体波走时层析成像方法及其在中国壳幔结构研究中的应用评述

文中对地震体波走时层析成像技术近30年的发展进行回顾和评述,并对该方法所存在的问题进行了分析和探讨以及给出应对策略。在壳幔速度结构的横向不均匀性、强震发生的深部构造环境、活火山区的深部结构和起源,以及造山带、板块碰撞带区域深部结构等4个方面对应用地震层析成像技术所取得的主要成果做了分类总结和探讨。研究证明,利用地震层析成像技术所获得的高分辨率地球内部结构为探索岩石圈的演化和板块运动规律及地震、火山活动发生的深部构造环境等提供了十分重要的科学依据。     

中缅毗邻区金腊Pb-Zn-Ag多金属矿田花岗岩锆石U-Pb定年与地球化学特征

位于中缅毗邻区的金腊铅锌银多金属矿田大地构造上处于保山—掸泰地块东缘,勐统—耿马—西盟元古宙—古生代被动大陆边缘活动带南段。与矿化有关的花岗岩(简称金腊花岗岩)包括老厂似斑状角闪二长花岗岩、勐林山似斑状黑云二长花岗岩和南腊碱长花岗斑岩。文中系统研究了上述岩石的主量元素、稀土元素、微量元素、成矿元素和锆石U-Pb同位素年龄等特征,从构造岩浆演化的角度,探讨上述岩体之间内在联系、成因演化以及与成矿的关系:(1)在金腊花岗岩三种岩石类型中,老厂似斑状角闪二长花岗岩和勐林山似斑状黑云二长花岗岩的锆石同位素U-Pb年龄皆为(45±1)Ma,形成于岩浆结晶分异早期阶段的深成环境,而南腊碱长花岗斑岩的锆石同位素U-Pb年龄为(43.41±0.78)Ma,形成于岩浆结晶分异晚期阶段的浅成环境。(2)主量元素和微量元素(稀土元素和某些微量元素(Zr/Hf、Nb/Ta、Rb/Sr、Rb/Ba、K/Rb、(Rb/Yb)N、Sr*、K*和Zr*)),结合U-Pb同位素定年研究表明,本区花岗岩形成于喜马拉雅同碰撞造山成矿作用末期局部拉张构造环境,并分别代表了构造岩浆演化过程中不同演化阶段岩浆分异结晶的产物。(3)上述三类花岗岩样品皆位于S型花岗岩区,但从老厂似斑状角闪二长花岗岩,勐林山似斑状黑云二长花岗岩,到南腊碱长花岗斑岩,样品分布逐渐远离"I"型花岗岩和"S"型花岗岩的分界线,这表明自老厂似斑状角闪二长花岗岩至勐林山似斑状黑云二长花岗岩,到南腊碱长花岗斑岩幔源组分逐渐减少。(4)相对中国花岗岩,南腊碱长花岗斑岩不仅更富集W、Cu、Bi、Sb、Mo、Sn、Ag、Pb和Au等成矿元素,而且还强烈富集F、B和As等矿化剂元素,因此,碱长花岗斑岩是最有成矿远景的岩体。     

Acquisition of Directional Parameters in Aerial Images Based on DEM Data

1　Extraction of the steep curve mapThe steep curve is defined as connection linefrom zero cross points which are produced fromthe convolution of Laplace ( LOG) filtration toDEM. Firstly, the elevation data from DEM areprocessed with LOG convolution and zero cross.The sampling formula is 2G(i,j) =12πσ6(r2 -2σ2)e-r2/2σ2 (1)where -M≤i≤M,-M≤j≤M,r2=i2+j2; M isthe filtration radius, nearly equaling to 5.1σ2; pre diction errorσis set to 4. Suppose that e[i,j] is asmall …     

Frequency analysis of climate extreme events in Zanjan, Iran

In this study, generalized extreme value distribution (GEV) and generalized Pareto distribution (GPD) were fitted to the maximum and minimum temperature, maximum wind speed, and maximum precipitation series of Zanjan. Maximum (minimum) daily and absolute annual observations of Zanjan station from 1961 to 2011 were used. The parameters of the distributions were estimated using the maximum likelihood estimation method. Quantiles corresponding to 2, 5, 10, 25, 50, and 100 years return periods were calculated. It was found that both candidate distributions fitted to extreme events series, were statistically reasonable. Most of the observations from 1961 to 2011 were found to fall within 1–10 years return period. Low extremal index (θ) values were found for excess maximum and minimum temperatures over a high threshold, indicating the occurrence of consecutively high peaks. For the purpose of filtering the dependent observations to obtain a set of approximately independent threshold excesses, a declustering method was performed, which separated the excesses into clusters, then the de-clustered peaks were fitted to the GPD. In both models, values of the shape parameters of extreme precipitation and extreme wind speed were close to zero. The shape parameter was less negative in the GPD than the GEV. This leads to significantly lower return period estimates for high extremes with the GPD model.     

