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Natural Resources Research - Solar radiation data are crucial for the design and evaluation of solar energy systems, climatic studies, water resources management, estimating crop productivity, etc....  相似文献   
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This paper presents a novel triple‐layer model, called VART DO‐3L, for simulation of spatial variations in dissolved oxygen (DO) in fine‐grained streams, characterized by a fluid mud (fluff or flocculent) layer (an advection‐dominated storage zone) as the interface between overlying stream water and relatively consolidated streambed sediment (a diffusion‐dominated storage zone). A global sensitivity analysis is conducted to investigate the sensitivity of VART DO‐3L model input parameters. Results of the sensitivity analysis indicate that the most sensitive parameter is the relative size of the advection‐dominated storage zones (As/A), followed by a lumped reaction term (R) for the flocculent layer, biological reaction rate (μo) in diffusive layer and biochemical oxygen demand concentration (L) in water column. In order to address uncertainty in model input parameters, Monte Carlo simulations are performed to sample parameter values and to produce various parameter combinations or cases. The VART DO‐3L model is applied to the Lower Amite River in Louisiana, USA, to simulate vertical and longitudinal variations in DO under the cases. In terms of longitudinal variation, the DO level decreases from 7.9 mg l at the Denham Springs station to about 2.89 mg l?1 at the Port Vincent station. In terms of vertical variation, the DO level drops rapidly from the overlying water column to the advection‐dominated storage zone and further to the diffusive layer. The DO level (CF) in the advective layer (flocculent layer) can reach as high as 40% of DO concentration (C) in the water column. The VART DO‐3L model may be applied to similar rivers for simulation of spatial variations in DO level. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   
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In this study subsidence due to groundwater withdrawal was investigated. Kerman Province in Iran is struggling with land subsidence problem due to extensive groundwater withdrawal mainly for farming. The rate and type of groundwater withdrawal has very important impact on settlement rate. In this research, effective parameters on land subsidence caused by groundwater withdrawal were determined by laboratory tests. Sampling had done up to depth of 300 m mainly with remolded specimens from Shams-abad, Nouq plain in Kerman province. Similar to the field preconsolidation pressure was applied on specimens in the laboratory. Rate of applied stress on prepared specimens was similar to effect of oscillation of groundwater level. In order to model the actual soil behavior in the laboratory, one-dimensional consolidation device (odometer) was adopted for testing. In these tests, the effect of loading caused by seasonal oscillation of groundwater table is considered by means of cyclic loading in the testing which has great effect on rate of settlements. The results of tests show that when the water table level periodically increases and decreases the amount of settlement decrease, comparing with the case when the groundwater table drop to a constant level. In order to predict the further effects of groundwater level oscillation and actual field condition on land subsidence, a finite element model based on Biots’ three-dimensional consolidation theory was developed. After calibration of finite element model with laboratory tests, this model was used for prediction the effect of groundwater level oscillation on actual field conditions.  相似文献   
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Soil is a material which is weak in tension; however, different materials such as geotextiles are used to address this inadequacy. In recent years more than one million square metres of geotextiles were used for reinforcing soil. Nevertheless, there are several significant problems associated with geotextiles, such as creep, low modulus of elasticity and susceptibility to aggressive environments. Carbon fibre reinforced polymer (CFRP) was introduced over two decades ago to the field of structural engineering and it can also be used in geotechnical engineering. CFRP has all the benefits associated with geotextiles and it boasts a higher strength, higher modulus, no creep and reliability in aggressive environments. In this investigation, the interface properties of CFRP-sand and fine sand were investigated using the pull-out test. The pull-out test device was designed and assembled using a triaxial loading device and a direct shear device. In the pull-out test, the normal force applied by the triaxial loading and pull-out force is applied by a direct shear device. CFRP samples were prepared in the lab. Precast and cast-in-place samples were tested. The pull-out force and corresponding displacements of each of the materials were recorded and compared.  相似文献   
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Nowadays, the world is witnessing the ever increasing need of Tunnel excavation due to their unique features and the kind of human applied plans. This has led to increase in demand of excavating this engineering factor. Tunnel excavation process faces a lot of challenges due to environmental and technological complexities which causes the economic evaluation and investigation of this project to be difficult. It is tried to develop the proposed model with regard to efficiency concept in order to evaluate and investigate the efficiency of relative economic performance of Tunnel excavation projects and turn to its modeling and implementing by data envelopment analysis and Fuzzy DEMATEL techniques. The results in Iran showed that the proposed model can turn to investigation and evaluation of economic efficiency of Tunnel excavation by considering two optimistic (ideal) and pessimistic perspectives such that the Tunnel excavation process of “Karaj water transition” and “Cheshmelangan water transition” among 12 rock Tunnel excavation projects of Iran in the time period of 1998–2013 were respectively introduced as the most efficient and the most inefficient rock Tunnel excavation projects.  相似文献   
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This paper evaluates the feasibility of using an artificial neural network (ANN) methodology for estimating the groundwater levels in some piezometers placed in an aquifer in north‐western Iran. This aquifer is multilayer and has a high groundwater level in urban areas. Spatiotemporal groundwater level simulation in a multilayer aquifer is regarded as difficult in hydrogeology due to the complexity of the different aquifer materials. In the present research the performance of different neural networks for groundwater level forecasting is examined in order to identify an optimal ANN architecture that can simulate the piezometers water levels. Six different types of network architectures and training algorithms are investigated and compared in terms of model prediction efficiency and accuracy. The results of different experiments show that accurate predictions can be achieved with a standard feedforward neural network trained usung the Levenberg–Marquardt algorithm. The structure and spatial regressions of the ANN parameters (weights and biases) are then used for spatiotemporal model presentation. The efficiency of the spatio‐temporal ANN (STANN) model is compared with two hybrid neural‐geostatistics (NG) and multivariate time series‐geostatistics (TSG) models. It is found in this study that the ANNs provide the most accurate predictions in comparison with the other models. Based on the nonlinear intrinsic ANN approach, the developed STANN model gives acceptable results for the Tabriz multilayer aquifer. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   
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