Wavelet regression model as an alternative to neural networks for monthly streamflow forecasting

The accuracy of the wavelet regression (WR) model in monthly streamflow forecasting is investigated in the study. The WR model is improved combining the two methods—the discrete wavelet transform (DWT) model and the linear regression (LR) model—for 1‐month‐ahead streamflow forecasting. In the first part of the study, the results of the WR model are compared with those of the single LR model. Monthly flow data from two stations, Gerdelli Station on Canakdere River and Isakoy Station on Goksudere River, in Eastern Black Sea region of Turkey are used in the study. The comparison results reveal that the WR model could increase the forecast accuracy of the LR model. In the second part of the study, the accuracy of the WR model is compared with those of the artificial neural networks (ANN) and auto‐regressive (AR) models. On the basis of the results, the WR is found to be better than the ANN and AR models in monthly streamflow forecasting. Copyright © 2009 John Wiley & Sons, Ltd.     

曲率模态小波法用于网壳结构损伤的识别和定位

工程结构损伤的识别与定位研究以往主要针对梁、框架等结构形式,根据大跨度空间结构杆件和节点繁多等特点,提出用曲率模态和小波混合方法对空间结构的损伤进行识别和定位.以跨度100 m的Schwedler网壳结构损伤前、后的曲率模态作为标识量,分别通过离散和连续小波变换,判断网壳结构有无损伤和损伤位置,统计了小波系数差与结构损伤的图形关系,计算了各种损伤工况下该方法判断损伤的准确程度.结果发现基于曲率模态和小波方法的大跨度网壳结构损伤定位精度很高,充分证明该方法对此类结构损伤定位具有有效性和实用性.     

Analysis of tracer tomography using temporal moments of tracer breakthrough curves

Hydraulic/partitioning tracer tomography (HPTT) was recently developed by Yeh and Zhu [Yeh T-CJ, Zhu J. Hydraulic/partitioning tracer tomography for characterization of dense nonaqueous phase liquid source zones, Water Resour Res 2007;43:W06435. doi:10.1029/2006WR004877.] for estimating spatial distribution of dense nonaqueous phase liquids (DNAPLs) in the subsurface. Since discrete tracer concentration data are directly utilized for the estimation of DNAPLs, this approach solves the hyperbolic convection–dispersion equation. Solution to the convection–dispersion equation however demands fine temporal and spatial discretization, resulting in high computational cost for an HPTT analysis. In this work, we use temporal moments of tracer breakthrough curves instead of discrete concentration data to estimate DNAPL distribution. This approach solves time independent partial differential equations of the temporal moments, and therefore avoids solving the convection–dispersion equation using a time marching scheme, resulting in a dramatic reduction of computational cost. To reduce numerical oscillations associated with convection dominated transport problems such as in inter-well tracer tests, the approach uses a finite element solver adopting the streamline upwind Petrov–Galerkin method to calculate moments and sensitivities. We test the temporal moment approach through numerical simulations. Comparing the computational costs between utilizing moments and discrete concentrations, we find that temporal moments significantly reduce the computation time. We also find that tracer moment data collected through a tomographic survey alone are able to yield reasonable estimates of hydraulic conductivity, as indicated by a correlation of 0.588 between estimated and true hydraulic conductivity fields in the synthetic case study.     

A non-parametric automatic blending methodology to estimate rainfall fields from rain gauge and radar data

Quantitative estimation of rainfall fields has been a crucial objective from early studies of the hydrological applications of weather radar. Previous studies have suggested that flow estimations are improved when radar and rain gauge data are combined to estimate input rainfall fields. This paper reports new research carried out in this field. Classical approaches for the selection and fitting of a theoretical correlogram (or semivariogram) model (needed to apply geostatistical estimators) are avoided in this study. Instead, a non-parametric technique based on FFT is used to obtain two-dimensional positive-definite correlograms directly from radar observations, dealing with both the natural anisotropy and the temporal variation of the spatial structure of the rainfall in the estimated fields. Because these correlation maps can be automatically obtained at each time step of a given rainfall event, this technique might easily be used in operational (real-time) applications. This paper describes the development of the non-parametric estimator exploiting the advantages of FFT for the automatic computation of correlograms and provides examples of its application on a case study using six rainfall events. This methodology is applied to three different alternatives to incorporate the radar information (as a secondary variable), and a comparison of performances is provided. In particular, their ability to reproduce in estimated rainfall fields (i) the rain gauge observations (in a cross-validation analysis) and (ii) the spatial patterns of radar fields are analyzed. Results seem to indicate that the methodology of kriging with external drift [KED], in combination with the technique of automatically computing 2-D spatial correlograms, provides merged rainfall fields with good agreement with rain gauges and with the most accurate approach to the spatial tendencies observed in the radar rainfall fields, when compared with other alternatives analyzed.     

