Sedimentology,mineralogy, and geochemistry of the Late Quaternary Meyghan Playa sediments,NE Arak,Iran: palaeoclimate implications     

Leila Abdi  Hossain Rahimpour-Bonab  Mohsen Mirmohammad-Makki  Johann Probst  Saeed Rezaeian Langeroudi 《Arabian Journal of Geosciences》2018,11(19):589

Playas are shallow ephemeral lakes that form in arid and semi-arid regions. Iran has a large number of playas such as Meyghan Playa, which is located in the northeast of Arak city that borders the central Iran and Sanandaj-Sirjan zones. This study aims to investigate the mineralogical, sedimentological, and geochemical characteristics of the playa sediments. In order to determine the palaeoenvironment, we carried out X-ray diffraction (XRD), X-ray fluorescence (XRF), and scanning electron microscopy (SEM) studies. Meyghan Playa sediments consist of very fine-grained sediments and contain both evaporite and clastic minerals. The evaporite minerals include calcite, gypsum, halite, glauberite, and thenardite, whereas clastic minerals are quartz and clay. The calcite abundance decreases from the margin to the central portion of the playa but gypsum and halite abundances show an increasing trend from the margin to the center. This observation is consistent with the general zonation of other playas. Variations of calcite and gypsum concentration profiles present increasing and decreasing trends with depth, which could be ascribed to the changes in climatic factors. These factors include brine chemical modifications owing to changes in evaporation and precipitation rates and variations in relative abundance of anions-cations or in the rate of clastic and evaporite minerals due to variations in the freshwater influx (climatic changes) with time. A decrease in calcite and increase in sulfate minerals (especially gypsum) with depth is probably due to the higher water level and rainfall, a more humid climate, and salinity variations.  相似文献   

Prediction of river flow using hybrid neuro-fuzzy models     

Armin Azad  Saeed Farzin  Hamed Kashi  Hadi Sanikhani  Hojat Karami  Ozgur Kisi 《Arabian Journal of Geosciences》2018,11(22):718

The complex nature of hydrological phenomena, like rainfall and river flow, causes some limitations for some admired soft computing models in order to predict the phenomenon. Evolutionary algorithms (EA) are novel methods that used to cover the weaknesses of the classic training algorithms, such as trapping in local optima, poor performance in networks with large parameters, over-fitting, and etc. In this study, some evolutionary algorithms, including genetic algorithm (GA), ant colony optimization for continuous domain (ACO_R), and particle swarm optimization (PSO), have been used to train adaptive neuro-fuzzy inference system (ANFIS) in order to predict river flow. For this purpose, classic and hybrid ANFIS models were trained using river flow data obtained from upstream stations to predict 1-, 3-, 5-, and 7-day ahead river flow of downstream station. The best inputs were selected using correlation coefficient and a sensitivity analysis test (cosine amplitude). The results showed that PSO improved the performance of classic ANFIS in all the periods such that the averages of coefficient of determination, R², root mean square error, RMSE (m³/s), mean absolute relative error, MARE, and Nash-Sutcliffe efficiency coefficient (NSE) were improved up to 0.19, 0.30, 43.8, and 0.13%, respectively. Classic ANFIS was only capable to predict river flow in 1-day ahead while EA improved this ability to 5-day ahead. Cosine amplitude method was recognized as an appropriate sensitivity analysis method in order to select the best inputs.  相似文献   

Spatial assessment of the potential of groundwater quality using fuzzy AHP in GIS     

Saeed Azimi  Mehdi Azhdary Moghaddam  Seyed Arman Hashemi Monfared 《Arabian Journal of Geosciences》2018,11(7):142

In this study, fuzzy AHP method is used for extracting the water quality indicators based on the Schuler standard and World Health Organization (WHO) guidelines during a 20-year period. For this purpose, the best fit of the zoning model was performed. Furthermore, by comparing the standard errors, the continuous Raster layer was extracted from the important parameters used in generating the qualitative potential assessment index. The classified layer was generated by integrating continuous layers in the GIS environment and with the use of Python programming. The similarity of the outputs of both methods indicates the presence of large sections of aquifers in the middle and southwestern regions of Iran in the “temporarily drinkable” and “bad” classes. The calculations showed that the majority of aquifers that were located in the “inappropriate” class during the first 10 years fell to less valuable class types. Based on the results of the model, there is a direct correlation between the drop in water resources and the decline in the quality indices. In addition, in the Urmia and Bushehr coastal aquifers, due to excessive water withdrawal and salty water penetration, the quality of the table water is in critical condition. Based on the results of the research, the aquifers in the range of Zagros and Alborz mountains show the least change in water quality. The reason for this is the depth of the aquifer and the ability to recharge it.  相似文献   

Seismic interaction of underground RC ducts and neighboring bridge piers in liquefiable soil foundation     

Saeed Moshirabadi  Masoud Soltani  Koichi Maekawa 《Acta Geotechnica》2015,10(6):761-780

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Role of land surface parameter change in dust emission and impacts of dust on climate in Southwest Asia     

