东北地震区b值和地震年平均发生率的统计分析

震级和频度关系式中的b值和地震年平均发生率是表征一个地区地震活动性的重要参数，也是地震危险性概率分析中不可缺少的计算参数。本文根据当前的地震目录，利用数理统计的方法给出了东北地震区的b值和地震的年平均发生率。该研究成果对在本区开展地震安全性评价和地震预报具有重要的参考价值。     

趋势面方法圈定龙关地区化探异常及应用效果评价

以河北省张家口龙关地区1∶20万水系沉积物数据为例,采用趋势面分析方法,用不同次数的多项式拟合地球化学元素的整体分布趋势,识别出局部异常,圈定元素异常分布图。在与传统平均方法对比研究后,界定Pb、Zn、Ag、Au、Cu的趋势面法应用效果,为相似区域提供参考。     

利用地震属性进行砂岩储层横向预测

地震属性分析技术一直是地震特殊处理和地质解释的主要研究内容。随着相关理论的发展,地震属性分析技术已经应用到油气勘探开发的各个阶段。S盆地南部处于勘探开发的前期,具有井少、二维地震测网较稀、储层预测难的特点。由于沉积地层的变化能引起地震波在动力学和运动学上的相应变化,因此利用地震属性能较好地进行储层特征的定性研究,即通过地震多种属性分析,进行研究区内砂岩储层横向预测。其研究技术路线实际上为先找储层,再进行初步油气检测,最后进行勘探目标优选。根据这个技术路线,地震属性的研究则相应地以三个方面的分析为主:即利用振幅属性来寻找砂体富集区,利用有效带宽判断砂层的均质性,再利用频率属性判断其含气性。地震属性分析方法的应用在早期天然气勘探开发具有可以推广的普遍意义。     

Indices for assessing the prediction bounds of hydrological models and application by generalised likelihood uncertainty estimation / Indices pour évaluer les bornes de prévision de modèles hydrologiques et mise en œuvre pour une estimation d'incertitude par vraisemblance généralisée

Abstract

To reflect the uncertainties of a hydrological model in simulating and forecasting observed discharges according to rainfall inputs, the estimated result for each time step should not be just a point estimate (a single numerical value), but should be expressed as a prediction interval, i.e. a band defined by the prediction bounds of a particular confidence level α. How best to assess the quality of the prediction bounds thus becomes very important for understanding the modelling uncertainty in a comprehensive and objective way. This paper focuses on seven indices for characterizing the prediction bounds from different perspectives. For the three case-study catchments presented, these indices are calculated for the prediction bounds generated by the generalized likelihood uncertainty estimation (GLUE) method for various threshold values. In addition, the relationships among these indices are investigated, particularly that of the containing ratio (CR) to the other indices. In this context, three main findings are obtained for the prediction bounds estimated by GLUE. Firstly, both the average band-width and the average relative band-width are seen to have very strong linear correlations with the CR index. Secondly, a high CR value, a narrow band-width, and a high degree of symmetry with respect to the observed hydrograph, all of which are clearly desirable properties of the prediction bounds estimated by the uncertainty assessment methods, cannot all be achieved simultaneously. Thirdly, for the prediction bounds considered, the higher CR values and the higher degrees of symmetry with respect to the observed hydrograph are found to be associated with both the larger band-widths and the larger deviation amplitudes. It is recommended that a set of different indices, such as those considered in this study, be employed for assessing and comparing the prediction bounds in a more comprehensive and objective way.     

Improving the performance of data-driven techniques through data pre-processing for modelling daily reservoir inflow

Abstract

The effect of data pre-processing while developing artificial intelligence (AI) -based data-driven techniques, such as artificial neural networks (ANN), model trees (MT) and linear genetic programming (LGP), is studied for Pawana Reservoir in Maharashtra, India. The daily one-step-ahead inflow forecasts are compared with flows generated from a univariate autoregressive integrated moving average (ARIMA) model. For the full-year data series, a large error is found mainly due to the occurrence of zero values, since the reservoir is located in an intermittent river. Hence, all the techniques are evaluated using two data series: 18 years of daily full-year inflow data (from 1 January to 31 December); and 18 years of daily monsoon season inflow data (from 1 June to 31 October) to take into account the intermittent nature of the data. The relevant range of inputs for each category is selected based on autocorrelation and partial autocorrelation analyses of the inflow series. Conventional pre-processing methods, such as transformation and/or normalization of data, do not perform well because of the large variation in magnitudes, as well as the many zero values (65% of the full-year data series). Therefore, the input data are pre-processed into un-weighted moving average (MA) series of 3 days, 5 days and 7 days. The 3-day MA series performs better, maintaining the peak inflow pattern as in the actual data series, while the coarser-scale (5-day and 7-day) MA series reduce the peak inflow pattern, leading to more errors in peak inflow prediction. The results indicate that AI methods are powerful tools for modelling the daily flow time series with appropriate data pre-processing, in spite of the presence of many zero values. The time-lagged recurrent network (TLRN) ANN modelling technique applied in this study maps the inflow forecasting in a better way than the standard multilayer perceptron (MLP) neural networks, especially in the case of the seasonal data series. The MT technique performs equally well for low and medium inflows, but fails to predict the peak inflows. However, LGP outperforms the other AI models, and also the ARIMA model, for all inflow magnitudes. In the LGP model, the daily full-year data series with more zero inflow values performs better than the daily seasonal models.

