2013年广西平果震群尾波衰减特征研究

2013年6~7月在广西平果县中铝广西分公司3号排泥库附近出现密集小震群活动。本文搜集本次震群中146次可用于计算尾波的ML1.0地震的近距离台站数字地震波形,利用波形高信噪比的尾波时间域信号,采用计算尾波品质因子Q_C(f)值的Sato模型,通过滤波及去除环境噪声,计算了地震波传播路径上的尾波Q_C(f)值;拟合Q_C(f)值与频率f之间的关系,分析了排泥库区域地震波衰减的时空特征。根据信噪比及计算要求,从近场7个台站的记录中挑选出273条三分向记录,计算尾波衰减参数,得到尾波Q_C(f)与频率f的关系为:Q(f)=(69.07±40.09)f~(0.90±0.23)。结果表明,本区域为低衰减区域,库区Q值相对较高,地震波衰减较慢,且Q值对频率的依赖性不强,研究区介质非均匀性程度低,介质较为稳定。     

Performance of detrending models of crop yield risk assessment: evaluation on real and hypothetical yield data

Detrending is a widely used technique for obtaining stationary time series data in residual analysis and risk assessment. The technique is frequently applied in crop yield risk assessment and insurance ratings. Although several trend models have been proposed in the literature, whether these models achieve consistent detrending results and successfully extract the true yield trends is rarely discussed. In the present article, crop insurance pricing is evaluated by different trend models using real and historical yield data, and hypothetical yield data generated by Monte Carlo simulations. Applied to real historical data, the linear, loglinear, autoregressive integrated moving average trend models produce different risk assessment results. The differences among the model outputs are statistically significant. The largest deviation in the county crop assessment reaches 6–8 %, substantially larger than the present countrywide gross premium rate of 5–7 %. In performance tests on simulated yield trends, popular detrending methods based on smoothing techniques proved overall superior to linear, loglinear, and integrated autoregression models. The best performances were yielded by the moving average and robust locally weighted regression models.     

景泰M_S4.7地震前的定点形变异常

2014年11月15日,在甘肃省白银市景泰县发生MS4.7地震,震源深度10km。在震中附近200km以内,甘肃省地震局共安装架设有14台各类形变观测仪器。本文通过对这些形变观测仪产出的分钟值观测资料做小波分析发现,在地震前1个月内共有11台(套)形变观测仪记录到了异常变化。其中:SSY、TJ、DSQ、SSQ型观测仪记录到异常的同步性非常好;CZB型观测仪记录到的异常比较乱,没有固定的规律。通过对这些异常变化的总结能够为地震预测提供一定的判断依据。     

Wave Propagation Modeling and Amplitude-Variation-with-Offset Response in a Fractured Coalbed

Coalbed methane can be detected employing the amplitudevariation-with-offset technique. However, there are two issues in applying this technique to a coalbed: strong azimuthal anisotropy resulting from high-density fractures, and the seismic response being composed of many or several individual reflections within the coalbed. To overcome these difficulties, we present an exact solution for reflections in extensive dilatancy anisotropy media. First, we build a three-layer model and simulate the wave propagation in this model. Then we derive an exact P- and converted S-wave reflection coefficient equation based on boundary conditions. Finally, substituting given model parameters into the exact equation, we obtain the variation in the reflection coefficient with incidence angle. The results show that the fracture factors, wavelet frequency and thickness of the coalbed have different effects on the reflection coefficient. Furthermore, we create a synthetic seismogram by forward calculation, and the result fits well with results of the exact equation.     

川西新场气田上三叠统须二、须四段相对优质储层成因差异性分析

川西新场地区须家河组储层埋藏深度大、成岩作用复杂、致密化程度高,但在整体超致密背景下,局部仍发育较多的相对优质储层.相对优质储层在埋深较大的须二段,往往发育较多的原生孔隙,和相对次要的次生孔隙;而埋深较小的须四段储层,次生孔隙占绝对优势,原生孔隙发育较少.造成这一现象的主要原因是须二、须四段原生孔隙保存和次生孔隙发育机制上的差异.须二段储层中较多刚性颗粒的存在和较为发育的包膜绿泥石是原生孔隙得到较好保存的主要原因;而其较大的单砂层厚度和较少的泥岩发育则导致了有机酸性流体的注入量较少,长石溶蚀有限.须四段塑性岩屑含量明显较高,储层原生孔隙在压实作用下几乎消失殆尽,但较薄的单砂层厚度和较多泥岩的叠置发育使长石在有机酸性流体作用下得到了充分溶蚀;这是须四段储层次生孔隙相对发育、长石含量很低、同时还有自生高岭石沉淀的主要原因.     

