Boundary depletion rate and drawdown in leaky wedge‐shaped aquifers

This study presents analytical solutions of the three‐dimensional groundwater flow to a well in leaky confined and leaky water table wedge‐shaped aquifers. Leaky wedge‐shaped aquifers with and without storage in the aquitard are considered, and both transient and steady‐state drawdown solutions are derived. Unlike the previous solutions of the wedge‐shaped aquifers, the leakages from aquitard are considered in these solutions and unlike similar previous work for leaky aquifers, leakage from aquitards and from the water table are treated as the lower and upper boundary conditions. A special form of finite Fourier transforms is used to transform the z‐coordinate in deriving the solutions. The leakage induced by a partially penetrating pumping well in a wedge‐shaped aquifer depends on aquitard hydraulic parameters, the wedge‐shaped aquifer parameters, as well as the pumping well parameters. We calculate lateral boundary dimensionless flux at a representative line and investigate its sensitivity to the aquitard hydraulic parameters. We also investigate the effects of wedge angle, partial penetration, screen location and piezometer location on the steady‐state dimensionless drawdown for different leakage parameters. Results of our study are presented in the form of dimensionless flux‐dimensionless time and dimensionless drawdown‐leakage parameter type curves. The results are useful for evaluating the relative role of lateral wedge boundaries and leakage source on flow in wedge‐shaped aquifers. This is very useful for water management problems and for assessing groundwater pollution. The presented analytical solutions can also be used in parameter identification and in calculating stream depletion rate and volume. Copyright © 2011 John Wiley & Sons, Ltd.     

Iranian ultrapotassic volcanism at ~11 Ma signifies the initiation of post‐collisional magmatism in the Arabia–Eurasia collision zone

Ultrapotassic rocks are a common, but volumetrically minor, hallmark of post‐collisional magmatism along the Alpine–Himalayan orogenic belt. Here, we document the occurrence of ultrapotassic volcanic rocks from the Eslamy peninsula, NW Iran in the Arabia–Eurasia collision zone. Our results indicate that magma genesis involved melting of phlogopite‐ and apatite‐bearing peridotites in the sub‐continental lithospheric mantle at ~11 Ma. These peridotites likely formed by metasomatism involving components derived from subducted sediments during Neotethyan subduction. The ~11 Ma ultrapotassic volcanism was preceded by a magmatic gap of ~11 Ma after the cessation of arc magmatism in NW Iran and Armenia, thus likely representing the initiation of post‐collisional magmatism. The age coincides with the onset of collision‐related magmatic activity and topographic uplift in the Caucasus–Iran–Anatolia region, and also with other regional geological events including the closure of the eastern Tethys gateway, the end of Arabian underthrusting and the start of escape tectonics in Anatolia.     

Seismic behaviour of pile in three-layered soil (case study: Babol City Center Project)

The significance of liquefaction-related damage to pile foundations has been clearly demonstrated by the major earthquakes occurring during past years. The current project investigates the seismic behaviour of a single pile in the three-layered soil of the Babol City centre site (located in Babol City, Mazandaran Province, Iran). The site soil consists of sandy and clayey soils modelled based on the data collected from drilled boreholes. Numerical analysis was performed using Flac2D finite difference program. Three different natural ground motion records are considered, and the influence of each earthquake on the bending moment and lateral displacement of the simulated pile is investigated. In addition, the effect of vertical surcharge on the settlement of the pile during the earthquakes is investigated. Results illustrate that the maximum bending moment has occurred on the interface of liquefiable and non-liquefiable soil layers.     

Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 136 landside locations were constructed from various sources. Then the landslide inventory map was randomly split into a training dataset 70 % (95 landslide locations) for training the ANN model and the remaining 30 % (41 landslides locations) was used for validation purpose. Nine landslide conditioning factors such as slope, slope aspect, altitude, land use, lithology, distance from rivers, distance from roads, distance from faults, and rainfall were constructed in geographical information system. In this study, both MLP and RBF algorithms were used in artificial neural network model. The results showed that MLP with Broyden–Fletcher–Goldfarb–Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. The success rate curve showed that the area under the curve for RBF and MLP was 0.9085 (90.85 %) and 0.9193 (91.93 %) accuracy, respectively. Similarly, the validation result showed that the area under the curve for MLP and RBF models were 0.881 (88.1 %) and 0.8724 (87.24 %), respectively. The results of this study showed that landslide susceptibility mapping in the Vaz Watershed of Iran using the ANN approach is viable and can be used for land use planning.     

