福建地区地下流体异常与中强地震福建地区地下流体异常与中强地震

在对福建的地下流体资料进行综合分析的基础上，提取了1990年以来闽台地区若干次中强地震的前兆异常信息，并对异常点的变化形态、时间、空间分布与地震活动特征进行了研究，初步掌握了闽台地区地震前地下流体中、短期或临震的前兆异常特征，并发现在不同的观测位置，将出现不同的地下流体前兆异常。     

新疆沙湾5.2级地震地下流体前兆异常特征的分析

列举了1996年1月9日新疆沙湾5．2级地震地下流体前兆观测的最新资料，总结了地震孕育由稳态进入非稳态过程中流体异常的特征。结果表明，地下流体前兆异常以中短期为主，主要集中分布在距震中200km范围内，异常形态和幅度复杂多样，并对这次地震的跟踪预测、前兆的可靠性问题进行了讨论。     

新疆沙湾5.2级地震地下水流体前兆异常特征的分析

列举了１９９６年１月９日新疆沙湾５．２级震地下流体前兆观测的最新资料，总结了地震孕育由稳态进行非稳态过程中流体异常的特征。结果表明，地下流体前兆异常以中短期为主，订集中分布在距震中２００ｋｍ范围内，异常形态和幅度复杂多样，并对这次地震的跟踪预测，前兆的可靠性问题进行了讨论。     

昆仑山口西8．1级地震前后青藏块体东北缘地下流体前兆特征

分析了昆仑山口西8．1级地震前后青藏块体东北缘地区地下流体前兆资料，研究了水化学、水物理前兆所表现的异常特征。认为在8．1级地震前，流体前兆的响应范围大，异常持续时间长，异常的同步性好；8．1级地震后，流体前兆出现大幅度调整，伴随着这一地区的一系列中强以上地震的连发，表明了青藏块体整体活动水平在逐步增强。通过对比青藏块体东北缘地区跨断层形变测量、重力和地磁等观测结果，对这种类型异常产生的物理机制进行了初步讨论。     

"九五"我国地震地下流体研究的主要科学进展

总结了“九五”以来我国在地震地下流体研究方面的主要科学进展，从流体前兆成因、异常识别与预报技术，流体的作用与前兆机理和观测技术等方面的研究进展进行了归纳论述。还阐述了地震地下流体研究的科学发展问题。     

地下流体对地震前兆作用的综述

地下流体及流体力普遍存在且对地震前兆产生作用。本文从前兆机理、实例等方面综述了地下流体及流体力(包括降水等产生的力)对地震前兆的作用,表明降水等产生的地下流体及流体力对地震前兆的作用不可忽略,无论是浅层地下流体还是深部地下流体均影响前兆异常的产生,且地下流体对地震前兆的作用是在特定的地质构造、水文地质环境下发生。     

内蒙两次5.9级地震与前兆异常特征的关系研究

以辽宁省长期丰富的地震前兆资料为基础，研究了内蒙两次5．9级地震与内蒙、东北地区前兆特征的关系。结果表明内蒙地震前前兆异常特征主要有：(1)前兆异常在时间上伴随内蒙巴林左旗5．9级地震事件的发生和结束呈阶段性起伏，空间上存在特征迁移；(2)中短期前兆异常阶段中以地形变为主体，在短临阶段地下流体和地磁出现异常。     

地下流体前兆模糊识别

在地震的孕育、发生到发展的过程中，可能会出现多项地下流体观测量不同程度的前兆异常变化，这些异常变化是复杂多样、模糊不清的。引入模糊识别法对一定区域和一定时间段的地下流体观测数据进行了分析和处理，表明模糊识别法可较好地识别和分辨出地下流体前兆的地震异常。     

地下流体附加力源的研究新思路

提出地下流体储量变化是地震和多种前兆发生的附加力源的新观点，认为多种天然的和人为的因素所引起的地下流体储量变化。是一种附加力源。它通过流体载荷、孔隙压力、动水压力及化学腐蚀等作用，促进地壳的构造变形，并导致多种地震前兆异常的产生；而流体载荷和构造变形，又可促进地震的孕育和发生。对于降水、地表水、开采等因素造成的异常变化，不能简单地当做干扰来加以排除，它本身包含有大量的地震前兆信息。论述了该思路的科     

