河北及邻区地震烈度衰减关系研究

地震震动的衰减关系在地震区划和工程场地的安全性评估过程中是不可或缺的。利用河北及周边区域历史地震的等震线资料,运用统计回归的分析方法,得到统计回归方程及地震烈度衰减关系,与其他烈度衰减关系进行对比分析,并与地震应急指挥技术系统软件及地震烈度分布资料进行对比,从而得到适用于河北及周边地区的地震烈度衰减关系。     

基于线性回归分析的主余震相关关系

预防强震后可能发生的余震对于保护灾区安全具有重要意义。为了对余震进行一定误差水平的快速判定,对主震与余震之间的关系进行分析。选取1970年1月1日—2009年9月30日全球范围5—10级地震进行预处理,采用基于最小二乘法的线性回归方法,对主震震级与最大余震震级关联关系、主震视应力与最大余震震级关联关系进行分析,并进行结果可视化。结果表明,主震与最大余震的震级存在一定线性关系,可为主震后在一定范围内对最大余震的快速判定提供一定参考。     

Space–time forecasting of groundwater level using a hybrid soft computing model

Forecasting of space–time groundwater level is important for sparsely monitored regions. Time series analysis using soft computing tools is powerful in temporal data analysis. Classical geostatistical methods provide the best estimates of spatial data. In the present work a hybrid framework for space–time groundwater level forecasting is proposed by combining a soft computing tool and a geostatistical model. Three time series forecasting models: artificial neural network, least square support vector machine and genetic programming (GP), are individually combined with the geostatistical ordinary kriging model. The experimental variogram thus obtained fits a linear combination of a nugget effect model and a power model. The efficacy of the space–time models was decided on both visual interpretation (spatial maps) and calculated error statistics. It was found that the GP–kriging space–time model gave the most satisfactory results in terms of average absolute relative error, root mean square error, normalized mean bias error and normalized root mean square error.     

Improvement and comparative assessment of a hydrological modelling approach on 20 catchments of various sizes under different climate conditions

Assessing water resources is an important issue, especially in the context of climatic changes. Although numerous hydrological models exist, new approaches are still under investigation. In this context, we propose a modelling approach based on the physical principle of least action. We present new hypotheses to develop the model further, to widen its application. The improved version of the model MODHYPMA was applied on 20 sub-catchments in Africa and the USA. Its performance was compared with two well-known lumped conceptual models, GR4J and HBV. The model could be successfully calibrated and validated. In calibration, GR4J performed better, while other models had similar performance. In validation, MODHYPMA and GR4J performed similarly and better than HBV. The parameter λ has medium sensitivity while parameters λ and TX have low sensitivity. The parameter uncertainty for MODHYPMA, analysed using the GLUE methodology, was higher during high flows but with good p and r factors.

EDITOR D. Koutsoyiannis ASSOCIATE EDITOR not assigned     

Iteratively re‐weighted and refined least squares algorithm for robust inversion of geophysical data

A robust metric of data misfit such as the ?₁‐norm is required for geophysical parameter estimation when the data are contaminated by erratic noise. Recently, the iteratively re‐weighted and refined least‐squares algorithm was introduced for efficient solution of geophysical inverse problems in the presence of additive Gaussian noise in the data. We extend the algorithm in two practically important directions to make it applicable to data with non‐Gaussian noise and to make its regularisation parameter tuning more efficient and automatic. The regularisation parameter in iteratively reweighted and refined least‐squares algorithm varies with iteration, allowing the efficient solution of constrained problems. A technique is proposed based on the secant method for root finding to concentrate on finding a solution that satisfies the constraint, either fitting to a target misfit (if a bound on the noise is available) or having a target size (if a bound on the solution is available). This technique leads to an automatic update of the regularisation parameter at each and every iteration. We further propose a simple and efficient scheme that tunes the regularisation parameter without requiring target bounds. This is of great importance for the field data inversion where there is no information about the size of the noise and the solution. Numerical examples from non‐stationary seismic deconvolution and velocity‐stack inversion show that the proposed algorithm is efficient, stable, and robust and outperforms the conventional and state‐of‐the‐art methods.     

