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991.
曲阳大理石矿发育的红色风化壳大都是第四纪第Ⅰ、Ⅱ间冰期湿热气候条件下溶蚀与风化作用的结果,形成硅酸—铁型风化壳。风化壳中红粘土化学成分R2O3(Al2O3+Fe2O3)含量达24.33—31.88%。当降水或地表水的垂直下渗,水中游离的氢离子与红粘土中固相的铝相互转化交换的愈多,红粘土的氢离子浓度愈大,pH值愈小其酸度愈大,溶蚀性增强。沿红粘土和大理岩接触面产生溶蚀作用,形成石芽、溶沟、溶槽、溶痕等岩溶形态,并在它们的表面保留有红粘土痕迹。 CAJ下 相似文献
992.
993.
Journal of Oceanology and Limnology - The circum-Pacific convergent margin is known as “the Ring of Fire”, with abundant volcano eruptions. Large eruptions are rare but very disastrous.... 相似文献
994.
本文介绍了碘酸钾标准物质的研制程序,其中包括溶液的配制、均匀性和稳定性检验、分析方法和数据统计处理方法等。并选择了具有高准确度的精密库仑法和自动电位滴定法分析定值,对制备浓度为0.01mol/dm3碘酸钾标准物质,其定值的相对不确定度可达0.1%,稳定期在一年以上 相似文献
995.
Dongyang?Yang Debin?Lu Jianhua?XuEmail author Chao?Ye Jianan?Zhao Guanghui?Tian Xinge?Wang Nina?Zhu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(8):2445-2456
The prediction of PM2.5 concentrations with high spatiotemporal resolution has been suggested as a potential method for data collection to assess the health effects of exposure. This work predicted the weekly average PM2.5 concentrations in the Yangtze River Delta, China, by using a spatio-temporal model. Integrating land use data, including the areas of cultivated land, construction land, and forest land, and meteorological data, including precipitation, air pressure, relative humidity, temperature, and wind speed, we used the model to estimate the weekly average PM2.5 concentrations. We validated the estimated effects by using the cross-validated R2 and Root mean square error (RMSE); the results showed that the model performed well in capturing the spatiotemporal variability of PM2.5 concentration, with a reasonably large R2 of 0.86 and a small RMSE of 8.15 (μg/m3). In addition, the predicted values covered 94% of the observed data at the 95% confidence interval. This work provided a dataset of PM2.5 concentration predictions with a spatiotemporal resolution of 3 km × week, which would contribute to accurately assessing the potential health effects of air pollution. 相似文献
996.
An InSAR scattering model for multi-layer snow based on Quasi-Crystalline Approximation (QCA) theory
Snow-cover parameters are important indicator factors for hydrological models and climate change studies and have typical vertical stratification characteristics. Remote sensing can be used for large-scale monitoring of snow parameters. InSAR (Interferometric Synthetic Aperture Radar) technology has advantages in detecting the vertical structure of snow cover. As a basis of snow vertical structure detection using InSAR, a scattering model can reveal the physical process of interaction between electromagnetic waves and snow. In recent years, the InSAR scattering model for single-layer snow has been fully studied; however, it cannot be applied to the case of multi-layer snow. To solve this problem, a multi-layer snow scattering mode is proposed in this paper, which applies the QCA (Quad-Crystal Approximation) theory to describe the coherent scattering characteristics of snow and introduces a stratification factor to describe the influence of snow stratification on the crosscorrelation of SAR echoes. Based on the proposed model, we simulate an InSAR volumetric correlation of different types of multi-layer snow at the X band (9.6 GHz). The results show that this model is suitable for multi-layer snow, and the sequence of sub-layers of snow has a significant influence on the volumetric correlation. Compared to the single layer model, the multi-layer model can predict a polarization difference in the volumetric correlation more accurately and thus has a wider scope of application. To make the model more available for snow parameter inversion, a simplified multi-layer model was also developed. The model did not have polarization information compared to that of the full model but showed good consistency with the full model. The phase of the co-polarization InSAR volumetric correlation difference is more sensitive to snow parameters than that of the phase difference of the co-polarization InSAR volumetric correlation and more conducive to the development of a parameter-inversion algorithm. The model can be applied to deepen our understanding of InSAR scattering mechanisms and to develop a snow parameter inversion algorithm. 相似文献
997.
3D P‐wave traveltime computation in transversely isotropic media using layer‐by‐layer wavefront marching 下载免费PDF全文
Jiangtao Hu Junxing Cao Huazhong Wang Xingjian Wang Renfei Tian 《Geophysical Prospecting》2018,66(7):1303-1314
Subsurface rocks (e.g. shale) may induce seismic anisotropy, such as transverse isotropy. Traveltime computation is an essential component of depth imaging and tomography in transversely isotropic media. It is natural to compute the traveltime using the wavefront marching method. However, tracking the 3D wavefront is expensive, especially in anisotropic media. Besides, the wavefront marching method usually computes the traveltime using the eikonal equation. However, the anisotropic eikonal equation is highly non‐linear and it is challenging to solve. To address these issues, we present a layer‐by‐layer wavefront marching method to compute the P‐wave traveltime in 3D transversely isotropic media. To simplify the wavefront tracking, it uses the traveltime of the previous depth as the boundary condition to compute that of the next depth based on the wavefront marching. A strategy of traveltime computation is designed to guarantee the causality of wave propagation. To avoid solving the non‐linear eikonal equation, it updates traveltime along the expanding wavefront by Fermat's principle. To compute the traveltime using Fermat's principle, an approximate group velocity with high accuracy in transversely isotropic media is adopted to describe the ray propagation. Numerical examples on 3D vertical transverse isotropy and tilted transverse isotropy models show that the proposed method computes the traveltime with high accuracy. It can find applications in modelling and depth migration. 相似文献
998.
