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41.
To project potential habitat changes of 57 fish species under global warming, their suitable thermal habitat at 764 stream gaging stations in the contiguous United States was studied. Global warming was specified by air temperature increases projected by the Canadian Centre of Climate Modelling General Circulation Model for a doubling of atmospheric CO2. The aquatic thermal regime at each gaging station was related to air temperature using a nonlinear stream temperature/air temperature relationship.Suitable fish thermal habitat was assumed to be constrained by both maximum temperature and minimum temperature tolerances. For cold water fishes with a 0 °C lower temperature constraint, the number of stations with suitable thermal habitat under a 2×CO2 climate scenario is projected to decrease by 36%, and for cool water fishes by 15%. These changes are associated with a northward shift of the range. For warm water fishes with a 2 °C lower temperature constraint, the potential number of stations with suitable thermal habitat is projected to increase by 31%. 相似文献
42.
Phuong Thao Thi Ngo Mahdi Panahi Khabat Khosravi Omid Ghorbanzadeh Narges Kariminejad Artemi Cerda Saro Lee 《地学前缘(英文版)》2021,12(2):505-519
The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses.In this study,we applied two novel deep learning algorithms,the recurrent neural network(RNN)and convolutional neural network(CNN),for national-scale landslide susceptibility mapping of Iran.We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors(altitude,slope degree,profile curvature,distance to river,aspect,plan curvature,distance to road,distance to fault,rainfall,geology and land-sue)to construct a geospatial database and divided the data into the training and the testing dataset.We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset.We calculated the receiver operating characteristic(ROC)curve and used the area under the curve(AUC)for the quantitative evaluation of the landslide susceptibility maps using the testing dataset.Better performance in both the training and testing phases was provided by the RNN algorithm(AUC=0.88)than by the CNN algorithm(AUC=0.85).Finally,we calculated areas of susceptibility for each province and found that 6%and 14%of the land area of Iran is very highly and highly susceptible to future landslide events,respectively,with the highest susceptibility in Chaharmahal and Bakhtiari Province(33.8%).About 31%of cities of Iran are located in areas with high and very high landslide susceptibility.The results of the present study will be useful for the development of landslide hazard mitigation strategies. 相似文献
43.
Sun Qingfeng Zamanian Kazem Huguet Arnaud Bayat Omid Wang Hong Badawy Hanan S. 《中国地球化学学报》2022,41(5):811-822
Acta Geochimica - Desert rhizoliths are generally found as weathered, broken and scattered samples on dune field surface, but rarely in-situ in their initial states buried under the soil of desert... 相似文献
44.
Bulletin of Earthquake Engineering - A structure may be subject to several aftershocks after a mainshock. In many seismic design provisions, the effect of the seismic sequences is either not... 相似文献
45.
Most approaches in statistical spatial prediction assume that the spatial data are realizations of a Gaussian random field.
However, this assumption is hard to justify for most applications. When the distribution of data is skewed but otherwise has
similar properties to the normal distribution, a closed skew normal distribution can be used for modeling their skewness.
Closed skew normal distribution is an extension of the multivariate skew normal distribution and has the advantage of being
closed under marginalization and conditioning. In this paper, we generalize Bayesian prediction methods using closed skew
normal distributions. A simulation study is performed to check the validity of the model and performance of the Bayesian spatial
predictor. Finally, our prediction method is applied to Bayesian spatial prediction on the strain data near Semnan, Iran.
The mean-square error of cross-validation is improved by the closed skew Gaussian model on the strain data. 相似文献
46.
Omid Saeidi Seyed Rahman Torabi Mohammad Ataei 《Rock Mechanics and Rock Engineering》2014,47(2):717-732
Rock mass classification systems are one of the most common ways of determining rock mass excavatability and related equipment assessment. However, the strength and weak points of such rating-based classifications have always been questionable. Such classification systems assign quantifiable values to predefined classified geotechnical parameters of rock mass. This causes particular ambiguities, leading to the misuse of such classifications in practical applications. Recently, intelligence system approaches such as artificial neural networks (ANNs) and neuro-fuzzy methods, along with multiple regression models, have been used successfully to overcome such uncertainties. The purpose of the present study is the construction of several models by using an adaptive neuro-fuzzy inference system (ANFIS) method with two data clustering approaches, including fuzzy c-means (FCM) clustering and subtractive clustering, an ANN and non-linear multiple regression to estimate the basic rock mass diggability index. A set of data from several case studies was used to obtain the real rock mass diggability index and compared to the predicted values by the constructed models. In conclusion, it was observed that ANFIS based on the FCM model shows higher accuracy and correlation with actual data compared to that of the ANN and multiple regression. As a result, one can use the assimilation of ANNs with fuzzy clustering-based models to construct such rigorous predictor tools. 相似文献
47.
