Landslides or slope failure pose a significant risk to human lives and infrastructures. The stability of slopes is controlled by various hydrological processes such as rainfall infiltration, soil water dynamics, and unsaturated soil behavior. Accordingly, soil hydrological monitoring and tracking the displacement of slopes become crucial to mitigate such risks by issuing early warnings to the respective authorities. In this context, there have been advancements in monitoring critical soil hydrological parameters and slope movement to ensure potential causative slope failure hazards are identified and mitigated before they escalate into disasters. With the advent of the Internet of Things (IoT), artificial intelligence, and high-speed internet, the potential to use such technologies for remotely monitoring soil hydrological parameters and slope movement is becoming increasingly important. This paper provides an overview of existing hydrological monitoring systems using IoT and AI technologies, including soil sampling, deploying on-site sensors such as capacitance, thermal dissipation, Time-Domain Reflectometers (TDRs), geophysical applications, etc. In addition, we review and compare the traditional slope movement detection systems, including topographic surveys for sophisticated applications such as terrestrial laser scanners, extensometers, tensiometers, inclinometers, GPS, synthetic aperture radar (SAR), LiDAR, and Unmanned Aerial Vehicles (UAVs). Finally, this interdisciplinary research from both Geotechnical Engineering and Computer Science perspectives provides a comprehensive state-of-the-art review of the different methodologies and solutions for monitoring landslides and slope failures, along with key challenges and prospects for potential future study.

Electrical resistivity tomography (ERT) has turned out to be one of the most applied and user-friendly geophysical methods in geotechnical and geoenvironmental research. ERT is an emerging technology that is becoming popular nowadays for investigating subsurface conditions. Multiple attributes of the technology using various electrode configurations significantly reduce measurement time and are suitable for applications even in hardly accessible mountain areas. It is a noninvasive test for subsurface characterization and a very sensitive method used to determine geophysical properties, i.e., structural integrity, water content, fluid composition, etc. This paper aimed to elucidate the ERT technique’s main features and applications in geotechnical and geoenvironmental engineering through four case studies. The first case study investigated the possible flow paths and areas of moisture accumulation after leachate recirculation in a bioreactor landfill. The second case study attempted to determine the moisture variation along highway pavement. The third case study explored the slope failure investigation by ERT. The fourth case study demonstrated the efficiency of the ERT method in the landfill evapotranspiration (ET) cover to investigate moisture variation on a broader scale and performance monitoring. In all of the four cases, ERT exhibited promising performance.

The integrity of earth infrastructure, encompassing slopes, dams, pavements, and embankments, is fundamental to the functioning of transportation networks, energy systems, and urban development. However, these infrastructures are increasingly threatened by a range of natural and anthropogenic factors. Conventional monitoring techniques, including inclinometers and handheld instruments, often exhibit limitations in spatial coverage and operational efficiency, rendering them insufficient for comprehensive evaluation. In response, Uncrewed Aerial Vehicles (UAVs) and Electrical Resistivity Imaging (ERI) have emerged as pivotal technological advancements, offering high-resolution surface characterization and critical subsurface diagnostics, respectively. UAVs facilitate the detection of deformations and geomorphological dynamics, while ERI is instrumental in identifying zones of water saturation and geological structures, detecting groundwater, characterizing vadose zone hydrology, and assessing subsurface soil and rock properties and potential slip surfaces, among others. The integration of these technologies enables multidimensional monitoring capabilities, enhancing the ability to predict and mitigate infrastructure instabilities. This article focuses on recent advancements in the integration of UAVs and ERI through data fusion frameworks, which synthesize surface and subsurface data to support proactive monitoring and predictive analytics. Drawing on a synthesis of contemporary research, this study underscores the potential of these integrative approaches to advance early-warning systems and risk mitigation strategies for critical infrastructure. Furthermore, it identifies existing research gaps and proposes future directions for the development of robust, integrated monitoring methodologies.

The hydrologic performance of evapotranspiration (ET) cover system for waste containment is significantly influenced by the hydraulic characteristics of cover soil such as saturated hydraulic conductivity (K_s), unsaturated hydraulic conductivity (K_Ψ), and soil water characteristic curve (SWCC). Due to environmental and field exposure conditions like freeze-thaw effect, wetting and drying cycle, plant root growth and death, along with animal and insect burrowing, these hydraulic properties of cover soil are highly susceptible to variation. Therefore, assessment of the changes in these soil hydraulic properties is vital for the evaluation of long-term cover performance. In this study, the hydraulic properties of ET cover soil were evaluated for three years of environmental and field exposure. The uniqueness of this study is highlighted by the non-destructive methodology, as destructive soil sampling was avoided to preserve the integrity of the cover system. Consequently, this study investigates the changes in the soil hydraulic properties based on field instrumentation and in situ testing in large-scale lysimeters constructed in the city of Denton landfill. Moisture and temperature sensors along with tensiometers were installed at the site in planned depth intervals. A Guelph permeameter was used to determine the field saturated hydraulic conductivity. The field investigation results indicated that K_s increased nearly 400 times the initial measurement, Van Genuchten’s α parameter increased by a factor of 41, and the n parameter decreased approximately 1.25 times the laboratory measured values after a three year span of field exposure. The results from this study establish the effect of hydraulic characteristic of soil on the cover hydrology and the potential implications for design considerations for long-term performance of the ET cover system for waste containment.