Darvishi Boloorani  Ali  Najafi  Mohammad Saeed  Mirzaie  Saham 《Natural Hazards》2021,109(1):111-132

Natural Hazards - Spatial–temporal changes of land surface parameters (land cover change, net primary production, and vegetation phenology) affect the characteristics of atmospheric dust....  相似文献   

Classification of rocks radionuclide data using machine learning techniques     

Abdul Razzaq Khan  Adil Aslam Mir  Sharjil Saeed  Muhammad Rafique  Khawaja M. Asim  Talat Iqbal  Abdul Jabbar  Saeed Ur Rahman 《Acta Geophysica》2018,66(5):1073-1079

The aim of this study is to assess the performance of linear discriminate analysis, support vector machines (SVMs) with linear and radial basis, classification and regression trees and random forest (RF) in the classification of radionuclide data obtained from three different types of rocks. Radionuclide data were obtained for metamorphic, sedimentary and igneous rocks using gamma spectroscopic method. A P-type high-purity germanium detector was used for the radiometric study. For analysis purpose, we have determined activity concentrations of ²³²Th, ²²⁶Ra and ⁴⁰K radionuclides, published elsewhere (Rafique et al. in Russ Geol Geophys 55:1073–1082, 2014), in different rock samples and built the classification model after pre-processing the data using three times tenfold cross-validation. Using this model, we have classified the new samples into known categories of sedimentary, igneous and metamorphic. The statistics depicts that RF and SVM with radial kernel outperform as compared to other classification methods in terms of error rate, area under the curve and with respect to other performance measures.  相似文献   

Review Paper: Methods of measurement for 4D seismic post-stack time shifts     

Colin MacBeth  Hamed Amini  Saeed Izadian 《Geophysical Prospecting》2020,68(9):2637-2664

The estimation of time-lapse time shifts between two, or several, repeated seismic surveys has become increasingly popular over the past eighteen years. These time shifts are a reliable and informative seismic attribute that can relate to reservoir production. Correction for these time shifts or the underlying velocity perturbations and/or subsurface displacement in an imaging sense also permits accurate evaluation of time-lapse amplitudes by attempting to decouple the kinematic component. To date, there are approximately thirty methods for time-shift estimation described in the literature. We can group these methods into three main families of mathematical development, together with several miscellaneous techniques. Here we detail the underlying bases for these methods, and the acknowledged benefits and weaknesses of each class of method highlighted. We illustrate this review with a number of time-lapse seismic examples from producing fields. No method is necessarily superior to the others, as its selection depends on ease of implementation, noise characteristics of the field data, and whether the inherent assumptions suit the case in question. However, cross-correlation stands out as the algorithm of choice based on the Pareto principle and waveform inversion the algorithm delivering best resolution. This is a companion study to the previous review of time-shift magnitudes and a discussion of their rock physics basis.  相似文献   

NF-GMDH-Based self-organized systems to predict bridge pier scour depth under debris flow effects     

Mohammad Najafzadeh  Farid Saberi-Movahed  Saeed Sarkamaryan 《Marine Georesources & Geotechnology》2018,36(5):589-602

Existence of debris structures inevitably ascends the rate of scour process around bridge piers and flow area not only lead into remarkable deviation of flow but also increase the velocity around bridge piers. A myriad of experimental and field studies to understand effective parameters on the scour depth with debris effects were conducted. To reach permissible values of the scour depth for the practical uses, relationships extracted in previous investigations suffer from lack of generalization for experimental data ranges. In this way, neuro-fuzzy group method of data handling (NF-GMDH)-based self-organized models is applied to evaluate the pier scour depth. In this study, NF-GMDH network is implemented using evolutionary algorithms listed particle swarm optimization (PSO), gravitational search algorithm (GSA), and genetic algorithm (GA). In all, 243 experimental datasets including a wide range of input and output parameters to develop the proposed models were compiled from various literature. The efficiency of NF-GMDH networks for training and testing stages was perused. NF-GMDH-PSO model provided the scour depth with more precise predictions (root mean squared error (RMSE)?=?0.388 and scatter index (SI)?=?0.343) in comparison with NF-GMDH-GA (RMSE?=?0.402 and SI?=?0.361) and NF-GMDH-GSA (RMSE?=?0.456 and SI?=?0.407) networks. In addition, blockage ratio (ΔA) was taken into account as the most sumptuous parameter with utmost level of effectiveness using the sensitivity analysis.  相似文献   

Bedload Sediment Rate Prediction for the Sand Transport Along Coastal Waters in Ocean Management Strategy     

Khorram  Saeed 《中国海洋工程》2020,34(6):840-852

China Ocean Engineering - Interactions among different landforms and varied complicated physical processes cause sediment transport in coastal regions being the interest of ocean management...  相似文献   

Active Control of A Piston-Type Absorbing Wavemaker with Fully Reflective Structure     

Mahjouri  Saeed  Shabani  Rasoul  Rezazadeh  Ghader  Badiei  Peyman 《中国海洋工程》2020,34(5):730-737

China Ocean Engineering - Multiple reflections of the waves between structure and wavemaker in hydraulic flumes could change the frequency content of the desired incident wave or result in...  相似文献