When to conduct an isotopic survey for lake water balance evaluation in highly seasonal climates 下载免费PDF全文
One‐time or short‐term lake water isotopic surveys are often employed to evaluate regional lake water balance. However, it can be difficult to determine the optimal time‐window for sampling to obtain a representative long‐term perspective of lake water balance in settings influenced by seasonal variations in precipitation, evaporative loss, glacial/snow meltwater, and larger seasonal shifts in isotopic composition of precipitation. This is especially true for areas of the Tibetan Plateau that are influenced by the summer Indian monsoon. Although high‐frequency sampling is always preferred as the most rigorous approach to characterize the water budget of lakes or watersheds, this may be impractical in remote regions and over large spatial scales. To assess the potential sensitivity of isotope balance characterization to seasonal variability, we used a weekly lake water isotope data set acquired over a period of 3 years on the Tibetan Plateau to evaluate the potential inaccuracies that might have arisen from using isotopic data collected during narrower time‐windows. For this assessment, we use weekly isotopic data collected during the study and assume that these sampling events were stand‐alone one‐time surveys. We then demonstrate the sensitivity of the isotope balance method in this setting, particularly for the rainy season that significantly underestimated the evaporation/inflow. In contrast, isotopic composition of the lake water was found to be more representative of long‐term conditions when sampled in October on the Tibetan Plateau. To broaden our evaluation of seasonality effects over a range of climatic zones, published high‐frequency isotopic data were also compiled, and a similar assessment was carried out for selected regions of the world. The synthesized data and model outputs, which confirm pronounced variations in lake water isotopic composition and evaporation/inflow across a range of seasonal climates, were used to determine optimal sampling windows for these specific regions. 相似文献
999.
Kangkang Li Xiaoguang Qin Xiaoyan Yang Bing Xu Lei Zhang Guijin Mu Dong Wei Chunxue Wang Yong Wu Xiaohong Tian Yongchong Lin Wen Li Jiaqi Liu Yinxin Jiao 《中国科学:地球科学(英文版)》2018,61(11):1659-1668
The Lop Nur region, in the east part of Tarim Basin, was an important transportation junction between west and east, north and south Eurasia. However, previous studies on prehistoric human activity have concentrated mostly on the Bronze Age, whereas that during the Stone Age remains largely unresearched. Here, we present a new direct evidence of human activity in the late Pleistocene, recorded on a grinding stone buried in a lacustrine sediment section of the Lop Nur region. The grain size distribution of the sediment section indicates that the site was probably in the center of a lake with weak hydrodynamic environment. Therefore, the stone artifact can only be carried to here by people instead of river and it was never move as soon as left here. Results of radiocarbon dating, the evident stratigraphic relations between the stone artifact and the sedimentary formation, indicate that the human activity could extend to approximately 13 ka BP. Furthermore, the results of starch-grain and use-wear analyses suggest that ancient humans gathered seeds of Triticeae, roots, and tubers and used the grinding stone to simply process selected plant as plant foodstuffs during this period. It implies that the environmental conditions in the river delta of the Lop Nur were inhabitable during the late Pleistocene. 相似文献
1000.
Qian Lu Shijie Wang Xiaoyong Bai Fang Liu Shiqi Tian Mingming Wang Jinfeng Wang 《Acta Geochimica》2020,(1):116-126
In near-infrared spectroscopy,the traditional feature band extraction method has certain limitations.Therefore,a band extraction method named the three-step extraction method was proposed.This method combines characteristic absorption bands and correlation coefficients to select characteristic bands corresponding to various spectral forms and then uses stepwise regression to eliminate meaningless variables.Partial least squares regression(PLSR)and extreme learning machine(ELM)models were used to verify the effect of the band extraction method.Results show that the differential transformation of the spectrum can effectively improve the correlation between the spectrum and nickel(Ni)content.Most correlation coefficients were above 0.7 and approximately 20%higher than those of other transformation methods.The model effect established by the feature variable selection method based on comprehensive spectral transformation is only slightly affected by the spectral transformation form.Infive types of spectral transformation,the RPD values of the proposed method were all within the same level.The RPD values of the PLSR model were concentrated between 1.6 and 1.8,and those of the ELM model were between 2.5 and2.9,indicating that this method is beneficial for extracting more complete spectral features.The combination of the three-step extraction method and ELM algorithm can effectively retain important bands associated with the Ni content of the soil.The model based on the spectral band selected by the three-step extraction method has better prediction ability than the other models.The ELM model of the first-order differential transformation has the best prediction accuracy(RP^2=0.923,RPD=3.634).The research results provide some technical support for monitoring heavy metal content spectrum in local soils. 相似文献