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Monitoring of the fluctuations of groundwater storage is particularly important in arid and semi-arid regions where water scarcity brings about various challenges. Remote sensing data and techniques play a preponderant role in developing solutions to environmental problems. The launch of Gravity Recovery and Climate Experiment (GRACE) satellites has eased the remote monitoring and evaluation of groundwater resources with an unprecedented precision over large scales. Within the scope of the current study, the latest release (RL06) of GRACE mass concentrations (Mascons) from Jet Propulsion Laboratory (JPL) dataset as well as Global Land Data Assimilation System (GLDAS) models of Noah and Catchment Land Surface Model (CLSM) were used to provide Groundwater Storage Anomalies (GWSA) over Turkey. The temporal interactions of the estimated GWSA with the climatic variables of precipitation and temperature (derived from the reanalysis datasets of CHELSA [Climatologies at High resolution for the Earth's Land Surface Areas] and FLDAS [the Famine Early Warning Systems Network Land Data Assimilation System], respectively) were investigated statistically. The results suggest that there is a descending trend (from 2003 to 2016) for Terrestrial Water Storage Anomalies (TWSA) and GWSA over Turkey with a total loss of 11 and 6 cm of water, respectively. The statistical analysis results also indicate that the monthly variations of GWSA over Turkey are highly correlated with precipitation and temperature at 2-month lag. The analysis of the climatology (long-term) values of monthly GWSA, precipitation and temperature also revealed high agreement between the variables. 相似文献
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Behnam Ghorbani Ehsan Sadrossadat Jafar Bolouri Bazaz Parisa Rahimzadeh Oskooei 《Geotechnical and Geological Engineering》2018,36(4):2057-2076
This study explores the potential of adaptive neuro-fuzzy inference systems (ANFIS) for prediction of the ultimate axial load bearing capacity of piles (Pu) using cone penetration test (CPT) data. In this regard, a reliable previously published database composed of 108 datasets was selected to develop ANFIS models. The collected database contains information regarding pile geometry, material, installation, full-scale static pile load test and CPT results for each sample. Reviewing the literature, several common and uncommon variables have been considered for direct or indirect estimation of Pu based on static pile load test, cone penetration test data or other in situ or laboratory testing methods. In present study, the pile shaft and tip area, the average cone tip resistance along the embedded length of the pile, the average cone tip resistance over influence zone and the average sleeve friction along the embedded length of the pile which are obtained from CPT data are considered as independent input variables where the output variable is Pu for the ANFIS model development. Besides, a notable criticism about ANFIS as a prediction tool is that it does not provide practical prediction equations. To tackle this issue, the obtained optimal ANFIS model is represented as a tractable equation which can be used via spread sheet software or hand calculations to provide precise predictions of Pu with the calculated correlation coefficient of 0.96 between predicted and experimental values for all of the data in this study. Considering several criteria, it is represented that the proposed model is able to estimate the output with a high degree of accuracy as compared to those results obtained by some direct CPT-based methods in the literature. Furthermore, in order to assess the capability of the proposed model from geotechnical engineering viewpoints, sensitivity and parametric analyses are done. 相似文献
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Oilfield development involves several key decisions, including the number, type (injection/production), location, drilling schedule, and operating control trajectories of the wells. Without considering the coupling between these decision variables, any optimization problem formulation is bound to find suboptimal solutions. This paper presents a unified formulation for oilfield development optimization that seeks to simultaneously optimize these decision variables. We show that the source/sink term of the governing multiphase flow equations includes all the above decision variables. This insight leads to a novel and unified formulation of the field development optimization problem that considers the source/sink term in reservoir simulation equations as optimization decision variables. Therefore, a single optimization problem is formulated to simultaneously search for optimal decision variables by determining the complete dynamic form of the source/sink terms. The optimization objective function is the project net present value (NPV), which involves discounted revenue from oil production, operating costs (e.g. water injection and recycling), and capital costs (e.g., cost of drilling wells). A major difficulty after formulating the generalized field development optimization problem is finding an efficient solution approach. Since the total number of cells in a reservoir model far exceeds the number of cells that are intersected by wells, the source/sink terms tend to be sparse. In fact, the drilling cost in the NPV objective function serves as a sparsity-promoting penalty to minimize the number of wells while maximizing the NPV. Inspired by this insight, we solve the optimization problem using an efficient gradient-based method based on recent algorithmic developments in sparse reconstruction literature. The gradients of the NPV function with respect to the source/sink terms is readily computed using well-established adjoint methods. Numerical experiments are presented to evaluate the feasibility and performance of the generalized field development formulation for simultaneous optimization of the number, location, type, controls, and drilling schedule of the wells. 相似文献
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Nitrate contamination in irrigation groundwater,Isfahan, Iran 总被引：1，自引：1，他引：0
Groundwater is one of the major sources of water in Isfahan. Efficient management of these resources requires a good understanding of its status. This paper focuses on the hydrochemistry and also it wants to assess the nitrate concentration in irrigation groundwater of Isfahan suburb. All the groundwater samples are grouped into three categories, including Na-Cl + Ca-Cl (63 %), Na-SO4 + Ca-SO4 (23 %) and Ca-HCO3 (14 %). According to the EC and SAR, the most dominant classes are C3S1, C4S2 and C4S3. 55 % of samples indicate very high salinity and medium to very high alkalinity that is not suitable for irrigation. 84 % of the groundwater samples show nitrate contents higher than HAV (13 mg l?), while more than 25 % exceeded the maximum contamination level (44.27 mg l?) according to EPA regulations. The horizontal and vertical distribution patterns of nitrate in groundwater samples show a surficial origin for nitrate contamination. The high nitrate content can be attributed to the agricultural activities along with domestic sewage and industrial wastewaters in populated area. Based on results, using high nitrate groundwater for irrigation can minimize the requirement for inorganic fertilizers and reduce the cost of cultivation and nitrate contamination. 相似文献
