring system is crucial. Due to the potential threat associated with slope stability, it has become the top priority in all risk management programs to predict the time of slope failure. Datasets from monitoring systems are used to perform slope failure analysis. Innovations in slope monitoring equipment in the recent years have made it possible to scan a broad rock face in a short period with sub-millimetric accuracy. Instruments like Slope Stability Radars (SSR) provide the quantitative data that is commonly used to perform risk management analysis. However, it is challenging to find a method that can provide an accurate time of failure predictions. Many studies in the recent past have attempted to predict the time of slope failure using the Inverse Velocity (IV) method, and to analyze the probability of a failure with the fuzzy neural networks. Various method investigated in this dissertation include: Minimum Inverse Velocity (MIV), Maximum Velocity (MV), Log Velocity (LV), Log Inverse Velocity (LIV), Spline Regression (SR) and Machine Learning (ML). Based on the results of these studies, the ML method has the highest rate of success in predicting the time of slope failures. The predictions provided by the ML showed ~86% improvement in the results in comparison to the traditional IV method and ~72% improvement when compared with the MIV method. The MIV method also performed well with ~75% improvement in the results in comparison to the traditional IV method. Overall, both the new proposed methods, ML and MIV, outperformed the traditional inverse velocity technique used for predicting slope failure.

Monitoring and maintaining the health of coastal wetlands is a global concern. The greatest threat to coastal wetlands in the Great Lakes Basin are anthropogenic removal and enrichment. The coastal wetlands in Georgian Bay are relatively undisturbed by humans, but face disturbance caused by reduced annual water-level fluctuations. Since these wetlands are critical habitat for many fish, bird, amphibian, and reptile species, many efforts to accurately monitor and maintain their health have been put into place. Recently, these wetlands have been experiencing an abrupt (~1 m) transition to higher water levels, following 14 years of sustained lows, which allowed trees and shrubs to invade the meadow vegetation zone. This sustained water-level pattern has never occurred in this region before, offering the unique opportunity to study wetlands undergoing a transition, where areas of 10+ years of upland plant species growth was inundated and became part of the wetland habitat. This thesis first investigates how this change in water level affects the distribution of meadow, emergent, floating, and submerged vegetation both in physical space and area. The second chapter of this thesis presents long-term water quality, macrophyte, and fish community monitoring using ecological indices. Water quality and macrophyte indices are robust enough to monitor wetlands undergoing a transition; however, issues arise in the calculation of the wetland fish index, as the changes in macrophyte distribution described in Chapter 1 impact the ability to replicate community sampling using fyke nets. The research done throughout this thesis is highly beneficial in adding to the limited knowledge of key factors impacting macrophyte community shifting. This work also identifies water-level scenarios where managers must adjust sampling protocols to succeed in effectively sampling wetland fish communities. / Thesis / Master of Science (MSc) / The coastal wetlands in the Georgian Bay area are primarily threatened by human development and the removal of annual water-level fluctuations. From 1999-2013, the water level decreased and remained low. In 2014, the water level rose about 1 m, causing flooding of grass and trees that had grown in the meadow zone during the 14 years when the water level was low. The first goal of this thesis is to explain how and why all wetland plants are relocating during this period. The second goal is to make sure that common indicators of wetland health (water quality, plants, and fish) can still be used during a time when flooding of grasses and trees was occurring in wetlands. The findings in this thesis contribute to the ability to predict and understand how the plants will shift within a wetland during a time of flooding, as well as informing managers on appropriate sampling protocols.