Approximation approach to the SRM based on root decomposition in the simulation of spatially varying ground motions

The spectral representation method(SRM) is widely used to simulate spatially varying ground motions.This study focuses on the approximation approach to the SRM based on root decomposition,which can improve the efficiency of the simulation.The accuracy of the approximation approach may be affected by three factors: matrix for decomposition,distribution of frequency interpolation nodes and elements for interpolation.The influence of these factors on the accuracy of this approach is examined and the following conclusions are drawn.The SRM based on the root decomposition of the lagged coherency matrix exhibits greater accuracy than the SRM based on the root decomposition of the cross spectral matrix.The equal energy distribution of frequency interpolation nodes proposed in this study is more effective than the counter pith with an equal spacing.Elements for interpolation do not have much of an effect on the accuracy,so interpolation of the elements of the decomposed matrix is recommended because it is less complicated from a computational efficiency perspective.     

利用支持向量机和高斯过程回归测定水库诱发的地震(英文)

水库诱发地震震级(M)的预测是在地震工程中的一项重要任务。本文采用支持向量机(SVM)和高斯过程回归(GPR)模型根据水库的参数预测了水库诱发地震震级(M)。综合参数(E)和最大的水库深度(H)作为支持向量机和高斯过程回归模型的输入参数。我们给出一个方程确定水库诱发地震震级(M)。将本文开发的支持向量机和建立的高斯过程回归方法与人工神经网络(ANN)方法相比。结果表明,本文研发的支持向量机和高斯过程回归方法是预测水库诱发地震震级(M)的有效工具。     

Investigation of the groundwater modelling component of the Integrated Water Flow Model (IWFM)

ABSTRACT

The Integrated Water Flow Model (IWFM), developed by the California Department of Water Resources, is an integrated hydrological model that simulates key flow processes including groundwater flows, streamflow, stream–aquifer interactions, rainfall–runoff and infiltration. It also simulates the agricultural water demand as a function of soil, crop and climatic characteristics, as well as irrigation practices, and allows the user to meet these demands through pumping and stream diversions. This study investigates the modelling performance of the groundwater module of IWFM using several hypothetical test problems that cover a wide range of settings and boundary conditions, by comparing the simulation results with analytical solutions, field and laboratory observations, or with results from MODFLOW outputs. The comparisons demonstrate that IWFM is capable of simulating various hydrological processes reliably.

EDITOR M.C. Acreman; ASSOCIATE EDITOR A. Efstratiadis     

Pre-processing of data-driven river flow forecasting models by singular value decomposition (SVD) technique

ABSTRACT

An appropriate streamflow forecasting method is a prerequisite for implementation of efficient water resources management in the water-limited, arid regions that occupy much of Iran. In the current research, monthly streamflow forecasting was combined with three data-driven methods based on large input datasets involving 11 precipitation stations, a natural streamflow, and four climate indices through a long period. The major challenges of rainfall–runoff modelling are generally attributed to complex interacting processes, the large number of variables, and strong nonlinearity. The sensitivity of data-driven methods to the dimension of input/output datasets would be another challenge, so large datasets should be compressed into independently standardized principal components. In this study, three pre-processing techniques were applied: singular value decomposition (SVD) provided more efficient forecasts in comparison to principal component analysis (PCA) and average values of inputs in all networks. Among the data-driven methods, the multi-layer perceptron (MLP) with 1-month lag-time outperformed radial basis and fuzzy-based networks. In general, an increase in monthly lag-time of streamflow forecasting resulted in a decline in forecasting accuracy. The results reveal that SVD was highly effective in pre-processing of data-driven evaluations.     

Scale impacts on spatial variability in reference evapotranspiration

ABSTRACT

Evapotranspiration (ET) is one of the most important components in the hydrological cycle, and a key variable in hydrological modelling and water resources management. However, understanding the impacts of spatial variability in ET and the appropriate scale at which ET data should be incorporated into hydrological models, particularly at the regional scale, is often overlooked. This is in contrast to dealing with the spatial variability in rainfall data where existing guidance is widely available. This paper assesses the impacts of scale on the estimation of reference ET (ETo) by comparing data from individual weather stations against values derived from three national datasets, at varying resolutions. These include the UK Climate Impacts Programme 50 km climatology (UKCP₅₀), the UK Met Office 5 km climatology (UKMO₅) and the regional values published in the Agricultural Climate of England and Wales (ACEW). The national datasets were compared against the individual weather station data and the UKMO₅ was shown to provide the best estimate of ETo at a given site. The potential impacts on catchment modelling were then considered by mapping variance in ETo to show how geographical location and catchment size can have a major impact, with small lowland catchments having much higher variance than those with much larger areas or in the uplands. Some important implications for catchment hydrological modelling are highlighted.

Editor D. Koutsoyiannis; Associate editor L. Ruiz     

2.5-D Gravity/Magnetic Model Studies in Sahl El Qaa Area, Southwestern Sinai, Egypt

The 2.5-D gravity-magnetic models of the upper crustal structures of Sahl El Qaa Area, Southwestern Sinai were constructed along seven profiles, focusing on the uppermost crustal layers to a depth of 4–5 km. In addition separation filtering process; spectral analysis and trend analysis were used to investigate the Bouguer and total intensity aeromagnetic field maps qualitatively and quantitatively. The study showed that the regional structures consist of tilted blocks in the form of a major NW-synclinal feature with an axis dipping northward. This feature is dissected by the NE trending cross faults forming horsts, grabens and step-fault structures. The tilted blocks are controlled by a major normal fault system and are greatly modified in the dip regime from north to south. They show a regional NW dip regime in northern and southern parts, where the depth to the basement reaches about 2–3 km in the down dip. In the central portion, the basin is dipping steeply to the east, with maximum depths attaining about 4–5 km.