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Mikhail K. Kaban Alexey G. Petrunin Harro Schmeling Meysam Shahraki 《Surveys in Geophysics》2014,35(6):1361-1373
A joint effect of weak zones, dividing lithospheric plates, and lateral viscosity variations (LVV) in the whole mantle on the observed geoid is investigated by a new numerical approach. This technique is based on the substantially revised method introduced by Zhang and Christensen (Geophys J Int 114:531–547, 1993) for solving the Navier–Stokes–Poisson equations in the spectral domain with strong LVV. Weak plate boundaries (WPB) are introduced based on an integrated global model of plate boundary deformations GSRM (Kreemer et al. in Geophys J Int 154:8–34, 2003). The effect of WPB on the geoid is significant and reaches ?40 to 70 m with RMS ~20 m. The peaks are observed over large subduction zones in South America and the southwestern Pacific in agreement with previous studies. The positive geoid anomaly in South America could be explained largely by a dynamic effect of decoupling of the Nazca and South American plates. The negative changes of the geoid mostly relate to mid-oceanic ridges. The amplitude of the effect depends on the viscosity contrasts at WPB compared with the plate viscosity until its value reaches the limit of 2.5–3 orders of magnitude. This value might be considered as a level at which the plates are effectively decoupled. The effect of WPB exceeds the effect of LVV in the whole mantle and generally does not correlate with it. However, inclusion of LVV reduces the geoid perturbations due to WPB by about 10 m. Therefore, it is important to consider all factors together. The geoid changes mainly result from changes of the dynamic topography, which are about ?300 to +500 m. The obtained results show that including WPB may significantly improve the reliability of instantaneous global dynamic models. 相似文献
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M. Imani R.-J. You C.-Y. Kuo 《International Journal of Environmental Science and Technology》2014,11(4):1035-1042
The demand for accurate predictions of sea level fluctuations in coastal management and ship navigation activities is increasing. To meet such demand, accessible high-quality data and proper modeling process are critically required. This study focuses on developing and validating a neural methodology applicable to the short-term forecast of the Caspian Sea level. The input and output data sets used contain two time series obtained from Topex/Poseidon and Jason-1 satellite altimetry missions from 1993 to 2008. The forecast is performed by multilayer perceptron network, radial basis function, and generalized regression neural networks. Several tests of different artificial neural network (ANN) architectures and learning algorithms are carried out as alternative methods to the conventional models to assess their applicability for estimating Caspian Sea level anomalies. The results derived from the ANN are compared with observed sea level values and with the forecasts calculated by a routine autoregressive moving average (ARMA) model. Different ANNs satisfactorily provide reliable results for the short-term prediction of Caspian Sea level anomalies. The root mean square errors of the differences between observations and predictions from artificial intelligence approaches can be significantly reduced by about 50 % compared with ARMA techniques. 相似文献
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Watershed-wide trend analysis of temperature characteristics in Karun-Dez watershed, southwestern Iran 总被引：2，自引：1，他引：1
Safar Marofi Samere Soleymani Meysam Salarijazi Hossein Marofi 《Theoretical and Applied Climatology》2012,110(1-2):311-320
Trend estimation of climatic characteristics for a watershed is required to determine developing compatible strategies related to design, development, and management of water resources. In this study, the trends of the annual maximum (T max), minimum (T min), and mean (T mean) air temperature; temperature anomaly (T anomaly); and diurnal temperature range (DTR) time series at 13 meteorological stations located in the Karun-Dez watershed were analyzed using the Mann–Kendall and linear regression trend tests. The pre-whitening method was used to eliminate the influence of serial correlation on the Mann–Kendall test. The result showed increasing trends in the T min, T mean, and T anomaly series at the majority of stations and decreasing trend in the T max and DTR series. A geographical analysis of the trends revealed a broad warming trend in most of the watershed, and the cooling trends were observed only in the southern parts. Furthermore, the geographical pattern of the trends in the T mean and T anomaly series was similar, and the T max data did not show any dominant trend for the whole watershed. This study provides temperature change scenarios that may be used for the design of future water resource projects in the watershed. 相似文献