祁连山地震带地下流体短期前兆异常特征分析

系统分析了地下流体短期前兆异常变化与中强地震的关系,提出祁连山地震带地下流体资料存在两类短期前兆异常,即转折型和单一型短期前兆异常,结合震例对这两类短期前兆异常的特征进行了分析,认为预报人员应特别注意该区内的这两类群体异常的特点,并把它应用到该区的地震预报中。     

基于模态分析和神经网络的裂缝损伤识别

提出了裂缝损伤诊断的神经网络方法,探讨了用模态技术和神经网络对混凝土结构裂缝损伤进行识别与定位的方法。文中以一简支矩形截面梁为研究对象,通过完好结构和损伤结构的有限元分析,获取两者的损伤标识量,输入BP神经网络训练。以损伤位置和裂缝高度作为输出参数,对其进行单处损伤定位的研究。数值仿真结果表明,采用神经网络方法可以对裂缝做出较好的诊断。     

利用单台地磁数据估算Ap和Kp指数的可行性分析

通过分析单台长期地磁场扰动幅度和地磁行星指数Ap和Kp关系,对1小时磁扰幅度rH的日平均与Ap进行拟合,快速估算Ap指数.对3小时内rH的平均与Kp进行对数拟合,估算Kp指数.采用肇庆地震台2003-2008年地磁H分量分钟值数据,估算行星Ap和Kp指数,与世界数据中心(WDC)给出的Ap和Kp指数进行统计分析.结果发...     

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.     

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Response of single benthic metrics and multi-metric methods to anthropogenic pressure gradients, in five distinct European coastal and transitional ecosystems

In recent times many benthic indices have been proposed to assess the ecological quality of marine waters worldwide. In this study we compared single metrics and multi-metric methods to assess coastal and transitional benthic status along human pressure gradients in five distinct environments across Europe: Varna bay and lake (Bulgaria), Lesina lagoon (Italy), Mondego estuary (Portugal), Basque coast (Spain) and Oslofjord (Norway). Hence, 13 single metrics (abundance, number of taxa, and several diversity and sensitivity indices) and eight of the most common indices used within the European Water Framework Directive (WFD) for benthic assessment were selected: index of size spectra (ISS), Benthic assessment tool (BAT), Norwegian quality index (NQI), Multivariate AMBI (M-AMBI), Benthic quality index (BQI), (Benthic ecosystem quality index (BEQI), Benthic index based on taxonomic sufficiency (BITS), and infaunal quality index (IQI). Within each system, sampling sites were ordered in an increasing pressure gradient according to a preliminary classification based on professional judgement. The different indices are largely consistent in their response to pressure gradient, except in some particular cases (i.e. BITS, in all cases, or ISS when a low number of individuals is present). Inconsistencies between indicator responses were most pronounced in transitional waters (i.e. IQI, BEQI), highlighting the difficulties of the generic application of indicators to all marine, estuarine and lagoonal environments. However, some of the single (i.e. ecological groups approach, diversity, richness) and multi-metric methods (i.e. BAT, M-AMBI, NQI) were able to detect such gradients both in transitional and coastal environments, being these multi-metric methods more consistent in the detection than single indices. This study highlights the importance of survey design and good reference conditions for some indicators. The agreement observed between different methodologies and their ability to detect quality trends across distinct environments constitutes a promising result for the implementation of the WFD’s monitoring plans. Moreover, these results have management implications, regarding the dangers of misclassification, uncertainty in the assessment, use of conflicting indices, and testing and validation of indices.     

Which objective function to calibrate rainfall–runoff models for low-flow index simulations?

Much has been written on the subject of objective functions to calibrate rainfall–runoff models. Many studies focus on the best choice for low-flow simulations or different multi-objective purposes. Only a few studies, however, investigate objective functions to optimize the simulations of low-flow indices that are important for water management. Here, we test different objective functions, from single objective functions with different discharge transformations or using low-flow indices, to combinations of single objective functions, and we evaluate their robustness and sensitivity to the rainfall–runoff model. We find that the Kling and Gupta efficiency (KGE) applied to a transformation of discharge is inadequate to fulfil all assessment criteria, whereas the mean of the KGE applied to the discharge and the KGE applied to the inverse of the discharge is sufficient. The robustness depends on the climate variability rather than the objective function and the results are insensitive to the model.

