Fully coupled elastoplastic hydro-mechanical analysis of unsaturated porous media using a meshfree method

This paper presents the first application of an advanced meshfree method, ie, the edge-based smoothed point interpolation method (ESPIM), in simulation of the coupled hydro-mechanical behaviour of unsaturated porous media. In the proposed technique, the problem domain is spatially discretised using a triangular background mesh, and the polynomial point interpolation method combined with a simple node selection scheme is adopted for creating nodal shape functions. Smoothing domains are formed on top of the background mesh, and a constant smoothed strain, created by applying the smoothing operation over the smoothing domains, is assigned to each smoothing domain. The deformation and flow models are developed based on the equilibrium equation of the mixture, and linear momentum and mass balance equations of the fluid phases, respectively. The effective stress approach is followed to account for the coupling between the flow and deformation models. Further coupling among the phases is captured through a hysteretic soil water retention model that evolves with changes in void ratio. An advanced elastoplastic constitutive model within the context of the bounding surface plasticity theory is employed for predicting the nonlinear behaviour of soil skeleton. Time discretisation is performed by adopting a three-point discretisation method with growing time steps to avoid temporal instabilities. A modified Newton-Raphson framework is designed for dealing with nonlinearities of the discretised system of equations. The performance of the numerical model is examined through a number of numerical examples. The state-of-the-art computational scheme developed is useful for simulation of geotechnical engineering problems involving unsaturated soils.     

A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold cross-validation approach for land subsidence susceptibility mapping

In this paper, we evaluate the predictive performance of an adaptive neuro-fuzzy inference system (ANFIS) using six different membership functions (MF). In combination with a geographic information system (GIS), ANFIS was used for land subsidence susceptibility mapping (LSSM) in the Marand plain, northwest Iran. This area is prone to droughts and low groundwater levels and subsequent land subsidence damages. Therefore, a land subsidence inventory database was created from an extensive field survey. Areas of land subsidence or areas showing initial signs of subsidence were used for training, while one-third of inventory database were reserved for testing and validation. The inventory database randomly divided into three different folds of the same size. One of the folds was chosen for testing and validation. Other two folds was used for training. This process repeated for every fold in the inventory dataset. Thereafter, land subsidence related factors, such as hydrological and topographical factors, were prepared as GIS layers. Areas susceptible to land subsidence were then analyzed using the ANFIS approach, and land subsidence susceptibility maps were created, whereby six different MFs were applied. Lastly, the results derived from each MF were validated with those areas of the land subsidence database that were not used for training. Receiver operating characteristics (ROC) curves were drawn for all LSSMs, and the areas under the curves were calculated. The ROC analyses for the six LSSMs yielded very high prediction values for two out of the six methods, namely the difference of DsigMF (0.958) and GaussMF (0.951). The integration of ANFIS and GIS generally led to high LSSM prediction accuracies. This study demonstrated that the choice of training dataset and the MF significantly affects the results.     

Risk assessment of polycyclic aromatic hydrocarbons in the West Port semi-enclosed basin (Malaysia)

Sediment samples collected from the West Port, the west coastal waters of Malaysia, were analyzed by standard methods to determine the degree of hydrocarbon contamination and identify the sources of polyaromatic hydrocarbons (PAHs). Concentrations of PAHs in the port sediments ranged from 100.3 to 3,446.9 μg/kg dw. The highest concentrations were observed in stations close to the coastline, locations affected by intensive shipping activities and industrial input. These were dominated by high-molecular-weight PAHs (4–6 rings). Source identification showed that PAHs originated mostly pyrogenically, from the combustion of fossil fuels, grass, wood, and coal or from petroleum combustion. Regarding ecological risk estimation, only station 7 was moderately polluted, the rest of the stations suffered rare or slight adverse biological effects with PAH exposure in surface sediment, suggesting that PAHs are not considered as contaminants of concern in the West Port.     

Landslide detection using deep learning and object-based image analysis

Landslides - Recent landslide detection studies have focused on pixel-based deep learning (DL) approaches. In contrast, intuitive annotation of landslides from satellite imagery is based on...     

How deep can forest vegetation cover extend their hydrological reinforcing contribution?

An experimental campaign was set up to quantify the contribution of evapotranspiration fluxes on hillslope hydrology and stability for different forest vegetation cover types. Three adjacent hillslopes, respectively, covered by hardwood, softwood, and grass were instrumented with nine access tubes each to monitor soil water dynamics at the three depths of 30, 60, and 100 cm, using a PR2/6 profile probe (Delta‐T Devices Ltd) for about 6 months including wet periods. Soil was drier under softwood and wetter under grass at all the three depths during most of the monitoring period. Matric suction derived via the soil moisture measurements was more responsive to changes in the atmospheric conditions and also recovered faster at the 30 cm depth. Results showed no significant differences between mean matric suction under hardwood (101.6 kPa) with that under either softwood or grass cover. However, a significant difference was found between mean matric suction under softwood (137.5 kPa) and grass (84.3 kPa). Results revealed that, during the wettest period, the hydrological effects from all three vegetation covers were substantial at the 30 cm depth, whereas the contribution from grass cover at 60 cm (2.0 kPa) and 100 cm (1.1 kPa) depths and from hardwood trees at 100 cm depth (1.2 kPa) was negligible. It is surmised that potential instability would have occurred at these larger depths along hillslopes where shallow hillslope failures are most likely to occur in the region. The hydrological effects from softwood trees, 8.1 and 3.9 kPa, were significant as the corresponding factor of safety values showed stable conditions at both depths of 60 and 100 cm, respectively. Therefore, the considerable hydrological reinforcing effects from softwood trees to the 100 cm depth suggest that a hillslope stability analysis would show that hillslopes with softwood trees will be stable even during the wet season.     