珠江三角洲城市群震害损失预测初步研究

城市群是经济快速发展的产物。已有的震例表明城市群震害比单个城市的震害更为复杂、严重,对社会的影响更为巨大。阐述了珠江三角洲城市群的发展现状及其地震活动性,分析了城市群的地震灾害特点．并利用现有的震害评估模型及基础数据对珠江三角洲城市群进行震害损失模拟．结果证明城市群震害损失较非城市群更严重．并提出了防御城市群地震灾害的措施、     

ENSO signals and their spatial-temporal variation characteristics recorded by the sea-level changes in the northwest Pacific margin during 1965–2005

Sea-level is closely linked to the Earth’s climate and its change is important as a metric for global and regional climate change. Identifying, extracting, and revealing such information through detailed analysis is the prerequisite for understanding the mechanisms of sea-level change. The monthly- average tide-change records reported and examined in this paper are from 10 tide gauge stations distributed in the northwest margin of the Pacific Ocean, registered during the period 1965-2005. In particular, we have utilized the Second Order Blind Identification (SOBI) method to identify and the Empirical Mode Decomposition (EMD) method to extract the El Niño-Southern Oscillation (ENSO) signals imprinted in those tide gauge records; and subsequently, we have investigated the spatial-temporal characteristics of the extracted ENSO signals using wavelet analysis methods. The following results are obtained: (1) the ENSO events recorded by each tide gauge series are of different types and intensity, which show considerable temporal-spatial variation characteristics, with sea-level responses to ENSO signals remarkably stronger in low latitude areas than in medium-high latitude areas; (2) due to the influences of ocean currents, topographical conditions, and other factors, there exist variations in the type of relationship between the sea-level changes and the recorded ENSO events at different latitudes; (3) sea-level changes can also denote scale-variation characteristics of ENSO events, and particularly, since 1980s, all the tide gauges located south of Kanmen show intense responses to ENSO and the timescale of ENSO events extended gradually from around 4 years to 2–8 years, reflecting variations in the intensity and frequency of ENSO events; and (4) reverse changes of certain scale were noted before and after strong ENSO events recorded by sea-level changes, supporting the research findings about the interaction (mutual coupling and superimposition) between the probability of occurrence of strong ENSO events and their time scale.     

ENSO signals and their spatial-temporal variation characteristics recorded by the sea-level changes in the northwest Pacific margin during 1965-2005

Sea-level is closely linked to the Earth's climate and its change is important as a metric for global and regional climate change. Identifying, extracting, and revealing such information through detailed analysis is the prerequisite for understanding the mechanisms of sea-level change. The monthlyaverage tide-change records reported and examined in this paper are from 10 tide gauge stations distributed in the northwest margin of the Pacific Ocean, registered during the period 1965-2005. In particular, we ha...     

基于Curvelet变换的地震资料信噪分离技术

在地震资料中,噪声干扰严重影响了有效信号的提取,为此必须进行信噪分离处理.本文提出一种基于Curvelet变换和KL变换相结合的软硬阈值折衷处理方法.首先对地震数据进行Curvelet变换,然后对各尺度系数选取适当阈值压制噪声干扰,再利用KL变换提取数据中的相干有效信号,最后重构得到去噪后的记录.经合成记录和实际地震资料处理实验证明,该方法与小波变换法相比较,更能有效进行信噪分离,提高地震剖面信噪比和分辨率.     

基于探地雷达信号处理的小波基选取研究

针对探地雷达信号处理和分析时小波基选取存在的问题,本文在分析探地雷达信号特点的基础上,首先从理论上讨论小波基的选取准则,然后再从实验角度进行对比、判别,认为在进行小波分解和重构时应该分别选择不同的小波基函数进行处理,这样可以保证重构信号的精确度,增强对信号的处理能力,从而也突破了以往分解与重构时都采用同一个小波基进行处理的做法.最后通过实际资料的处理,指出bior2.6小波基在进行雷达信号处理时效果最佳,不仅去噪彻底,而且能够保留有效信号的高频部分,提高信号的分辨率和信噪比,为后续解释工作打好了基础.     

参数化地震子波估计模型定阶方法研究综述

参数化模型地震子波提取中模型阶数的确定对子波提取的精度至关重要,笔者针对因果地震子波MA、ARMA模型,总结了目前比较成熟的四类定阶方法：相关分析法、信息量准则法、线性代数法及基于优化算法的模型定阶方法,分析比较发现这些算法都存在不同程度的缺陷,只能在各自的适用范围内得到较好的定阶结果,针对算法在子波建模应用中的不足提出了改进建议;同时分析比较了基于高阶累积量的非因果系统模型定阶的各种方法,并对非因果地震子波模型定阶进行了展望.