A new approach for the geological risk evaluation of coal resources through a geostatistical simulation 总被引：1，自引：1，他引：0
Estimations of mineral resources and ore reserves have been recently widely used by mining engineers and investors. The classification framework based on the prepared code by the Joint Ore Reserves Committee of The Australasian Institute of Mining and Metallurgy, Australian Institute of Geoscientists and Minerals Council of Australia (JORC code), which is one of the international standards for mineral resource and ore reserve reporting, provides a template system that conforms to international society requirements. Recent research has shown that an existing fault risk can affect the mineral resource and ore reserve estimation. According to this research, the faulted area that is involved in the effect on the estimated region is so extensive that it is not distinguishable. In this research, a new method called FGT (F for fault, G for grade and T for thickness) is introduced and presented for the estimation of mineral resources. The proposed method can provide an error map of a particular aspect of the combination of coal accumulation (G), fault risk (F) and thickness (T), and its output would categorise the mineral resources. This method was implemented in the Parvadeh Ш coal deposit, which is located in the eastern portion of Central Iran. The deposit contains five seams named B1, B2, C1, C2 and D; of these, C1 was selected as the most important seam in the exploratory grid analysis. Thus, C1 alone can reflect the properties of the Parvadeh Ш deposit. In this study, we compared the conventional method and the FGT method. This comparison indicated that the areas that should be rejected from the region in the FGT method are less and more distinguishable than those determined with the conventional method. Therefore, the inferred resources can be completely differentiated from the indicated and measured resources with a high resolution. The conventional method cannot distinguish between these three categories at this level of resolution. Therefore, the FGT approach has high precision in classifying the coal resource compared to the conventional method. 相似文献
48.
Fault detection in 3D by sequential Gaussian simulation of Rock Quality Designation (RQD) 总被引：1，自引：0，他引：1
Gazestan phosphate ore deposit (Central Iran) is an apatite deposit which is instrumental in selecting the method of excavation. The position of fault systems and the condition of rock quality also play a role in the method used for mineral resources and ore reserves estimation. Conversely, the Rock Quality Designation (RQD) is a parameter that provides a quantitative judgment of rock mass quality obtained from drill cores. This factor can be applied to detect the fractured zones which occur due to fault systems. Additionally, the faulted areas can be determined by surface geological map and a few by core drilling. Some of the faulted areas are not distinguishable in the surface and are covered by soils, especially within 3D modeling and visualization. In this study, an attempt has been made to establish a relationship between the RQD percentages which were geostatistically simulated and faulted areas through the region. In comparison, the results showed that low RQD domains (RQD <20 %) can be interpreted as fault zones; high RQD domains (RQD >50 %) correspond to less fractured areas, and the contact between high and low RQD domain is gradual. Therefore, this categorization of RQD domains can be incorporated to detect the faulted zones in 3D models for mine design. Based on the categorization, the uncertainty within the area was calculated to introduce two new core drilling points for the completion of this phase of exploratory grid from the fault structural viewpoint, in order to have a proper model of ore reserve to estimate. It was concluded that this procedure can be utilized for conceptual comprehension of fault trends in 3D modeling for the method selection of excavation and complete the estimation procedure phase. 相似文献
49.
Abedi Maysam Asghari Omid Norouzi Gholam-Hossain 《Arabian Journal of Geosciences》2015,8(4):2179-2189
Arabian Journal of Geosciences - This paper describes a general framework of incorporating magnetic data as prior information in the modeling of an iron deposit based on sparse drilling boreholes.... 相似文献
50.
Mehmet Aktas Galip Aydin Andrea Donnellan Geoffrey Fox Robert Granat Lisa Grant Greg Lyzenga Dennis McLeod Shrideep Pallickara Jay Parker Marlon Pierce John Rundle Ahmet Sayar Terry Tullis 《Pure and Applied Geophysics》2006,163(11-12):2281-2296
We describe the goals and initial implementation of the International Solid Earth Virtual Observatory (iSERVO). This system is built using a Web Services approach to Grid computing infrastructure and is accessed via a component-based Web portal user interface. We describe our implementations of services used by this system, including Geographical Information System (GIS)-based data grid services for accessing remote data repositories and job management services for controlling multiple execution steps. iSERVO is an example of a larger trend to build globally scalable scientific computing infrastructures using the Service Oriented Architecture approach. Adoption of this approach raises a number of research challenges in millisecond-latency message systems suitable for internet-enabled scientific applications. We review our research in these areas. 相似文献