Slope stability plays an important role in rock engineering. During the design, construction and post design phases of rock slope stability, engineers and geologists need to pay close attention to the rock conditions within the rock slope to prevent slope failures, protect employees and maintain economic profit. This dissertation is based on a general four step procedure to construct and maintain rock slope stability with confidence. These four steps include field investigations, material testing and rock strength database, slope modelling and slope monitoring. The author provides past, present and alternatives methods for each step for the introduced slope stability procedure. Specific topics within each step are investigated displaying results, recommendations and conclusions. Step one involves data collection during field investigations for rock slope design. Orientation of rock core during drilling programs has become extremely pertinent and important for slope stability and underground mining operations. Orientation is needed to provide essential data to describe the structure and properties of discontinuities encountered during the design process to understand favourable and unfavourable conditions within a rock slope and underground openings. This chapter examines and discusses the limitations and benefits of four methods of obtaining borehole discontinuity orientations from drilling programs including clay-imprint, ACT I, II, III Reflex, EZY-MARK, and OBI/ABI Televiewer systems. Results, recommendations and conclusions are provided in this study. During step two to maintain rock slope stability, a rock strength database was created and used to correlate and compare RQD values to rock abrasion, shear strength and other rock characterization methods. Rock abrasion plays a significant role in geotechnical design, tunneling operations and the safety of foundations from scour; however, rock abrasion can be used to develop higher confidence in important parameters such as RQD and hardness. More rock abrasivity research is needed to provide a more accurate and compatible method for all subsurface material properties used in mining and civil engineering projects. This report will provide simple correlations relating abrasion resistance to RQD, UCS, Geological Strength Index (GSI) and Rock Mass Rating (RMR) of metamorphic rock. Results, discussions and conclusions are provided. Step 3 to determine rock slope stability entails utilizing computer modeling to predict failure conditions and wear rock mass properties. Computer modeling and slope monitoring for rock slopes have become essential to assess factor of safety (FOS) values to predict slope instability and estimate potential failure. When utilizing computer models, the limit equilibrium method (LEM) provides FOS values according to force and moment equilibrium; the shear strength reduction (SSR) technique calculates FOS using stress- and deformation-based analyses. Currently, both methods are prevalent in the engineering industry and applied by geotechnical engineers to analyze and determine stability in rock slopes for mining and civil engineering projects. Slope modeling techniques are then used to observe slope conditions and predict when slope failure may occur (FOS = 1.0). Comparison, results and conclusions are presented. Lastly, the dissertation (step 4: slope monitoring) will investigate past studies of FOS comparisons, review calculation methods and provide procedures and results using remote sensing data. The main objective of the dissertation is to provide engineers with essential information needed to ensure high confidence in factor of safety predictions and how alternative methods can be utilized. Recommendations, future research and conclusions regarding FOS and slope monitoring are provided within the dissertation.

This thesis investigates the design, implementation and validation of a multi-antenna GPS system to monitor the displacement of deforming slopes. The system utilises a switched antenna array design allowing data from multiple antennas to be sampled sequentially by one GPS receiver. The system provides quasi-continuous GPS observations that can produce a precise and reliable coordinate time-series of the movement of the slope under consideration. GPS observations and particularly those concerned with the monitoring of steep slopes, are subject to systematic errors that can significantly degrade the quality of the processed position solutions. As such, this research characterises the data in terms of multipath effects, the spectrum of the coordinate time-series, and the carrier to noise power density ratio of the raw GPS observations. Various GPS processing parameters are then investigated to determine optimal processing parameters to improve the precision of the resulting coordinate time-series. Results from data stacking techniques that rely on the daily correlation of the repeating multipath signature find that the GPS data actually decorrelates somewhat from day to day. This can reduce the effectiveness of stacking techniques for the high precision monitoring of steep slopes. Finally, advanced stochastic models such as elevation angle and carrier-to-noise weighting are investigated to optimise the precision of the coordinate time-series data. A new in-line stochastic model is developed based on weighting GPS observations with respect to the level of systematic error present within the data. By using these advanced types of stochastic models, reductions to the noise level of the coordinate time-series of approximately 20 and 25 percent are possible in the horizontal and height components respectively. / Results from an extensive field trial of this system on a deforming high-wall of an open-pit mine indicate that approximately 135mm of displacement occurred over the 16-week field trial. The precision of the coordinate time-series for surface stations approaches ±4.Omm and ±5.4mm in the horizontal and height components respectively. For sub-surface stations next to the mine wall, coordinate precision has been determined as ±4.9mm.component and ±7.6mm in the height component respectively.