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1.
Human‐induced land use/land cover (LULC) changes are among the most important processes that shape the dynamics of the earth’s surface. This phenomenon, which is occurring at an astonishing rate, and its consequential environmental impacts have become an important area of research for scientists.Therefore, a wide range of methods and models have been developed to detect and predict these alterations, among which cellular automata (CA) models such as the CA‐Markov model, due to their affinity to geographic information system (GIS) and remote sensing (RS), are appropriate for detailed resolution modelling and simulating dynamic spatial processes. In Iran, the district of Ravansar has undergone severe LULC changes recently, thus to take the necessary precautions, decision‐makers need to predict and determine the extent of these changes. In this study, using spatial analysis methods the LULC changes in Ravansar were investigated from 1992 to 2015. Subsequently, the CA‐Markov model was applied to simulate the spatial pattern changes of LULC until 2030. Our results indicated that from 1992 to 2015, this region has witnessed a noticeable increase in the areas of the built‐up and agricultural lands (both aquatic and non‐aquatic), resulting in the decrease of the gardens, range, and bare lands. The simulated LULC map showed that this trend will continue due to more urbanization and development of agricultural areas.  相似文献   
2.
In this paper, a modeling procedure is carried out to numerically analyze the end bearing capacity of drilled shafts in sand. The Mohr–Coulomb elastic plastic constitutive law with stress dependent elastic parameters is used for all numerical analyses performed in this study. The numerical results are compared with the available experimental equations. It is seen that numerical results are in good agreement with experimental equations. The variation of the end bearing capacity of drilled shafts versus embedment depth is also studied. Numerical results show that with increase in pile embedment depth, the end bearing capacity increases. However, the rate of increase becomes smaller as the pile embedment depth increases. Also, numerical analyses show that, for equal settlement, the end bearing decreases with increase in the pile diameter. Finally, a sensitivity analysis is performed to obtain the separate effect of each sand parameter on the end bearing capacity of drilled shafts, and the parameters that are most influential are identified.  相似文献   
3.
The saltation regime is very important for understanding the sediment transport mechanism. However,there is no consensus on a model for the saltation regime. This study answers several questions raised with respect to the Eulerian-Lagrangian modeling of sediment transport. The first question is why the previous saltation models that use different combinations of hydrodynamic forces yielded acceptable results? The second question is which shear lift model(i.e. a shear lift expression and its coefficient) is more appropriate? Another important question is which hydrodynamic forces have greater contributions to the saltation characteristics of a sediment particle? The last question is what are the contributions of the turbulence fluctuations as well as effects of using two-and three-dimensional(2 D and 3 D) models on the simulation results? In order to fairly answer these questions, a systematic study was done by considering different scenarios. The current study is the first attempt to clearly discuss these issues. A comprehensive 3 D saltation model for non-cohesive sediment was developed that includes all the hydrodynamic forces acting on the particle. The random nature of sediment transport was included using turbulent flow and bed-particle collision models. The eddy interaction model was applied to generate a3 D turbulent flow field. Bed-particle collisions were considered using the concept of a contact zone and a corresponding contact point. The validation of the model was done using the available experimental data for a wide range of sediment size(0.03 to 4.8 cm). For the first question, the results indicated that some of the hydrodynamic effects show opposing trends and some have negligible effects. With these opposing effects it is possible to adjust the coefficients of different models to achieve acceptable agreement with the same experimental data while omitting some aspects of the physics of the process. A suitable model for the shear lift force was developed by linking the lift coefficient to the drag coefficient and the contributions of the hydrodynamic forces and turbulence fluctuations as well as the consequences of using of 2 D and 3 D models were studied. The results indicate that the shear lift force and turbulent flow fluctuations are important factors for the saltation of both sand and gravel, and they cannot be ignored.  相似文献   
4.
The complex stream bank profiles in alluvial channels and rivers that are formed after reaching equilibrium has been a popular topic of research for many geomorphologists and river engineers. The entropy theory has recently been successfully applied to this problem. However, the existing methods restrict the further application of the entropy parameter to determine the cross-section slope of the river banks. To solve this limitation, we introduce a novel approach in the extraction of the equation based on the calculation of the entropy parameter (λ) and the transverse slope of the bank profile at threshold channel conditions. The effects of different hydraulic and geometric parameters are evaluated on a variation of the entropy parameter. Sensitivity analysis on the parameters affecting the entropy parameter shows that the most effective parameter on the λ-slope multiplier is the maximum slope of the bank profile and the dimensionless lateral distance of the river banks.  相似文献   
5.
Due to the complicated nature of environmental processes, consideration of uncertainty is an important part of environmental modelling. In this paper, a new variant of the machine learning-based method for residual estimation and parametric model uncertainty is presented. This method is based on the UNEEC-P (UNcertainty Estimation based on local Errors and Clustering – Parameter) method, but instead of multilayer perceptron uses a “fuzzified” version of the general regression neural network (GRNN). Two hydrological models are chosen and the proposed method is used to evaluate their parametric uncertainty. The approach can be classified as a hybrid uncertainty estimation method, and is compared to the group method of data handling (GMDH) and ordinary kriging with linear external drift (OKLED) methods. It is shown that, in terms of inherent complexity, measured by Akaike information criterion (AIC), the proposed fuzzy GRNN method has advantages over other techniques, while its accuracy is comparable. Statistical metrics on verification datasets demonstrate the capability and appropriate efficiency of the proposed method to estimate the uncertainty of environmental models.  相似文献   
6.
