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This work presents the first attempt to develop unconditionally stable, implicit finite difference solutions of one-sided spatial fractional advection-dispersion equation (s-FADE) by imposing the nonzero Dirichlet boundary condition (ND BC) or the nonzero fractional Robin boundary condition (NFR BC) at inlet boundary and the zero fractional Neumann boundary condition (ZFN BC) at outlet boundary. The results of the numerical studies performed using artificial solute transport parameters demonstrated that the numerical solution with the NFR BC as the inlet boundary produced much more realistic concentration values. The numerical solution with the NFR BC at the inlet boundary was capable of correctly describing the Fickian and non-Fickian behaviors of the solute transport at different α values, and it had the relatively same accuracy at different numbers of the spatial nodes. Also, the practical application of the numerical solution with the NFR BC as the inlet boundary was investigated by conducting tracer experiments in homogeneous and heterogeneous soil columns. According to the obtained results, this numerical solution described well solute transport in the homogenous and heterogeneous soils. The α values of the homogeneous and heterogeneous soils were obtained in the ranges of 1.849–1.999 and 1.248–1.570, respectively, which were in excellent agreement with the physical properties of the soils. In a nutshell, the numerical solution of the s-FADE with the NFR BC as the inlet boundary can be successfully applied to describe the solute transport in the homogeneous and heterogeneous soils with bounded spatial domains. 相似文献
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Mousa Abedini Bahareh Ghasemian Ataollah Shirzadi Himan Shahabi Kamran Chapi Binh Thai Pham 《国际地球制图》2013,28(13):1427-1457
AbstractA novel artificial intelligence approach of Bayesian Logistic Regression (BLR) and its ensembles [Random Subspace (RS), Adaboost (AB), Multiboost (MB) and Bagging] was introduced for landslide susceptibility mapping in a part of Kamyaran city in Kurdistan Province, Iran. A spatial database was generated which includes a total of 60 landslide locations and a set of conditioning factors tested by the Information Gain Ratio technique. Performance of these models was evaluated using the area under the ROC curve (AUROC) and statistical index-based methods. Results showed that the hybrid ensemble models could significantly improve the performance of the base classifier of BLR (AUROC?=?0.930). However, RS model (AUROC?=?0.975) had the highest performance in comparison to other landslide ensemble models, followed by Bagging (AUROC?=?0.972), MB (AUROC?=?0.970) and AB (AUROC?=?0.957) models, respectively. 相似文献
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Climate change impact on wave energy in the Persian Gulf 总被引：1，自引：0，他引：1
Bahareh Kamranzad Amir Etemad-Shahidi Vahid Chegini Abbas Yeganeh-Bakhtiary 《Ocean Dynamics》2015,65(6):777-794
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This study presents single‐objective and multi‐objective particle swarm optimization (PSO) algorithms for automatic calibration of Hydrologic Engineering Center‐ Hydrologic Modeling Systems rainfall‐runoff model of Tamar Sub‐basin of Gorganroud River Basin in north of Iran. Three flood events were used for calibration and one for verification. Four performance criteria (objective functions) were considered in multi‐objective calibration where different combinations of objective functions were examined. For comparison purposes, a fuzzy set‐based approach was used to determine the best compromise solutions from the Pareto fronts obtained by multi‐objective PSO. The candidate parameter sets determined from different single‐objective and multi‐objective calibration scenarios were tested against the fourth event in the verification stage, where the initial abstraction parameters were recalibrated. A step‐by‐step screening procedure was used in this stage while evaluating and comparing the candidate parameter sets, which resulted in a few promising sets that performed well with respect to at least three of four performance criteria. The promising sets were all from the multi‐objective calibration scenarios which revealed the outperformance of the multi‐objective calibration on the single‐objective one. However, the results indicated that an increase of the number of objective functions did not necessarily lead to a better performance as the results of bi‐objective function calibration with a proper combination of objective functions performed as satisfactorily as those of triple‐objective function calibration. This is important because handling multi‐objective optimization with an increased number of objective functions is challenging especially from a computational point of view. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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Soil aggregate stability has been known as one of the most important soil properties which is influenced by cultivation system. This study investigates the effect of different cultivation systems on aggregate stability indices in two statuses of dry (DSA?>?0.25 mm) and wet (WSA?>?0.25 mm). The study was done in six cultivation systems consisting wheat, barley, maize, alfalfa, fallow, and plowed farms. The results showed that aggregate stability indices affected significantly by the type of cultivation system. In contrast, no meaningful effect of soil depth (0–10 and 10–20 cm) on selected soil properties was observed. In addition, soil primary particles as well as organic carbon differed significantly between the cultivation systems. Wheat and alfalfa farms consisted of larger aggregates, while water-stable aggregate for wheat found to be in a greater degree. Moreover, wheat and barley showed the highest contents of organic carbon. The results of WSA?>?0.25 mm indicated that the correlation coefficients for sand, silt, clay, and organic carbon contents were ?0.67, 0.74, 0.12, and 0.70, respectively. Compared to the DSA?>?0.25 mm, the effect of soil organic carbon on the WSA?>?0.25 mm was arisen while the influence of clay fraction reduced. 相似文献
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Mehdi Zare Sepideh Karimiparidari Hossein Memarian Farnaz Kamranzad 《Arabian Journal of Geosciences》2016,9(19):737