A simplified stress analysis of rising salt domes

We use a simple analytical model to estimate the stress field in density‐driven, rising salt domes and adjacent sediments, and to describe the evolution of these domes. We show that the pressure exerted by the salt pushing out against its wall rocks (the salt pressure) decreases linearly up the flank of the dome, but is always greater than the overburden stress. In fact, the salt pressure normal to the dome boundary is everywhere the maximum principal stress, whereas the hoop stress parallel to the circumference of the dome is the minimum stress. In addition, we quantitatively describe the critical stages of salt dome evolution (initiation, upbuilding, and downbuilding), relating these stages to sedimentation rate and basin thickness. This analysis also shows that even the highest sedimentation rates are unlikely to accumulate enough sediments to bury downbuilding domes as long as the salt supply is unrestricted. Despite the simplicity of the model, its predictions are in good agreement with field observations near salt domes. Overall, our analytical model can provide critical insight into the stress field perturbation in and near rising salt domes and can be used to assess the accuracy of numerical models and field measurements near these domes.     

Field and dual magnetic susceptibility proxies for heavy metal pollution assessment in the urban soil of Al-Karak City, South Jordan

A total of 115 urban soil samples collected on grid bases from Al-Karak, South Jordan, were investigated for their field and dual-frequency magnetic susceptibility (χ _field, χ _d) and heavy metal content using Bartington susceptibility meters and ICP-MS. The upper soils have higher magnetic susceptibility values than lower soils, and large particles contain more heavy metals and higher magnetic susceptibility than smaller particles. This might be attributed to the lack of pedogenesis due to arid climate influence. Within the upper soil all heavy metal showed positive significant correlation with upper soil low-frequency χ _dlf. This was evident from the distribution maps produced by Surfer 9.0 for χ _dlf and heavy metals. The results showed that higher χ _dlf is associated with traffic-dominated sites more than other areas. The frequency-dependent susceptibility (χfd %) falls between 2 and 10 %, which indicate the presence of admixture of fine supermagnetic particles. Mildly correlation exists between χfd % and χ _dlf, which implies that soils contain anthropogenic multi-domain grains. Selected samples have been analyzed for their mineral constituents; the results indicate the presence of magnetite as the main magnetic mineral. This confirms the anthropogenic source of pollution mainly from the vehicle-related materials. The results indicate the applicability of magnetic susceptibility for pollution detection.     

Study of the Engineering Geological Problems of the Havasan Dam,with Emphasis on Clay-Filled Joints in the Right Abutment

Havasan dam site is located in northwest of Iran. The planned concrete dam is to be built on Cretaceous limestone. Faulted and fractured limestone is exposed at the dam abutments and in the reservoir area. Rock mass properties including the deformation modulus and uniaxial compressive strength were calculated using different rock mass classification systems (RMR, Q, GSI and DMR). Laboratory tests indicate that joint filling materials contain clay with low to high plasticity (CL to CH) and low to medium potential swelling pressures. X-ray diffraction analysis confirms that the reason for potential swelling of joint fillings is the existence of clay minerals (such as illite and montmorillonite). The study results about the shear strength of clay-filled joints show that under JRC–JCS condition (laboratory scale), JRC _n –JCS _n (large scale) and normal stress equal to 0.25–4 MPa, the range of shear strength of clay-filled joints will be equal to 0.2–2.17 and 0.14–1.72 MPa. In some areas dissolution along the joints results in high permeability, especially in the right abutment. Three dominant joint sets occur in the exploration galleries which have been excavated in the right abutment. The maximum aperture of these joints varies from 7 to 9 cm, and the joints are typically filled with clay. Preliminary analysis shows that the presence of open joints which will cause seepage of water, combined with the impact of the clay-filled joints and forces acting on the slopes, could lead to slope failures and rock falls. In addition, the assessment of slope stability results in abutments using limited equilibrium method and Swedge software under dynamic and static conditions shows that two wedges formed on the slopes of the abutment by the natural joints are potentially unstable. The rock wedge on the left abutment is smaller but presents higher sliding potential. In addition, there is no probability of planar failure due to the geological condition of the dam abutments. This paper summarizes the site investigation and subsequent analysis, which resulted in a recommendation not to construct this site. We offer some potential mitigation plans to consider if a dam were to be built at this site.     

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971–2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015–2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.