河北邯邢地区铁、煤矿山治水及水资源开发利用途径

邯邢地区西部武安—涉县古生代凹陷中,沉积了一套厚大的寒武—奥陶系的碳酸盐岩,是本区岩溶水的主要赋存层位。邯邢地区的工、农业及生活用水主要是依靠岩溶水资源。但该区埋藏着丰富的铁、煤等矿产,由于地下岩溶水丰富又给矿山的开采造成很大的困难,为了解决这一矛盾,处理好供排关系,充分开发利用铁、煤矿产和地下水资源,本文提出一些探索性看法。      

古环境对河北古岩溶发育影响

碳酸盐岩的岩溶发育过程是诸多因素综合作用的结果。古气候环境对河北古岩溶发育起到控制作用。喜山期早第三纪河北南部显示了热带—亚热带气候特征,根据古地磁测得的磁矢量值推算河北邢台内邱一带古纬度值为20.6°,要比现今纬度靠南16°左右。早第三纪是河北古岩溶发育形成的主要时期,该期形成的数层溶洞分布于太行山,燕山区和河北平原几千米深的古潜山。河北存在古岩溶而且发育的还很强烈,因此,不能用现代气候去否认北方曾有过古岩溶的事实,也不能把古岩溶与现代岩溶混为一谈。      

安徽淮北北部岩溶水资源评价及开发利用

根据地质、水文地质条件、把所论岩溶地区划分为“基岩裸渗区”、“山前平原连通区”和“深隐伏越流区”三种资源评价区,采用水均衡的方法,进行岩溶水开采资源的计算,并以此为据,预测了有远景的水源地八处,提出了合理开发利用意见。      

曲阳大理石矿岩溶发育机制研究

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      

人影高炮作业落区的一种判定方法

提出了人影高炮弹丸轨迹的运动方程,根据方程计算理论弹丸落点并得出安全区外扩的误差范围。针对人影高炮作业射界设定安全区的情况,提出落点位于安全区内外的判定方法,从而在理论上给出判断人影高炮作业安全性的问题。     

The formation of explosive volcanos at the circum-Pacific convergent margin during the last century

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....     

碘酸钾标准物质的研制

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     

Predicting spatio-temporal concentrations of PM<Subscript>2.5</Subscript> using land use and meteorological data in Yangtze River Delta,China

The prediction of PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 concentration predictions with a spatiotemporal resolution of 3 km × week, which would contribute to accurately assessing the potential health effects of air pollution.     

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.     

3D P‐wave traveltime computation in transversely isotropic media using layer‐by‐layer wavefront marching

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.