Using constrained inversion of gravity and magnetic field to produce a 3D litho‐prediction model

Geologically constrained inversion of gravity and magnetic field data of the Victoria property (located in Sudbury, Canada) was undertaken in order to update the present three‐dimensional geological model. The initial and reference model was constructed based on geological information from over 950 drillholes to constrain the inversion. In addition, downhole density and magnetic susceptibility measured in six holes were statistically analysed to derive lower and upper bounds on the physical properties attributed to the lithological units in the reference model. Constrained inversion of the ground gravity and the airborne magnetic data collected at the Victoria property were performed using GRAV3D and MAG3D, respectively. A neural network was trained to predict lithological units from the physical properties measured in six holes. Then, the trained network was applied on the three‐dimensional distribution of physical properties derived from the inversion models to produce a three‐dimensional litho‐prediction model. Some of the features evident in the lithological model are remnants of the constraints, where the data did not demand a significant change in the model from the initial constraining model (e.g., the thin pair of diabase dykes). However, some important changes away from the initial model are evident; for example, a larger body was predicted for quartz diorite, which may be related to the prospective offset dykes; a new zone was predicted as sulfide, which may represent potential mineralisation; and a geophysical subcategory of metabasalt was identified with high magnetic susceptibility and high density. The litho‐prediction model agrees with the geological expectation for the three‐dimensional structure at Victoria and is consistent with the geophysical data, which results in a more holistic understanding of the subsurface lithology.     

Soil water dynamics under different forest vegetation cover: Implications for hillslope stability

Though it is well known that vegetation affects the water balance of soils through canopy interception and evapotranspiration, its hydrological contribution to soil hydrology and stability is yet to be fully quantified. To improve understanding of this hydrological process, soil water dynamics have been monitored at three adjacent hillslopes with different vegetation covers (deciduous tree cover, coniferous tree cover, and grass cover), for nine months from December 2014 to September 2015. The monitored soil moisture values were translated into soil matric suction (SMS) values to facilitate the analysis of hillslope stability. Our observations showed significant seasonal variations in SMS for each vegetation cover condition. However, a significant difference between different vegetation covers was only evident during the winter season where the mean SMS under coniferous tree cover (83.6 kPa) was significantly greater than that under grass cover (41 kPa). The hydrological reinforcing contribution due to matric suction was highest for the hillslope with coniferous tree cover, while the hillslope with deciduous tree cover was second and the hillslope with grass cover was third. The greatest contributions for all cover types were during the summer season. During the winter season, the wettest period of the monitoring study, the additional hydrological reinforcing contributions provided by the deciduous tree cover (1.5 to 6.5 kPa) or the grass cover (0.9 to 5.4 kPa) were insufficient to avoid potential slope failure conditions. However, the additional hydrological reinforcing contribution from the coniferous tree cover (5.8 to 10.4 kPa) was sufficient to provide potentially stable hillslope conditions during the winter season. Our study clearly suggests that during the winter season the hydrological effects from both deciduous tree and grass covers are insufficient to promote slope stability, while the hydrological reinforcing effects from the coniferous tree cover are sufficient even during the winter season. Copyright © 2018 John Wiley & Sons, Ltd.     

Paleoenvironment of geomorphic surfaces of an alluvial fan in the eastern Isfahan,Iran, in the light of micromorphology and clay mineralogy

Alluvial fans are one of the most important landforms in geomorphological and paloenvironmental studies. The objective of this study was the application of clay mineral assemblages and micromorphological properties of the studied paleosols in the geomorphic surfaces of an alluvial fan in the eastern Isfahan as proxies for paleoenvironmental and paleoclimatic changes. Micromorphology, X-ray diffraction, and scanning electron microscopy approaches were used to study the representative pedons. The results indicated that the illuviation process in the calcareous soils of the arid regions of the eastern Isfahan was probably in response to Quaternary moist conditions. There was no significant difference between clay coating properties of the studied relict and buried paleosols. Clay mineralogical study suggested that kaolinite and illite were inherited from the parent materials, while smectite and palygorskite were formed in the soil environment. Paleoargillic horizon was characterized by smectite and calcic (especially the calcrete) horizons were dominated by palygorskite. Palygorskite was accumulated by both neoformation and illuviation processes. High clay content, high intensity of smectite peak, and activity of the illuviation process in paleoargillic horizon demonstrated the seasonality of climate (rainfall) even in the moist periods of Quaternary in Central Iran. Clay mineralogical assemblages suggested a trend of increasing environmental aridity in the study area. This study, therefore, highlighted the role of clay mineralogical investigations in arid lands’ geomorphological and paleoenvironmental researches.