Search Results (3)

This study explores the growing application of 3D remote sensing in geohazard studies, particularly for rock slope monitoring. It highlights the use of cost-effective Street View Imagery (SVI) and Unmanned Aerial Vehicles (UAV) through Structure-from-Motion (SfM) photogrammetry as tools for 3D rockfall monitoring. Using multi-temporal SVI and UAV Imagery from the Koto Panjang cliff in Indonesia, we quantify rockfall volume changes over seven years and assess associated geohazards. The results reveal a total rockfall retreat of 5270 m³, with an average annual rate of 7.53 m³/year. Structural analysis identified six major discontinuity sets and confirmed inherent instability within the rock mass. Kinematic simulations using SVI and UAV-derived data further assessed rockfall trajectories and potential impact zones. Results indicate that 40% of simulated rockfall deposits accumulated near existing roads, with significant differences in distribution based on scree slope angles. This emphasizes the role of scree slope in influencing rockfall propagation. In conclusion, SVI and UAV imagery presents a valuable tool for 3D point cloud reconstruction and rockfall hazard assessment, particularly in areas lacking historical data. The study showcases the effectiveness of using SVI and UAV imagery in quantifying historical past rockfall volume and identifies critical areas for mitigation strategies, highlighting the importance of scree slope angle in managing rockfall hazard. Full article

River flow forecasting is an essential tool to manage floods in the current era, especially for flash flooding scenarios in urban areas. This study focuses the flash flooding scenario in the Nullah Lai basin, which comprises the twin cities Islamabad and Rawalpindi. Steep slopes in the Margalla hills and Islamabad create high numbers of flash floods in the lower reaches of Rawalpindi, which are densely populated. When high-intensity rainfall occurs in the steep slopes of Margalla and Islamabad, high-volume floods with high velocity pour down, which instantaneously reaches the less-sloped Rawalpindi regions, which causes the raising of the water level in the stream, and flooding occurs. The section of the Nullah Lai Rawalpindi starting from the Qatarian bridge to the Gawalmandi bridge has always faced flash flooding over time. In the period of few hours, the water level reaches several fts in the nullah, which is why it is not possible to alert the people living on the banks in a timely manner, a problem that illuminates the need for a forecasting system at Nullah Lai. In the current research, the China Metrological Agency forecast center (CMA)’s ensemble forecast data have been utilized to achieve forecasts in the Nullah Lai. For this purpose, two initial objectives were set to achieve which basic needs are required process the data available in grib format from data centers. A digital model of the Nullah Lai was made using hydrology tools available in ArcGIS 10.3. A digital equation was obtained from gene expression modeling (GEP), which was later used to generate the ensemble stage forecast against the ensemble rainfall forecast. The results obtained show that the flash flooding phenomenon in Nullah Lai can, with some uncertainty, be predicted well in time. Using 3-days-ahead forecast data from CMA, the same floods were predicted 3 days before the event. This research also provides the procedure to use the ensemble forecast data in developing an automated model to generate the ensemble stage forecast for coming events. This study will help the administrative authorities better manage the upcoming floods and save lives and capital costs lost in the flash flooding phenomena which continuously happen in the basin of the Nullah Lai. Full article

Based on a previous risk calculation study conducted along a road corridor, risk is recalculated using a stochastic simulation by introducing variability into most of the parameters in the risk equation. This leads to an exceedance curve comparable to those of catastrophe models. This approach introduces uncertainty into the risk calculation in a simple way, and it can be used for poorly documented cases to compensate for a lack of data. This approach tends to minimize risk or question risk calculations. Full article