地震检波器的横向灵敏度特性

地震检波器受到地面横向运动激励时的输入输出关系定义为检波器的横向灵敏度特性.本文对检波器线圈受到横向激励时产生的轴向振动进行了分析.可以看到,当悬挂线圈的弹簧片悬丝发生动力失稳时,检波器的横向灵敏度突然增大;在线圈横向振幅很小的情况下,失稳频率接近悬丝的横向固有频率.利用谱分析技术可以准确地从检波器噪声中检测出检波器的横向灵敏度和失稳频率,即检波器假频.     

不同区域海温对亚洲夏季副热带西风急流变异主模态的影响

利用1979—2014年ERA Interim再分析资料和NCAR CAM5.1大气环流模式,围绕海温对夏季亚洲急流变异主模态的影响展开研究。首先通过理论分析和动力诊断方法,对急流主模态的物理特征进行分析,并证实了海温与急流变异的显著联系。随后基于观测结果设计数值试验方案,探究不同区域海温对急流演变的具体贡献。结果表明,急流第一模态与太平洋及印度洋异常海温紧密联系,在二者相似的贡献下,高层异常风场表现为沿急流轴线南北偏移的纬向对称分布;急流第二模态的上、下游风场则受到不同海表热源影响,在印度洋、太平洋及北大西洋异常海温的协同作用下,亚洲上空形成了四极型纬向非对称的风场分布。该结果有利于更加综合地认识亚洲夏季副热带急流的变异特征,也为研究海温对急流的影响效应提供了新的依据。     

甘肃南部武都地区泥石流危险性评价

泥石流的发生受控于多种因子,而各因子属性段对泥石流的发生起到不同的作用.以甘肃南部武都地区为研究区,考虑到地震扰动影响并结合当地的地质环境条件,选取了高程、坡度、岩性、土地利用类型、滑坡点密度、地震因子、地质构造缓冲区及归一化植被指数(NDVI)等8个评价因子进行危险性评价.而后基于信息量模型和敏感性分析法对各影响因子属性类进行计算分析,得到各属性类的量化值.最后通过叠置分析,得到泥石流灾害危险性分区.结果表明,在中度、高度及极高度危险区内,信息量模型中分布的泥石流面积占研究区泥石流总面积的百分比为22.5％,24.7％,37.2％,而敏感性模型中占到的比例分别为25.5％,28.1％和36.4％.敏感性模型中中度危险区以上包含的泥石流比例占到90％,大于信息量模型的84.4％,因此,采用敏感性模型得到的危险性分区结果具有更高的精确性,能够为实际应用提供参考依据.     

Sensitivity analysis of spatially aggregated responses: A gradient‐based method

We often need to report on environmental, economic and social indicators, and properties at aggregated spatial scales, e.g. average income per suburb. To do this, we invariably create reporting polygons that are somewhat arbitrary. The question arises: how much does this arbitrary subdivision of space affect the outcome? In this paper, we develop a new, gradient‐based framework for carrying out a rigorous analysis of the sensitivity of integrating functions to quantitative changes in their spatial configuration. This approach is applied to both analytical and empirical models, and it allows the reporting of a hierarchy of sensitivity measures (from global to local). We found that the concepts of a vector space representing the spatial configurations and the response (hyper‐)surface on which gradients indicate the sensitivities to be helpful in developing the sensitivity analytical framework of spatial configurations in different dimensions. This approach works well with both analytical and empirical integrating functions. This approach resulted in a clear ranking of the sensitivities of the responses to changes in the reporting regions in an existing environmental reporting application. The approach also allowed us to find which vertices, and the directions of change of those vertices, influenced the outcome most. The application of the spatial framework allows the results to be reported in a hierarchical way, from the sensitivities of an integrative response to changes in a whole reserve/reporting system, down to the sensitivity along each of the dimensions of the vertices in the spatial configuration. The results of the spatial sensitivity framework that we developed in this paper can be readily visualized by plotting the sensitivities as vectors on geographic maps. This simplifies the presentation and facilitates the uptake of the results in the situations where the spatial configurations are complicated.     

农户生计对气候变化的敏感性研究综述

开展农户生计对气候变化的敏感性研究有利于深入认识气候变化与生计的关系,对增强农户的气候变化适应能力和降低生计脆弱性具有重要意义。在梳理不同领域敏感性概念的基础上,阐述了农户生计对气候变化敏感性的科学内涵和研究框架,重点分析了敏感性表征和综合评价指标体系。农户生计对气候变化的敏感性是指气候变化和极端事件对农户生计的影响程度,敏感性表征主要表现在气候变化对自然资源、人类健康、牲畜、资产和收入等方面的影响,不同地区和人群敏感性表征具有差异性。农户生计对气候变化的敏感性随着发展程度提高而下降,生计多样化、基础设施建设等有助于降低气候变化的影响。生计敏感性多为脆弱性研究的一部分,常以可持续生计分析为框架,运用指标评估法进行综合评价。未来研究需要完善敏感性理论框架和研究方法,加强适应的有效性评估,以及开展跨区域或跨时段的生计敏感性对比研究,重点关注生态脆弱和贫困地区。     

Hybrid meta-heuristic machine learning methods applied to landslide susceptibility mapping in the Sahel-Algiers

