On Inflow to a Tunnel in a Fractured Double-Porosity Aquifer

Inflow to a tunnel is a great public concern and is closely related to groundwater hydrology, geotechnical engineering, and mining engineering, among other disciplines. Rapid computation of inflow to a tunnel provides a timely means for quickly assessing the inflow discharge, thus is critical for safe operation of tunnels. Dewatering of tunnels is another engineering practice that should be planned. In this study, an analytical solution of the inflow to a tunnel in a fractured unconfined aquifer is obtained. The solution takes into account either the spherical or slab-shaped matrix block and the unsteady state interporosity flow. The instantaneous drainage water table and anisotropic hydraulic conductivities of the fractures network are also considered. Both uniform flux and uniform head boundary condition are considered to simulate the constant head boundary condition in the tunnel. The effects of the hydraulic parameters of the fractured aquifer on the inflow variation of the tunnel are explored. The application of the presented solution to obtain the optimum location and discharge of the well to minimize the inflow to a tunnel is illustrated.     

CHDS: conflict handling in direct sampling for stochastic simulation of spatial variables

Stochastic Environmental Research and Risk Assessment - In recent years, multiple-point geostatistical (MPS) approaches have gained significant popularity for modeling subsurface heterogeneity in...     

Location of Areas Prone to Flood Spreading Using GIS (Ilam Province,Iran)

Water Resources - The present study aimed to locate the areas prone to flood spreading in order to manage surface water resources. Therefore, the information layers of slope, land capability,...     

Context-aware abstraction and generalization of street networks: two cognitively engineered user-oriented approaches using network Voronoi diagrams

Generalization and spatial contextual awareness are prevalent concepts in geographic information systems. This study adopted a context-dependent user-centred network generalization method to create a sub-network for optimal route finding. The results show an increase in the number of preferred traversed edges. A route presentation approach is suggested that is based on cognitively engineered user-oriented abstraction of street network. Successive abstractions hierarchize the street network to create a hierarchical presentation structure. The route is projected onto one level in the structure. Then, instead of showing the exact route, the network Voronoi regions represented by the projected route are shown. Experience indicates that the suggested method is an efficient way of route presentation for a hierarchical regionalized structure of a human cognitive map.     

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and <Emphasis Type="Italic">t</Emphasis>-distributed deviations

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student’s) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.     

Identification and delineation of saline soils using aerial photographs in Yamuna Alluvial plain,Haryana

Salinity is creating great problems in the Yamuna Alluvial Plain. State Government is taking steps for reclaiming these lands to increase agricultural production. Impeded drainage, excess canal irrigation, topography parent material, shallow depth and bad quality of ground water are the main factors which are responsible for the genesis of saline soils in the alluvial plains of Haryana. On the arial photographs tonal differences on account of salt concentration in the soil are clearly seen. These differences are aslo associated with physiography and soil conditions which can be easily delineated. The information thus; collected can be used for reclamation of saline soils.     

Equatorial radius of the Earth: A dynamical determination

An intrresting variation on the familiar method of determining the earth's equatorial radius a_e, from a knowledge of the earth's equatorial gravity is suggested. The value of equatorial radius thus found is 6378,142±5 meters. The associated parameters are GM=3.986005±.000004 × 10²⁰ cm³ sec-⁻² which excludes the relative mass of atmosphere ≅10⁻⁶ ξ GM, the equatorial gravity γ_e 978,030.9 milligals (constrained in this solution by the Potsdam Correction of 13.67 milligals as the Potsdam Correction is more directly, orless indirectly, measurable than the equatorial gravity) and an ellipsoidal flattening of f=1/298.255.     