Spatiotemporal variation and driving forces of reference evapotranspiration in Jing River Basin,northwest China

Evapotranspiration is an important component of the hydrological cycle, which integrates atmospheric demands and surface conditions. Research on spatial and temporal variations of reference evapotranspiration (ET_o) enables understanding of climate change and its effects on hydrological processes and water resources. In this study, ET_o was estimated by the FAO‐56 Penman–Monteith method in the Jing River Basin in China, based on daily data from 37 meteorological stations from 1960 to 2005. ET_o trends were detected by the Mann–Kendall test in annual, seasonal, and monthly timescales. Sensitivity coefficients were used to examine the contribution of important meteorological variables to ET_o. The influence of agricultural activities, especially irrigation on ET_o was also analyzed. We found that ET_o showed a decreasing trend in most of the basin in all seasons, except for autumn, which showed an increasing trend. Mean maximum temperature was generally the most sensitive parameter for ET_o, followed by relative humidity, solar radiation, mean minimum temperature, and wind speed. Wind speed was the most dominant factor for the declining trend in ET_o. The more significant decrease in ET_o for agricultural and irrigation stations was mainly because of the more significant decrease in wind speed and sunshine hours, a mitigation in climate warming, and more significant increase in relative humidity compared with natural stations and non‐irrigation stations. Changes in ET_o and the sensitivity coefficient of meteorological variables in relation to ET_o were also affected by topography. Better understanding of ET_o response to climate change will enable efficient use of agricultural production and water resources, which could improve the ecological environment in Jing River Basin. Copyright © 2015 John Wiley & Sons, Ltd.     

陕北黄土丘陵沟壑区农户气候变化的适应行为及影响因素分析

从农户个体微观视角,研究农业的活动主体--农户的气候变化适应行为。选择陕北黄土丘陵沟壑区,采用问卷调查和半结构式访谈相结合的方法研究农户气候变化感知与适应行为,运用二元逻辑回归模型分析影响该地区农户适应行为的因素。结果表明：农户对气候变化趋势感知比较一致,认为近5 年夏季和冬季气温升高,降水减少,但与实际观测存在一定偏差。农户应对气候变化采取适应行为的比重并不高,只有57.8% 的农户表示采取了相应的措施来应对气候变化。农户适应行为受气候变化感知的影响,此外,家庭社会经济属性对农户采取适应行为的概率影响显著,而性别、年龄、文化程度等人口属性因素与农户采取适应行为的概率关系不大。     

Early Cretaceous porphyry copper mineralization in Northeast China: the Changfagou example

The Changfagou Cu deposit is a newly discovered porphyry deposit located in the southern Jilin Province of Northeastern China, on the northeastern margin of the North China Craton. To better understand the formation of the Cu deposit, we report the zircon U–Pb and molybdenite Re–Os dating, and Sr-, Nd-, and Hf- isotopic data of the granite porphyry. LA-ICP-MS dating of zircon grains from two mineral zones in the granite porphyry yield ages of 115.7 ± 0.8 and 115.3 ± 0.6 Ma, which is interpreted as the emplacement age of the granite porphyry. The molybdenite Re–Os model ages of 112.5 to 113.8 Ma, an isochron age of 113.3 ± 1.3 Ma, and a weighted mean model age of 113.0 ± 0.7 Ma, which represents the age of the Cu mineralization quite well. The Changfagou granite porphyry samples lack amphibole and muscovite, and are compositionally characterized by high SiO₂, high Na₂O+K₂O, and low P₂O₅, enriched in some Rb, Th, U, and Pb, and depleted in Nb, Ta, Ti, P, and Eu. Mineralogical and geochemical features suggest that the Changfagou granite porphyry samples are slightly peraluminous and are of highly fractionated I-type granitoids. The granitic rocks also have relatively high (⁸⁷Sr/⁸⁶Sr)_i (0.71199 to 0. 71422), and both low εNd(t) (?14.56 to ?13.19) and εHf(t) values (?14.916 to ?8.644), which suggest that Changfagou granite porphyry are derived from mixed sources of crustal and mantle, and diagenesis and mineralization were possibly related to the switch in subduction direction of the Palaeo-Pacific Plate in the late phase of Early Cretaceous.     

Detecting hotspots of urban residents’ behaviours based on spatio-temporal clustering techniques

Hotspots are regions where the number of spatial objects is obviously high within the time intervals. As the behaviours of urban residents are considered as a typical kind of spatio-temporal pattern, the detection of hotspots of urban residents’ behaviours appears necessary, since important information might be discovered in hotspots. In this paper, we propose an approach to detect the spatio-temporal hotspots of urban residents’ behaviours. This approach is validated based on the GPS data of floating cars of a city in southern China. The approach consists of four main steps: first, the effective spatio-temporal trajectories and the important characteristic points contained in each trajectory are extracted from the GPS data; second, the spatio-temporal clusters are generated by clustering the characteristic points based on a kernel density estimation algorithm; third, the spatio-temporal hotspots are detected by filtering the spatio-temporal clusters with high densities; last, the detected hotspots are analysed and interpreted. The results show that the proposed approach is effective and useful in detecting hotspots of urban residents’ behaviours.