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Bahram Saeidian Abbas Rajabifard Behnam Atazadeh Mohsen Kalantari 《Transactions in GIS》2023,27(6):1724-1747
In underground environments, survey elements such as survey points and observations provide the information required to define legal boundaries. These elements are also used to connect underground legal spaces to a geodetic survey network. Due to the issues of current 2D approaches for managing underground cadastral data, prominent 3D data models have been extended to support underground land administration. However, previous studies mostly focused on defining underground legal spaces and boundaries, with less emphasis on survey elements. This research aims to extend CityGML to support underground cadastral survey data. The proposed extension is based on the survey elements elicited from underground cadastral plans, which is then implemented for an underground case study area in Melbourne, Australia. This extension integrates underground survey data with legal and physical data in a 3D digital environment and provides an improved representation of survey elements, facilitating the management and communication of underground cadastral survey data. 相似文献
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Geochemical aspects of molybdenum and precious metals distribution in the Sar Cheshmeh porphyry copper deposit, Iran 总被引：1，自引：0，他引：1
Constraints on hypogene distribution of Mo and precious metals (Au and Ag) in the Sar Cheshmeh porphyry copper deposit indicated that much of the metals tend to be concentrated within the Cu-rich potassic core as well as with strongly phyllic alteration. The gradual increase in metal concentrations from weak potassic alteration to strong potassic and phyllic alteration zones is observed that could be related to cumulative effects of the early to the late stages of alteration and mineralization which is increased vein density and metal deposition. Comparison between inter-element relationships in hypogene ore types indicated that precious metals and Cu positively correlate over a wide range of values, indicating a spatial and temporal association of precious metals with Cu sulfides. In contrast, the sympathetic relationship of Mo with Cu and precious metals is only present in low-grade ores which are deposited in weak potassic alteration zone. This suggests contemporaneous deposition of minor Mo with Cu and precious metals during the early stage of mineralization. In the transitional stages of mineralization, significant portion of Mo deposition occurred independent of Cu and precious metals which is supported by negative correlation between Mo and Cu (also with precious metals) in silicified ores. In the late stage of mineralization, where the highest values of the metals had occurred with sericitization, differences in the distribution of the metals and inter-element relationships are significant that could be attributed to the heterogeneous distribution of Mo, Cu, and precious metals during the evolution of the porphyry system. The hypogene metal arrangement indicated that ores with the highest values of Cu and precious metals are not essentially enriched in Mo. 相似文献
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Behnam V. Damirchi Marcelo R. Carvalho Luís A. G. Bitencourt Osvaldo L. Manzoli Daniel Dias‐da‐Costa 《国际地质力学数值与分析法杂志》2021,45(1):83-107
A new discrete fracture model is introduced to simulate the steady‐state fluid flow in discontinuous porous media. The formulation uses a multi‐layered approach to capture the effect of both longitudinal and transverse permeability of the discontinuities in the pressure distribution. The formulation allows the independent discretisation of mesh and discontinuities, which do not need to conform. Given that the formulation is developed at the element level, no additional degrees of freedom or special integration procedures are required for coupling the non‐conforming meshes. The proposed model is shown to be reliable regardless of the permeability of the discontinuity being higher or lower than the surrounding domain. Four numerical examples of increasing complexity are solved to demonstrate the efficiency and accuracy of the new technique when compared with results available in the literature. Results show that the proposed method can simulate the fluid pressure distribution in fractured porous media. Furthermore, a sensitivity analysis demonstrated the stability regarding the condition number for wide range values of the coupling parameter. 相似文献
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Mohammadali Tarrahi Siavash Hakim Elahi Behnam Jafarpour 《Computational Geosciences》2016,20(5):929-952
Ensemble methods present a practical framework for parameter estimation, performance prediction, and uncertainty quantification in subsurface flow and transport modeling. In particular, the ensemble Kalman filter (EnKF) has received significant attention for its promising performance in calibrating heterogeneous subsurface flow models. Since an ensemble of model realizations is used to compute the statistical moments needed to perform the EnKF updates, large ensemble sizes are needed to provide accurate updates and uncertainty assessment. However, for realistic problems that involve large-scale models with computationally demanding flow simulation runs, the EnKF implementation is limited to small-sized ensembles. As a result, spurious numerical correlations can develop and lead to inaccurate EnKF updates, which tend to underestimate or even eliminate the ensemble spread. Ad hoc practical remedies, such as localization, local analysis, and covariance inflation schemes, have been developed and applied to reduce the effect of sampling errors due to small ensemble sizes. In this paper, a fast linear approximate forecast method is proposed as an alternative approach to enable the use of large ensemble sizes in operational settings to obtain more improved sample statistics and EnKF updates. The proposed method first clusters a large number of initial geologic model realizations into a small number of groups. A representative member from each group is used to run a full forward flow simulation. The flow predictions for the remaining realizations in each group are approximated by a linearization around the full simulation results of the representative model (centroid) of the respective cluster. The linearization can be performed using either adjoint-based or ensemble-based gradients. Results from several numerical experiments with two-phase and three-phase flow systems in this paper suggest that the proposed method can be applied to improve the EnKF performance in large-scale problems where the number of full simulation is constrained. 相似文献