A novel spatial index using spatial analyses and hierarchical fuzzy expert system for obtaining green TOD: a case study in Tehran city

Sustainable development is a vital and challenging factor for managing urban growth smartly. This factor contains three main components, namely economic growth, ecological protection and social justice. Green Transit-Oriented Development (GTOD) is a consummate planning approach in line with those components. Implementation of GTOD in an urban area is underpinned by its quantification. Therefore, a quantitative spatial index based on several indicators related to TOD and Green urbanism concepts should be developed. In this study, Geo-spatial Information Science and hierarchical fuzzy inference system (HFIS) were employed to calculate the indicators and aggregate them, respectively. In order to showcase the feasibility of the proposed method, it was implemented in a case study area in the City of Tehran, Iran. The result of this method is an integrated spatial GTOD index, which measures the neighbourhoods’ GTOD levels. These measurements specify weaknesses and strengths of neighbourhoods’ factors. Therefore, this index helps decision-makers to plan neighbourhoods based on land use and public transit views. Additionally, the HFIS method helps decision-makers to consider criteria and indicators with their inherent uncertainties and aggregate them with much fewer rules. For evaluating the results, the developed GTOD index was assessed with municipal action planning and attraction maps. According to the outcomes of the assessment, it is concluded that the proposed method is adequately robust and efficient for smart and sustainable urban planning.     

Predicting groundwater level of wells in the Diyala River Basin in eastern Iraq using artificial neural network

Al-Mansourieh zone is a part of Al-Khalis City within the province of Diyala and located in the Diyala River Basin in eastern Iraq with a total area about 830 km2.Groundwater is the main water source for agriculture in this zone.Random well drilling without geological and hydraulic information has led the most of these wells to dry up quickly.Therefore,it is necessary to estimate the levels of groundwater in wells through observed data.In this study,Alyuda NeroIntelligance 2.1 software was applied to predict the groundwater levels in 244 wells using sets of measured data.These data included the coordinates of wells(x,y),elevations,well depth,discharge and groundwater levels.Three ANN structures(5-3-3-1,5-10-10-1 and 5-11-11-1)were used to predict the groundwater levels and to acquire the best matching between the measured and ANN predicted values.The coefficient of correlation,coefficient determination(R2)and sum-square error(SSE)were used to evaluate the performance of the ANN models.According to the ANN results,the model with the three structures has a good predictability and proves more effective for determining groundwater level in wells.The best predictor was achieved in the structure 5-3-3-1,with R2 about 0.92,0.89,0.84 and 0.91 in training,validation,testing and all processes respectively.The minimum average error in the best predictor is achieved in validation and testing processes at about 0.130 and 0.171 respectively.On the other hand,the results indicated that the model has the potential to determine the appropriate places for drilling the wells to obtain the highest level of groundwater.     

Early Cretaceous sedimentary provenance and structural evolution of the central Sanandaj–Sirjan Zone,Iran: implications for palaeogeographic reconstructions of the northern Neo-Tethyan margin

ABSTRACT

The Early Cretaceous was an important epoch in the evolution of the Earth system in which major tectonic episodes occurred, especially along the Alpine–Himalayan belt. The paucity of reliable palaeogeographic data from the central segment of this geological puzzle, however, hampers the reconstruction of a panoramic view of its Early Cretaceous palaeogeography and geodynamic setting. Here we present multidisciplinary provenance data from Lower Cretaceous strata of the overriding plate of the Neo-Tethyan subduction zone (the Sanandaj–Sirjan Zone; SSZ, of central Iran), including structural, basin-fill evolution, petrographic and geochemical analyses. Sandstone provenance analysis of Lower Cretaceous red beds suggests the occurrence of sub-mature litho-quartzose sandstones attributed to an active continental arc margin in convergent setting predominantly derived from plutonic, quartzose sedimentary and metamorphic rocks exposed in the central SSZ. Weathering indices indicate moderate chemical weathering in the source area which may be related to close source-to-sink relationships or arid climate. Our palaeogeographic reconstructions and original geological mapping indicate that the erosion of uplifted basement rocks exposed in horst blocks provided the sediment sources for the syn-extensional deposition of uppermost Jurassic–lowermost Cretaceous conglomerates and Lower Cretaceous siliciclastic red beds within a continental retro-arc basin during initiation of the ‘Neo-Tethys 2?. The polyphase tectonic reactivation along the principal fault of the study area controlled the syn- and post-extensional tectonostratigraphic evolution that reflect the corresponding mechanical decoupling/coupling along the northern Neo-Tethyan plate margin.