Landslides are considered as one among many phenomena jeopardizing human beings as well as their constructions. To prevent this disastrous problem, researchers have used several approaches for landslide susceptibility modeling, for the purpose of preparing accurate maps marking landslide prone areas. Among the most frequently used approaches for landslide susceptibility mapping is the Artificial Neural Network (ANN) method. However, the effectiveness of ANN methods could be enhanced by using hybrid metaheuristic algorithms, which are scarcely applied in landslide mapping. In the current study, nine hybrid metaheuristic algorithms, genetic algorithm (GA)-ANN, evolutionary strategy (ES)-ANN, ant colony optimization (ACO)-ANN, particle swarm optimization (PSO)-ANN, biogeography based optimization (BBO)-ANN, gravitational search algorithm (GHA)-ANN, particle swarm optimization and gravitational search algorithm (PSOGSA)-ANN, grey wolves optimization (GWO)-ANN, and probability based incremental learning (PBIL)-ANN have been used to spatially predict landslide susceptibility in Algiers’ Sahel, Algeria. The modeling phase was done using a database of 78 landslides collected utilizing Google Earth images, field surveys, and six conditioning factors (lithology, elevation, slope, land cover, distance to stream, and distance to road). Initially, a gamma test was used to decrease the input variable numbers. Furthermore, the optimal inputs have been modeled by the mean of hybrid metaheuristic ANN techniques and their performance was assessed through seven statistical indicators. The comparative study proves the effectiveness of the co-evolutionary PSOGSA-ANN model, which yielded higher performance in predicting landslide susceptibility compared to the other models. Sensitivity analysis using the step-by-step technique was done afterward, which revealed that the distance to the stream is the most influential factor on landslide susceptibility, followed by the slope factor which ranked second. Lithology and the distance to road have demonstrated a moderate effect on landslide susceptibility. Based on these findings, an accurate map has been designed to help land-use managers and decision-makers to mitigate landslide hazards.     

A sensitivity analysis of factors affecting in geologic CO2 storage in the Ordos Basin and its contribution to carbon neutrality

To accelerate the achievement of China’s carbon neutrality goal and to study the factors affecting the geologic CO₂ storage in the Ordos Basin, China’s National Key R&D Programs propose to select the Chang 6 oil reservoir of the Yanchang Formation in the Ordos Basin as the target reservoir to conduct the geologic carbon capture and storage (CCS) of 100000 t per year. By applying the basic theories of disciplines such as seepage mechanics, multiphase fluid mechanics, and computational fluid mechanics and quantifying the amounts of CO₂ captured in gas and dissolved forms, this study investigated the effects of seven factors that influence the CO₂ storage capacity of reservoirs, namely reservoir porosity, horizontal permeability, temperature, formation stress, the ratio of vertical to horizontal permeability, capillary pressure, and residual gas saturation. The results show that the sensitivity of the factors affecting the gas capture capacity of CO₂ decreases in the order of formation stress, temperature, residual gas saturation, horizontal permeability, and porosity. Meanwhile, the sensitivity of the factors affecting the dissolution capture capacity of CO₂ decreases in the order of formation stress, residual gas saturation, temperature, horizontal permeability, and porosity. The sensitivity of the influencing factors can serve as the basis for carrying out a reasonable assessment of sites for future CO₂ storage areas and for optimizing the design of existing CO₂ storage areas. The sensitivity analysis of the influencing factors will provide basic data and technical support for implementing geologic CO₂ storage and will assist in improving geologic CO₂ storage technologies to achieve China’s carbon neutralization goal.©2022 China Geology Editorial Office.     

平凉台井下地电阻率观测影响系数分析

根据地电阻率影响系数理论,以平凉台4层电性结构为例,分析了井下对称四极地电阻率观测影响系数随深度和极距的变化。结果表明:对于固定的观测极距,影响系数与电极埋深之间的关系复杂;通过计算各层影响系数的大小,认为平凉台井下观测对地表及浅层干扰有较好的抑制作用,其分析结果可为在类似台址电性结构中实施井下地电阻率观测时选择电极埋深和供电极距提供参考。     

基于一阶速度-应力方程的VTI介质最小二乘逆时偏移

地下地层普遍存在各向异性,忽略介质各向异性会导致速度估计不准确,成像精度下降.基于二阶声波方程的最小二乘逆时偏移忽略了介质各向异性及密度变化的影响,致使模拟地震数据与实际观测数据不匹配,影响收敛速度和反演成像质量.VTI介质一阶速度-应力方程能较好适应各向异性变密度情况,为此,本文首先从VTI介质一阶速度-应力方程出发,进行波动方程线性化;其次推导了相应的扰动方程和伴随方程,并通过伴随状态法得到梯度更新公式;最终形成基于一阶方程的LSRTM算法理论及实现流程.在实现算法的基础上,通过数值试算及成像结果对比,验证了本文算法在处理变密度和VTI介质时的有效性和优越性.偏移速度以及各向异性Thomsen参数误差的敏感性测试及误差收敛曲线对比结果进一步表明:速度及Thomsen参数对成像结果存在明显影响,其中速度敏感性最强,参数epsilon次之,参数delta的敏感性最弱.     

Two‐dimensional joint inversions of cross‐hole resistivity data and resolution analysis of combined arrays

In this study, a new two‐dimensional inversion algorithm was developed for the inversion of cross‐hole direct current resistivity measurements. In the last decades, various array optimisation methods were suggested for resistivity tomography. However, researchers have still collected data by using classical electrode arrays in most cross‐hole applications. Therefore, we investigated the accuracy of both the individual and the joint inversion of the classical cross‐hole arrays by using both synthetic and field data with the developed algorithm. We showed that the joint inversion of bipole–bipole, pole–bipole, bipole–pole, and pole–tripole electrode arrays gives inverse solutions that are closer to the real model than the individual inversions of the electrode array datasets for the synthetic data inversion. The model resolution matrix of the suggested arrays was used to analyse the inversion results. This model resolution analysis also showed the advantage of the joint inversion of bipole–bipole, pole–bipole, bipole–pole, and pole–tripole arrays. We also used sensitivity sections from each of the arrays and their superpositions to explain why joint inversion gives better resolution than the any individual inversion result.