Citation Jothiprakash, V. & Kote, A. S. (2011) Improving the performance of data-driven techniques through data pre-processing for modelling daily reservoir inflow. Hydrol. Sci. J. 56(1), 168–186.     

用对称映射ARMA模型的零极点研究子波相位对反射系数序列反演的影响

为研究地震子波相位对反射系数序列反演的影响,在自回归滑动平均(ARMA)模型描述子波的基础上,提出采用z域对称映射ARMA模型零极点的方法构造了一系列相同振幅谱、不同相位谱的地震子波,并结合谱除法对人工合成地震记录进行反射系数序列反演.理论分析表明,子波相位估计不准时反射系数序列反演结果中残留一个纯相位滤波器,该纯相位滤波器的相位谱为真实子波和构造子波的相位谱之差.采用丰度和变分作为评价方法,在反演结果中确定出真实的或准确的反射系数序列.仿真实验和实际数据处理结果也验证了子波相位对反射系数序列反演的影响规律和评价方法的有效性,为进一步提高反射系数序列反演结果精度指明了研究方向.     

Sea ice thickness measurement in spring season in Bothnian Bay using an electromagnetic induction instrument

As an important component of the cryosphere,sea ice is very sensitive to the climate change.The study of the sea ice physics needs accurate sea ice thickness.This paper presents an electromagnetic-induction(EM) technique which can be used to measure the sea ice thickness distribution efficiently,and the successful application in Bothnian Bay.Based on the electromagnetic field theory and the electrical properties of sea ice and seawater,EM technique can detect the distance between the instrument and the ice/water interface accurately,than the sea ice thickness is obtained.Contrastive analysis of the apparent conductivity data obtained by EM and the value of drill-hole at same positions allows a construction of a transformable formula of the apparent conductivity to sea ice thickness.The verification of the sea ice thickness calculated by this formula indicates that EM technique is able to get reliable sea ice thickness with average relative error of only 12%.The statistic of all ice thickness profiles shows that the level ice distribution in Bothnian Bay was 0.4-0.6 m.     

陕甘宁青地区的地形变特征与强震活动

分析了陕甘宁青地区的地壳形变特征及其与强震的关系．结果表明：(1)地壳形变特征存在时空差异性。不同地区地形变活动强弱与其至主要边界断裂带的距离存在相关性，主要边界断裂带附近地区相对活动强烈，远处则减弱。(2)不同时期各断层地形变活动强弱不同，既和构造应力场的变化有关，又与地震活动关系密切；断层垂直形变的逆继承性构造运动的活动时期远小于继承性构造运动的活动时期，且不同区域地壳构造运动发生转折的时间不尽相同，同时断层形变前兆异常亦存在时空差异性。(3)多场地、大范围的断层活动异常可能与强震活动相呼应。     

A change detection algorithm for terrain surface moisture mapping based on multi‐year passive microwave remote sensing (Examples of SSM/I and TMI Channels)

As an indication of the surface polarized emission, a polarization index (PI) of microwave radiance from the terrain surface (half‐space of canopy‐soil land) is derived from the radiative transfer model. This PI separates the radiance effects of the canopy‐soil moisture and interference from surface roughness and atmosphere, and is suitable to describe the change of terrain surface moisture, especially for extreme drought or flood conditions. As an example, the statistics of the monthly average < PI > from 6 years' data of the Defense Meteorological Satellite Program (DMSP) SSM/I observations at the lowest frequency 19·35 GHz channel as available are applied for the demonstration of the surface moisture status over a large and heterogeneous territory such as China. The deviation of the PI data at the same month from the average < PI > , i.e. Δ_nPI(≡(PI? < PI>)/ < PI>), gives prominence to focusing moisture variation of terrain surface, and its anomaly shows possible drought or flood occurrence in extreme conditions. The Δ_nPI mapping is validated by the typical examples of the drought in China's Shanxi area in May 2001 and the flood around China's Yangtze River in August 1998, respectively. Our approach is recommended for lower frequency channels to minimize the influence from vegetation canopy for future applications (such as the channels of the Advanced Microwave Scanning Radiometer [AMSR‐E] launched in May 2002 and microwave imaging radiometer of China's Fengyun satellite series). When the monthly < PI > and the ground truth of average volumetric moisture < m_v > of the region are correctly evaluated, it is tractable to retrieve the soil land surface moisture by using the PI data at the same month and the same region without much knowledge of surface roughness, vegetation canopy and other factors. As an example, the retrieval of m_v is favourably tested by using the Tropical Rainfall Measuring Mission (TRMM) Tropical Microwave Imager (TMI) data. Copyright © 2007 John Wiley & Sons, Ltd.     

城市地铁控制网稳定性分析及应用

城市地铁控制网是城市地铁工程的基准,是工程施工质量安全的保障,其稳定与否直接影响到联系测量及贯通误差的计算。本文研究了控制网的稳定性分析方法,结合北京地铁五号线某段控制网,利用两期平面观测数据对控制网进行稳定性分析,保证了隧道的安全贯通。