7.
In the current research, the ground-penetrating radar (GPR) method has been employed to identify physical and geometrical parameters of buried cylindrical structures using the pattern recognition approach. To achieve this goal, the well-established mathematical relationships between geometrical parameters of cylindrical target (radius, burial depth, and horizontal location) and the associated GPR hyperbolic response characteristics are employed using the template matching method. In order to validate the applicability of the template matching method in providing estimates of such parameters, the method is first examined on GPR responses of synthetic models with known geometrical parameters followed by applying on real data using two different similarity criteria including 2-D spatial convolution and normalized cross correlation in the wave number domain. In the first step, the GPR responses of 71 synthetic models encompassing one, two, and three horizontal cylinders were produced using the improved 2-D finite difference in frequency domain. Then, appropriate preprocessing sequences to reduce random noise caused by forward modeling were applied on synthetic data. The proposed algorithm applied on several synthetic model responses could estimate the known geometrical parameters of the buried cylinders with acceptable accuracy (maximum error of 15%). The template matching algorithm was also used to extract geometrical parameters of water and wastewater pipes buried in Imam Hossein Square, Isfahan city, as real GPR data. Depending on environmental conditions and subsurface host formation, the real GPR data normally contain a variety of noises; therefore, a series of appropriate objective preprocessing and processing stages were designed in order to apply on real GPR images before deploying template matching algorithm. The applicability of the template matching algorithm on real data and validity of the estimated parameters were proved based on assessing the accuracy of the estimated geometrical parameters of respective pipes through GPR response versus the measured parameters. The proposed algorithm was designed in such a way that all steps of estimating geometrical parameters of buried cylindrical targets are automatically carried out.  相似文献   
8.
Ambient response measurements were made on an eighteen-storey building at three different stages of construction to detect any changes in the frequencies, mode shapes and stiffness with construction. The first nine frequencies and corresponding mode shapes for each stage of construction are found. A comparison is made among these mode shapes and frequencies and with the mode shapes and frequencies of an analytical model incorporating beams, columns, shear walls, panels and diagonal elements. The added effects, on frequencies and mode shapes, of non-structural elements such as stairs, elevators, claddings and partition walls are studied. Using Improved Statistical Structural Identification, an attempt is made to study the stiffening effect of non-structural elements by updating the stiffness matrix of the building.  相似文献   
9.
Soil temperature (T S) strongly influences a wide range of biotic and abiotic processes. As an alternative to direct measurement, indirect determination of T S from meteorological parameters has been the focus of attention of environmental researchers. The main purpose of this study was to estimate daily T S at six depths (5, 10, 20, 30, 50 and 100?cm) by using a multilayer perceptron (MLP) artificial neural network (ANN) model and a multivariate linear regression (MLR) method in an arid region of Iran. Mean daily meteorological parameters including air temperature (T a), solar radiation (R S), relative humidity (RH) and precipitation (P) were used as input data to the ANN and MLR models. The model results of the MLR model were compared to those of ANN. The accuracy of the predictions was evaluated by the correlation coefficient (r), the root mean-square error (RMSE) and the mean absolute error (MAE) between the measured and predicted T S values. The results showed that the ANN method forecasts were superior to the corresponding values obtained by the MLR model. The regression analysis indicated that T a, RH, R S and P were reasonably correlated with T S at various depths, but the most effective parameters influencing T S at different depths were T a and RH.  相似文献   
10.
Atmospheric modeling is considered an important tool with several applications such as prediction of air pollution levels, air quality management, and environmental impact assessment studies. Therefore, evaluation studies must be continuously made, in order to improve the accuracy and the approaches of the air quality models. In the present work, an attempt is made to examine the air pollution model (TAPM) efficiency in simulating the surface meteorology, as well as the SO2 concentrations in a mountainous complex terrain industrial area. Three configurations under different circumstances, firstly with default datasets, secondly with data assimilation, and thirdly with updated land use, ran in order to investigate the surface meteorology for a 3-year period (2009–2011) and one configuration applied to predict SO2 concentration levels for the year of 2011.The modeled hourly averaged meteorological and SO2 concentration values were statistically compared with those from five monitoring stations across the domain to evaluate the model’s performance. Statistical measures showed that the surface temperature and relative humidity are predicted well in all three simulations, with index of agreement (IOA) higher than 0.94 and 0.70 correspondingly, in all monitoring sites, while an overprediction of extreme low temperature values is noted, with mountain altitudes to have an important role. However, the results also showed that the model’s performance is related to the configuration regarding the wind. TAPM default dataset predicted better the wind variables in the center of the simulation than in the boundaries, while improvement in the boundary horizontal winds implied the performance of TAPM with updated land use. TAPM assimilation predicted the wind variables fairly good in the whole domain with IOA higher than 0.83 for the wind speed and higher than 0.85 for the horizontal wind components. Finally, the SO2 concentrations were assessed by the model with IOA varied from 0.37 to 0.57, mostly dependent on the grid/monitoring station of the simulated domain. The present study can be used, with relevant adaptations, as a user guideline for future conducting simulations in mountainous complex terrain.  相似文献   
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