Two main goals are considered in this paper: (1) modification and computation of the local coefficients of the space-time windows in the well-known declustering algorithm introduced by Gardner and Knopoff (1974) and (2) checking the independence of the Iranian mainshocks obtained from applying the new modified model. First, 21 of the well-documented earthquake sequences of Iran in the time period of 1972 to 2008 with the mainshock magnitude ranged from M w = 5.4–7.1 were used to define the new local space-time windows of declustering. Generally, using these Iranian earthquake sequences led to introduce bigger space-time windows for the new model in comparison to the Gardner and Knopoff’s (1974) windows. In the next step, to control the independence of Iranian mainshocks, the events of the Iranian earthquake catalog in the time span of 1964–2010 with moment magnitude of M w = 3.5–7.4 were used. In this respect, dependent events corresponding to the seven seismotectonic zones of Iran were removed using the new modified space-time windows. After declustering, the mainshock catalog was examined by the Kolmogorov–Smirnov goodness-of-fit test, and it was found to follow a Poisson distribution in all the studied seismotectonic zones of Iran. The same test on times between successive declustered events shows that the inter-event times of all catalogs follow an exponential distribution. 相似文献
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This paper aims to determine the damage distribution and to analyze the available strong motion records of the April 25, 2015 Nepal earthquake and its eight aftershocks. For this purpose, an earthquake investigation team was dispatched to Nepal from May 6 to 11, 2015 to evaluate the damages of the epicentral region and the four affected cities containing Kathmandu, Bhaktapur, Gorkha, and Pokhara. Based on the observations from the damages to the built environment, an iso-intensity map is prepared on the EMS-98 intensity scale in which the maximum intensity in the epicentral region is estimated to be about VIII. However, based on the geological and geotechnical evidences such as landslide volumes and ground fissures, the maximum intensity can be inferred about IX or X on the International Union for Quaternary Research (INQUA) intensity scale. In addition, the available strong motion data of the 2015 Nepal mainshock and its eight large aftershocks recorded at the KATNP accelerometric station in Kathmandu were processed and analyzed. In order to investigate the probable site effects, the Fourier amplitude spectra (FAS) of the horizontal north-south (N) and east-west (E) components and the average of them (H avg) were divided to the FAS of the vertical (Z) component and thus, the \( \raisebox{1ex}{$ N$}\!\left/ \!\raisebox{-1ex}{$ Z$}\right. \), \( \raisebox{1ex}{$ E$}\!\left/ \!\raisebox{-1ex}{$ Z$}\right. \), \( \raisebox{1ex}{${H}_{\mathrm{avg}}$}\!\left/ \!\raisebox{-1ex}{$ Z$}\right. \) spectral ratios were calculated. Based on these horizontal to vertical spectral ratios, a low-frequency peak at about 0.2–0.3 Hz (3.5–5-s period) is observed clearly in all the records. Accordingly, the repeated results might imply site amplification due to the thick alluvial deposits and the high groundwater level at the KATNP accelerometric station within the Kathmandu basin. It should be noted that all the horizontal to vertical spectral ratios of the aftershocks show a high peak at around 1.5–3 Hz, which is missed in the horizontal to vertical spectral ratio of the mainshock. On the other hand, considering the low angle of the causative fault plane, a near-source directivity effect on the fault normal direction (here, the vertical component) of the April 25, 2015 mainshock rupture may exist. Therefore, vertical to horizontal spectral ratios (\( \raisebox{1ex}{$ Z$}\!\left/ \!\raisebox{-1ex}{$ N$}\right. \) and \( \raisebox{1ex}{$ Z$}\!\left/ \!\raisebox{-1ex}{$ E$}\right. \)) were also calculated to find the vertical peak more clearly. The figures confirmed a peak at the frequency of 1.5–3 Hz in the mainshock spectra which is not repeated on the aftershock spectra and thus can probably be attributed as the pulse of directivity effect toward Kathmandu. This inferred directivity pulse can be also well distinguished on the velocity and displacement time histories of the mainshock. 相似文献
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Forecasting of wave parameters is necessary for many marine and coastal operations. Different forecasting methodologies have been developed using the wind and wave characteristics. In this paper, artificial neural network (ANN) as a robust data learning method is used to forecast the wave height for the next 3, 6, 12 and 24 h in the Persian Gulf. To determine the effective parameters, different models with various combinations of input parameters were considered. Parameters such as wind speed, direction and wave height of the previous 3 h, were found to be the best inputs. Furthermore, using the difference between wave and wind directions showed better performance. The results also indicated that if only the wind parameters are used as model inputs the accuracy of the forecasting increases as the time horizon increases up to 6 h. This can be due to the lower influence of previous wave heights on larger lead time forecasting and the existing lag between the wind and wave growth. It was also found that in short lead times, the forecasted wave heights primarily depend on the previous wave heights, while in larger lead times there is a greater dependence on previous wind speeds. 相似文献
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Haoyuan Hong Biswajeet Pradhan Maher Ibrahim Sameen Bahareh Kalantar Axing Zhu Wei Chen 《Landslides》2018,15(4):753-772
Landslide is a natural disaster that threatens human lives and properties worldwide. Numerous have been conducted on landslide susceptibility mapping (LSM), in which each has attempted to improve the accuracy of final outputs. This study presents a novel region-partitioning approach for LSM to understand the effects of partitioning a focused region into smaller areas on the prediction accuracy of common regression models. Results showed that the partitioning of the study area into two regions using the proposed method improved the prediction rate from 0.77 to 0.85 when support vector machine was used, and from 0.87 to 0.88 when logistic regression model was utilized. The spatial agreements of the models were also improved after partitioning the area into two regions based on Shannon entropy equations. Our comparative study indicated that the proposed method outperformed the geographically weighted regression model that considered the spatial variations in landslide samples. Overall, the main advantages of the proposed method are improved accuracy and the reduction of the effects of spatial variations exhibited in landslide-conditioning factors. 相似文献
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