EDITOR A. Castellarin; ASSOCIATE EDITOR C. Perrin     

地电扰动指数GEI研究

本文应用中国大陆地区11个地电场台站5.5年（2012-01-01—2017-05-31）中磁静日和磁扰日的观测数据,并联系地电场变化敏感响应地下介质非均匀性和空间电磁活动的特点,发展了地电扰动指数,即消除静日地电变化的幅值比地电指数（GEI）.对比各台站的地电指数与地磁指数,87.43%的单台地电指数D与单台地磁指数K在数值上完全相同或相差1,93.75%的单台平均地电指数Ds与单台平均地磁指数[K+0.5]（四舍五入）相同或仅相差1,说明地电指数能用于量化界定地电扰动水平,如同地磁指数量化界定磁扰水平.地电指数将服务于地球电磁环境监测、科学研究等领域,同时也可以用来评估地电场观测数据的质量.     

Derivation of vegetative variables from a landsat tm image for modelling soil erosion

A study was carried out to assess the potential use of satellite thematic mapper (TM) images to produce maps of vegetation-related variables for erosion modelling. In a Mediterranean study area in southern France the (semi-)natural vegetation was described at 33 field plots using four quantitative methods: the Fosberg structural classification system, the cover and management factor of the Universal Soil Loss Equation, the leaf area index and the total percentage cover. After radiometric correction of the image, the spectral TM bands were processed following three different methods. Each method aimed at combining the data of the six spectral TM bands into a single band in such a way that the resulting image displayed optimal information on green vegetation cover. The algorithms used comprise the normalized difference vegetation index, the conventional ‘tasselled cap’ transformation and a locally tuned tasselled cap transformation. Only slight differences were found between the different methods to calculate spectral vegetation indices for this particular case. Furthermore, the correlations between the field variables and image-derived spectral indices are generally small. The largest correlations were found for the normalized vegetation index and the leaf area index (r + 0·71) and for the normalized vegetation index and Fosberg's structural vegetation classes (r + 0·76). However, Fosberg's method results in very general classes, which are of little use for soil erosion models. Furthermore, the spectral indices appeared to be sensitive for the vitality of the vegetation. Consequently, an area covered by a sensed, senescent vegetation will not yield a large value for the spectral index, but its soil is protected against splash erosion. This might lead to a misinterpretation of the soil protective cover when satellite images are used. A final conclusion is that a balance has to be found between the more accurate, but time-consuming field surveys to gather information on erosion-controlling factors and a certain loss of accuracy associated with the use of quick and easy remote sensing methods.     

Indices for the Objective Assessment of Tsunami Forecast Models

Many past studies have verified numerical simulations of tsunamis using only qualitative and subjective methods. This paper investigates the relative merits of several indices that can be used to objectively verify tsunami model performance. A number of commonly used indices, such as error in the maximum amplitude and root-mean-square error, are considered, as well as some further indices that have been developed for other specific applications. Desirable qualities of the indices are presented and these include computational efficiency, invariance when applied to tsunamis of any size or to time series of varying length (including relatively short series), and the ability to clearly identify a single best prediction from within a set of simulations. A scenario from the T2 tsunami scenario database is chosen as the control. From this, time series of sea-level elevations are extracted at designated test points located at a range of distances from the tsunami source region. Parameters of the T2 database are perturbed in order to examine the performance of the indices. Of the indices examined, several performed better than others, with Wilmott’s Index of Agreement and Watterson’s transformed Mielke index found to be the best. Combining data from multiple locations was shown to improve the performance of the indices. This study forms the basis for future evaluation of the indices using real observations of tsunamis.     

An evidential reasoning-based sustainability index for water resources management

ABSTRACT

Evidential reasoning (ER) is introduced as a new basis for developing and implementing sustainability indices (SI). The ER-based evaluations keep the merits of previous well-known sustainability indices and provide added values such as more accurate grade-based assessment and aggregation of performance criteria. The proposed modifications significantly improve the capability of the SI to scrutinize and differentiate various water-supply conditions. Available data from Gorganrud-Qaresou basin, northern Iran, are used to evaluate the applicability and efficiency of the sustainability index. The results of the proposed method are compared with two water resources sustainability indices with similar concepts but different bases. It is shown that the ER-based SI can better distinguish undesirable water-supply scenarios.