Browsing by Author "Kundu, P."

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    Landslides and debris flow triggered by the July 2024 extreme rainstorm in the Chooralmala watershed in Wayanad, India
    (Springer Science and Business Media Deutschland GmbH, 2025) Kolathayar, S.; Menon, V.; Kundu, P.
    [No abstract available]
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    Random Forest Classifier-Based Landslide Susceptibility Mapping for West Bengal
    (Springer Science and Business Media Deutschland GmbH, 2025) Kundu, P.; Kolathayar, S.; Umesh, P.
    Communities in hilly and mountainous areas are seriously at risk for their safety and way of life due to recurring events of landslides. Landslides frequently occur in West Bengal, India, resulting in significant infrastructure damage and fatalities. The current research utilizes a machine learning approach based on geographic information systems to create the West Bengal region’s landslide susceptibility map (LSM). Random forest classifier (RFC) has been selected from several Blackbox models since it has been proven to be a useful tool for creating reliable map of landslide susceptibility. To conduct the analysis, an inventory was made using historical landslide data gathered from several web sources. The environmental factors considered to analyze the study area are Elevation, Slope, Aspect, Flow Accumulation and Topographic Wetness Index (TWI). Other factors also were considered, like Distance from Lineament and Fault, Distance from railway or roadway, Average Annual Rainfall, and Normal Density Vegetation Index (NDVI). The model was trained on a 80% subset of the data and then validated on the remaining 20% data. The results showed that the RFC model accurately predicted the landslide occurrences, and the confusion matrix analyses the accuracy to be 92.12%. The model’s results created the LSM for the West Bengal (WB) region. Areas with a high, moderate, and low susceptibility to landslides were indicated on the map. In this location, the model overperforms by categorizing undesirable points as landslide prone. But it indicates the requirement of further study in the district of Purulia. The created LSM can be useful for different planning in the WB as well as can be extended to other regions, offering relevant data for decision-making. The accuracy of analysis can be further increased with better resolution field data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
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    Site-Specific Probabilistic Seismic Hazard Assessment of the New Indian Parliament Building Site in Delhi
    (Springer Science and Business Media Deutschland GmbH, 2025) Varma, N.; Kundu, P.; Kolathayar, S.
    Earthquakes are a significant geological hazard that causes destruction to life and property. A timely and thorough seismic hazard assessment of regions of national importance is necessary to ensure public safety. Delhi, the national capital of India, is classified as Zone IV in seismic zoning. A comprehensive probabilistic seismic hazard assessment (PSHA) was conducted to determine the seismic hazard at the site of the newly constructed Parliament building in New Delhi, focusing on seismically active faults in the area. The building was designed to withstand heavy earthquake loads, but the data used for its construction was based on older analytics. This study bridges that gap by using recent earthquake data. A catalogue completeness analysis was performed on homogenised and declustered earthquake data, and the area was divided into six subzones to calculate seismicity parameters for each source. Region-specific ground motion was evaluated using an attenuation relationship developed for North Indian states. The ground motion prediction equation (GMPE) specific to the region was integrated into the model to determine probabilistic seismic susceptibility. Peak ground acceleration (PGA) at the bedrock level was calculated for 2 and 10% probability of exceedance over a fifty-year period, and uniform hazard response spectra were determined for the site. The results show bedrock PGA values of 0.31 g and 0.14 g at 2% and at 10% exceedance probability over 50-years. These values are slightly higher than those found in previous studies of the region, indicating an increased seismic susceptibility. This study concludes that the region is susceptible to seismic activity, with an increase in bedrock PGA potentially leading to higher surface-level PGA. Further studies and geotechnical investigations are recommended to fully assess surface-level hazards. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
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    Synergistic Techniques for Landmass Movement Detection: A Review towards Sustainable Slope Stability Monitoring
    (Springer Science and Business Media Deutschland GmbH, 2025) Kundu, P.; Kolathayar, S.; Umesh, P.
    The lives of people, infrastructure, and economic stability are seriously threatened by compromised slope stability. This review explores various techniques used for landmass movement detection, highlighting their strengths and limitations. The paper emphasises on the importance of accurate and timely detection of unstable slopes for effective risk mitigation and early warning systems. Traditional methods like field surveys and topographic mapping are obsolete but crucial for understanding baseline conditions. Satellite-based remote sensing techniques like Interferometric Synthetic Aperture Radar (InSAR) and Light Detection and Ranging (LiDAR) offer vast area coverage and can detect subtle ground deformations, enabling rapid response strategies. Ground-based sensor networks with real-time monitoring capabilities complement these methods for slope stability assessment. Satellite-based detection methods using techniques like Differential Global Positioning System (DGPS) and Real-Time Kinematic (RTK) offer valuable insights for researchers to select and deploy monitoring suited for specific unstable slopes. Additionally, the Internet of Things (IoT) is revolutionising ground movement detection by enabling seamless sensor-to-central data connectivity for real-time monitoring and analysis. The accuracy of detection of landmass movement is increasing with advancements in detection techniques. Remotely sensed methods provide advantages like remotely detecting movement in difficult terrain but come with shortcomings in real-time measurement. Methods based on sensors and IoT are better suited for real-time monitoring, but devices are comparatively costly and difficult to install. It is suggested that research towards ensemble systems can solve the problem with real-time forecasting of upcoming geohazards and provide a sustainable solution for landslide problems in hilly regions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
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    The Shirur landslide of July 2024 triggered by intense rainfall and unchecked development
    (KeAi Communications Co., 2025) Kundu, P.; Menon, V.; Kolathayar, S.; Umesht, P.
    On the morning of July 16, 2024, a significant landslide occurred in Shirur of Uttara Kannada district, Karnataka, India. The landslide claimed seven lives, leaving one person missing and severely disrupting the transport network by blocking National Highway 66. The displaced debris travelled 180m across the highway and into the Gangavali River, causing a significant splash and damaging structures on the opposite bank. The event, characterised by a rotational slip, was triggered by a combination of anthropogenic activities and intense rainfall. The construction of National Highway 66, which involved the removal of the slope's toe without adequate protection for the excavation, significantly destabilised the area. On 15th July, the rain gauge in Ankola recorded rainfall of 260 ?mm. The accumulated rainfall calculated for Shirur using Inverse Distance Weightage (IDW) for the storm period of 4 days was 198 ?mm, which increased the pore water pressure within the soil, weakening its shear strength and leading to slope failure. This incident underscores the need for further analysis and the implementation of appropriate mitigation measures, as the region remains at risk for future landslides. The Shirur landslide serves as a critical reminder of the dynamic nature of such disasters, particularly when human activities exacerbate natural hazards. © 2025 The Authors