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Improved rotational hardening rule for cohesive soils and definition of inherent anisotropy 
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下载免费PDF全文 Improved, microfabric‐inspired rotational hardening rules for the plastic potential and bounding surfaces associated with the generalized bounding surface model for cohesive soils are presented. These hardening rules include 2 new functions, fη and , that improve the simulation of anisotropically consolidated cohesive soils. Three model parameters are associated with the improved hardening rules. A detailed procedure for obtaining suitable values for these parameters is presented. The first 2 parameters affect the simulation of constant stress ratio loading where, because of the presence of fη, the third parameter is inactive. The second new function, , accelerates the rotation of the plastic potential and bounding surfaces during shearing, which is particularly important for overconsolidated soils tested in extension. This paper also describes the proper manner in which to define the inherent anisotropy. This seemingly straightforward test has rarely been discussed in sufficient detail. 相似文献
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ABSTRACTThe potential of different models – deep echo state network (DeepESN), extreme learning machine (ELM), extra tree (ET), and regression tree (RT) – in estimating dew point temperature by using meteorological variables is investigated. The variables consist of daily records of average air temperature, atmospheric pressure, relative humidity, wind speed, solar radiation, and dew point temperature (Tdew) from Seoul and Incheon stations, Republic of Korea. Evaluation of the model performance shows that the models with five and three-input variables yielded better accuracy than the other models in these two stations, respectively. In terms of root-mean-square error, there was significant increase in accuracy when using the DeepESN model compared to the ELM (18%), ET (58%), and RT (64%) models at Seoul station and the ELM (12%), ET (23%), and RT (49%) models at Incheon. The results show that the proposed DeepESN model performed better than the other models in forecasting Tdew values. 相似文献
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Water Resources - The lack of long term observed data is the main challenge in many simulation-based studies for identification of nutrient critical source areas (CSAs). This study explored the... 相似文献
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The transmission of seismic waves in a particular region may influence the hydraulic properties of a rock mass, including permeability, which is one of the most important. To determine the effect of a seismic wave on the hydraulic behavior of a fractured rock mass, systematic numerical modeling was conducted. A number of discrete fracture network(DFN) models with a size of 20 m × 20 m were used as geometrical bases, and a discrete element method(DEM) was employed as a numerical simulation tool. Three different boundary conditions without(Type Ⅰ) and with static(Type Ⅱ) and dynamic(Type Ⅲ) loading were performed on the models, and then their permeability was calculated. The results showed that permeability in Type Ⅲ models was respectively 62.7% and 44.2% higher than in Type I and Type Ⅱ models. This study indicates that seismic waves can affect deep earth, and, according to the results, seismic waves increase the permeability and change the flow rate patterns in a fractured rock mass. 相似文献
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In this study, we successfully present the analysis and forecasting of Caspian Sea level pattern anomalies based on about 15 years of Topex/Poseidon and Jason-1 altimetry data covering 1993–2008, which are originally developed and optimized for open oceans but have the considerable capability to monitor inland water level changes. Since these altimetric measurements comprise of a large datasets and then are complicated to be used for our purposes, principal component analysis is adopted to reduce the complexity of large time series data analysis. Furthermore, autoregressive integrated moving average (ARIMA) model is applied for further analyzing and forecasting the time series. The ARIMA model is herein applied to the 1993–2006 time series of first principal component scores (sPC1). Subsequently, the remaining data acquired from sPC1 is used for verification of the model prediction results. According to our analysis, ARIMA (1,1,0)(0,1,1) model has been found as optimal representative model capable of predicting pattern of Caspian Sea level anomalies reasonably. The analysis of the time series derived by sPC1 reveals the evolution of Caspian Sea level pattern can be subdivided into five different phases with dissimilar rates of rise and fall for a 15-year time span. 相似文献