ABSTRACT Weak and clay-bearing rocks and soils are highly abundant worldwide. They are currently being investigated for their suitability for deep geological repositories for high-level radioactive waste. For this purpose, uniaxial compressive strength, tensile strength, and shear strength parameters are required. However, preparing suitable core samples is not always possible. Moreover, determining these strength parameters at various locations is often time-consuming and scale dependent. To overcome these difficulties, a portable and non-destructive penetration test can be used both in the laboratory and in the field. The objective of the current study is to develop a method for predicting the shear strength parameters of clay and weak rocks. Weak and clay-bearing geological materials were collected from various locations in Europe and Türkiye. In situ needle penetration tests were also conducted to make a preliminary assessment of the mechanical properties of the collected samples at their natural moisture content. Shear strength parameters of selected samples were determined using a triaxial compression test device (Hoek cell) and a modified direct shear box apparatus. The latter was specially developed for performing shear tests on soil-type materials. The results of the experimental studies suggest that the penetration resistance and shear strength parameters of the studied materials are statistically significantly related.
ABSTRACT Cover crops, which are plants or mixtures of plants grown primarily to enhance and protect soil health, are a key strategy in sustainable agriculture. Traditionally, they have been uniformly planted in a field typically during off-season when the main crops are not in competition. However, advancements in precision agriculture, particularly the integration of remote-sensing technology, demand more efficient seeding strategies based on field variability. The aims of this study were to assess the specific needs of a field in Aurora County, SD, and determine the type and optimal combinations of the cover crop mix. The cover crop species considered in this study included legumes, grasses, and brassicas. The remote-sensing data were extracted from Sentinel-2 satellite imagery. Soil samples were collected from 0 to 30 cm depth, and soil properties were measured. Additionally, topographic maps such as slope and aspect were extracted from light detection and ranging (LiDAR) data. The results of precision cover crop analyses showed that 6.5 percent (7.8 ha), 20.6 percent (24.7 ha), 38.1 percent (45.7 ha), 29.6 percent (35.5 ha), and 5.3 percent (6.3 ha) of the studied field should planted in the following mixtures of crops: rye, radish, and vetch; triticale, turnip, and vetch; triticale, radish, and clover; triticale, rapeseed, and pea; and barley, flax, and clover, respectively. The mixtures significantly improved soil properties by reducing compaction, increasing residue C/N ratio, and enhancing weed suppression compared with the control. The resulting map should be interpreted as a decision-support recommendation rather than a fully validated field prescription.
ABSTRACT This study evaluates andesite rock slope stability in İzmir, Türkiye, using mobile LiDAR (iPhone 14Pro) and hybrid classification systems. The acquired 3D point cloud (1.7 × 106 points) demonstrated high spatial accuracy when validated against global navigation satellite system data. Automated analysis via discontinuity set extractor revealed that applying a “full-persistence” assumption artificially reduces mean discontinuity spacing by 40–70 percent compared with a realistic “non-persistence” model, drastically underestimating rock block sizes. Kinematic analysis indicated a 40 percent probability of wedge failure, primarily driven by the highly persistent J6 set (lmax = 16 m). To directly compare slope mass rating (SMR), Q-slope, and rock hazard index (RHI) outputs, a “normalized risk index (Rindex)” was utilized. SMR yielded an overly optimistic evaluation Rindex = 0.41, failing to capture the geometric severity of the critical wedge. In contrast, RHI successfully identified this localized hazard (“moderate risk,” Rindex = 0.51) by directly accounting for geometric continuity. The Q-slope system proved to be the most conservative (Rindex = 0.60), indicating that the current 72° slope requires a reduction to 57°. The findings demonstrate that integrating mobile LiDAR with geometry-sensitive systems such as RHI provides a more reliable, targeted hazard assessment than traditional approaches.
ABSTRACT Topographic differencing using high-resolution elevation data is a powerful tool for investigating land surface change. Impacts from ground subsidence were first observed in southern Utah in 2005 after winter flooding eroded earth fissures near Beryl Junction. In 2009, ground cracks were discovered throughout a new development located in Cedar Valley. Subsequent investigations in Cedar and Parowan Valleys used field mapping, ground surveying, interferometric synthetic aperture radar, and groundwater budgets to demonstrate that subsidence due to groundwater overdraft and pore space compaction had been occurring for decades. This study examined topographic differences across both Cedar and Parowan Valleys based upon previously published 1 m light detection and ranging (LiDAR) digital elevation models collected in October 2011 and May 2020. Differencing, histogram analysis, threshold classification, profiling, and spatial statistics revealed that somewhere between ∼40 and ∼90 percent of the ∼740 km2area is experiencing subsidence with an average rate of 1.2 cm/yr. Three localized areas (Parowan, Enoch Graben, and Quichapa Lake), encompassing about 23 percent of the study area, are experiencing higher subsidence rates ranging from 2.3 to 5.4 cm/yr. Investigation of these subsidence features using LiDAR differencing demonstrated how detailed spatial variability in subsidence is directly linked to basin structure. Importantly, differential subsidence across basin faults can account for all the surface slip observed across some apparent Holocene fault scarps. In other cases, differential subsidence is decreasing the apparent offset across fault scarps. Topographic differencing results also revealed evidence of ongoing earth fissuring along the west side of Enoch Graben.
ABSTRACT Natural rock mass discontinuities form mechanically weak zones whose mechanical properties critically influence the stability and safety of engineered slopes. However, in practical engineering scenarios, large numbers of discontinuities cannot be manually surveyed and documented. To address this limitation, this study proposes an intelligent rock mass discontinuity identification method based on a complexity-penalized fuzzy C-means (FCM) algorithm, which automatically retains or eliminates clusters to ensure clustering accuracy. The proposed method is validated using typical discontinuities of a steep rock slope in the lower reservoir area of a pumped-storage power station. After discontinuity set classification, individual discontinuities are further extracted using an improved planar region-growing algorithm. The results demonstrate that (1) the proposed method overcomes the limitation of conventional FCM algorithms that require a predefined number of clusters, optimizes the cluster selection process, reduces computational cost, and significantly improves clustering accuracy; (2) the improved planar region-growing algorithm directly integrates planar geometric characteristics with candidate growth points, enabling the identification of small and fragmented discontinuities embedded within large planar surfaces; and (3) in the case study, the proposed method achieves a global accuracy of 92.15 percent and a mean intersection-over-union of 88.98 percent, indicating reliable clustering performance.