Prestack amplitude versus angle inversion for Young's modulus and Poisson's ratio based on the exact Zoeppritz equations

Elastic parameters such as Young's modulus, Poisson's ratio, and density are very important characteristic parameters that are required to properly characterise shale gas reservoir rock brittleness, evaluate gas characteristics of reservoirs, and directly interpret lithology and oil‐bearing properties. Therefore, it is significant to obtain accurate information of these elastic parameters. Conventionally, they are indirectly calculated by the rock physics method or estimated by approximate formula inversion. The cumulative errors caused by the indirect calculation and low calculation accuracy of the approximate Zoeppritz equations make accurate estimation of Young's modulus, Poisson's ratio, and density difficult in the conventional method. In this paper, based on the assumption of isotropy, we perform several substitutions to convert the Zoeppritz equations from the classical form to a new form containing the chosen elastic constants of Young's modulus, Poisson's ratio, and density. The inversion objective function is then constructed by utilising Bayesian theory. Meanwhile, the Cauchy distribution is introduced as a priori information. We then combine the idea of generalised linear inversion with an iterative reweighed least squares algorithm in order to solve the problem. Finally, we obtain the iterative updating formula of the three elastic parameters and achieve the direct inversion of these elastic parameters based on the exact Zoeppritz equations. Both synthetic and field data examples show that the new method is not only able to obtain the two elastic parameters of Young's modulus and Poisson's ratio stably and reasonably from prestack seismic data but also able to provide an accurate estimation of density information, which demonstrates the feasibility and effectiveness of the proposed method. The proposed method offers an efficient seismic method to identify a “sweet spot” within a shale gas reservoir.     

Weighting the impacts to stream water quality in small basins devoted to forage crops,dairy and beef cow production

Livestock for beef and milk production are important economic activities worldwide. These require intensive cultures of pastures and forages, with the consequent impacts on water quality in downstream rivers and reservoirs. Monthly temporal variation of nutrients and water quality were assessed along one year at basin scale (basin area <3500 ha). Several indicators of farming intensity (number of dairy cows and beef cows, percentage of area devoted to crops) and management practices (effluent treatment, fertilizer application) were related to the export of nutrients and sediments from the basins and with the water quality of receiving streams using partial least square regression analysis (PLS). According to PLS analysis, the most relevant variables to explain water quality degradation and high export coefficients of nutrients and sediments, were the percentage of basin area dedicated to crop activities and the density of dairy cows without effluent treatment. Beef and dairy cows had an important local impact on stream water without animal access restrictions. We also propose some hypotheses regarding the transport pathways of sediments and nutrients to streams. Our results demonstrate the urgent need to implement best management practices at the farm scale within each basin, focusing on: adequate phosphorus fertilization, implementation of a complete dairy effluent treatment system and animal restriction to fluvial channels.     

古登堡-里希特定律中的b值统计样本量研究

b值是研究地震活动的重要指标,其广泛应用于地震危险性分析和地震预测研究之中,与实际资料的完整性、样本量的大小、计算方法等因素有着重要的关系。常见的b值计算方法有最小二乘法和最大似然法,样本量的大小对这2种方法影响很大。本文利用蒙特卡罗模拟地震目录和汾渭地震带实际目录作为样本,从中抽取不同大小的样本量进行计算,研究不同样本量下这2种方法计算得到的b值与设定值或真实值之间的差别。结果表明,最小二乘法需要的最低样本量为1000,最大似然法为200;当样本量达不到要求时,计算出的b值是不可靠的;由于对样本量的要求不同,前者适用于计算区域的整体b值,而后者在研究某区域b值在时间轴上的变化方面更有优势。本研究为确定2种b值计算方法对样本量的最低要求提供了参考依据。     

三原则整体最小二乘用于平面自由网平差计算

文中在平面网平差中应用整体最小二乘理念.在最小二乘模型中,为了消除观测方程系数误差和未知参数系统误差,加入系数改正数和参数改正数,并提出三原则整体最小二乘模型.研究平差两大步骤,用最小二乘多次改用"参考点组"而选出w个稳定点;用最小二乘多次改用"近似坐标"而消除系数误差和参数系统误差.三原则整体最小二乘适用于平面自由网...     

渤海湾多源重力数据的自适应融合处理

针对信号与误差的方差分量不一致问题及协方差阵病态性问题,分别在多源重力数据最小二乘配置融合过程中引入方差分量估计方法及Tikhonov正则化方法,得到基于方差分量估计的正则化配置法,实际算例结果表明,利用该方法能够有效削弱上述问题,减小重力数据融合结果的系统差,提高数据融合的精度及可靠性。