Integrated evaluation of urban groundwater hydrogeochemistry in context of fractal behaviour of groundwater level fluctuations

The present study was carried out as part of a complex survey of urban groundwater quality and quantity in Szeged, southeast Hungary. The concentrations of 12 inorganic contaminants in 28 shallow groundwater monitoring wells were determined over a 2-year period (2010–2012). The evaluation of concentrations indicates remarkable contamination all over the city. Discriminant analysis (DA) was used to evaluate the spatial changes of groundwater quality. The groundwater levels were measured over a 14-year period (2000–2013). The fractal properties of water level fluctuations time series characterizing the groundwater system and Tisza River were investigated using rescaled range (R/S) analysis. The resulting Hurst exponents clearly showed the persistency and thus long memory effects of both the groundwater and the river flow. Comparison of the results of DA with the results of R/S analysis thus implies that the geological conditions and the changing groundwater quantities are not related to groundwater quality.

EDITOR A. Castellarin

ASSOCIATE EDITOR A. Fiori     

Using principal component analysis in the investigation of groundwater hydrochemistry of Upper Jezireh Basin,Syria

Principal component analysis (PCA) was applied to hydrochemical and isotopic data of 34 groundwater samples. This allowed the reduction of 20 variables to four significant PCs that explain 81.9% of the total variance; F1 (47.1%) explains the groundwater mineralization, whereas F2 (17%) shows isotopic enrichment and nitrate pollution. Based on an iso-factor scores map of F1, three water zones were delineated: Zone A (F1 < ?1), with fresh groundwater from the unconfined aquifer; Zone B (1 > F1 > ?1), with moderate mineralization from the confined–unconfined aquifer boundary; and Zone C (F1 > 1), with the most mineralized hot water from the confined aquifer. The iso-factor scores map of F2 delineates positive values representing samples from the unconfined aquifer, with freshwater and nitrate contamination associated with stable isotope enrichment, whereas negative values represent samples from the confined aquifer. The results clearly demonstrate the usefulness of PCA in groundwater hydrochemistry investigations.     

Time series analysis for evaluating hydrological responses of pore-water pressure to rainfall in a slope

Characterization of pore-water pressure at the soil–atmosphere interface is a major requirement in relation to slope instability. A rain-gauge and five piezometers (BH1–BH5) were installed on a slope located in a Korean military base. The upper slope (BH4, BH5) was covered with plastic sheets to prevent rainwater from percolating into the slope due to safety issues. Rainfall is matched by prompt changes in the pore-water pressure except at BH5. Due to the plastic cover, the pore water does not show any significant change in the early period by evapotranspiration. From correlation analysis, two wells (BH3, BH5) have longer memory effects due to matrix flow of past precipitation. Two principal components show hydrological responses of pore water to rainfall during intense rainfall, but PC2 does not indicate any important changes in low or no rainfall. This study suggests that correlation analysis with PCA can be a valuable tool for interpreting datasets consisting only of pore-water pressure.     

新型预制装配式楼盖抗倒塌试验研究

地震及爆炸荷载下的结构连续倒塌问题对人民的生命财产造成重大威胁,是土木工程领域研究的一个热门方向。为了提高新型预应力空心楼板结构的整体性,防止由于竖向支承构件的失效形成楼板的局部或者连续倒塌,对2块新型预应力空心板足尺模型进行四分点静力加载试验,研究新型预制装配式两跨连续楼板的抗连续倒塌能力。试件均由预应力空心短板通过板端伸出U形筋和胡子筋进行对接连接,板侧纵向拼缝通过胡子筋和植筋与边梁的纵筋进行连接,2个试件的计算跨度相同。本文采用在加载过程中突然拆除中间支座,得到楼板破坏形态、裂缝发展、承载能力、应变、最大变形等试验结果。对试件的受力过程、悬索作用机理进行分析,最后得到楼盖拼缝及板侧边梁连接构造的布置合理,新型预制装配式楼盖采用合适的周边连系和横向拼缝连接可以达到理想的抗倒塌能力。     

基于主成分降维的总悬浮物浓度遥感估算模型适用性分析

总悬浮物浓度(C_TSM)是水质评价的重要参数.为了提高内陆Ⅱ类水体总悬浮物浓度估算的精度,利用主成分分析方法对2009年4月太湖水体实测高光谱数据进行降维处理,进而以不同数量的主成分作为变量,分别构建总悬浮颗粒物浓度的多元线性回归估算模型并比较这些模型的效果,从而确定最优的主分量个数;结合近年运行的高光谱传感器,对模型的适用性进行评价.结果表明:①前三个主成分(PC₁、PC₂、PC₃)从不同侧面涵盖了悬浮物浓度信息,它们与ln(C_TSM)的相关系数分别为0.728、0.401和0.403;②当主成分个数为6时,模型达到最优;模型的精度高于4个传统经验模型;③在400~850 nm之间,波段数大于45的高光谱传感器数据都能利用主成分分析的方法构建精度较高的总悬浮物浓度估算模型;此外,MERIS、HJ1-HSI、Hyperion和CHRIS这些常用的高光谱传感器的波段设置,都适合于主成分建模.     

Modeling spatially correlated spectral accelerations at multiple periods using principal component analysis and geostatistics

Regional seismic risk assessments and quantification of portfolio losses often require simulation of spatially distributed ground motions at multiple intensity measures. For a given earthquake, distributed ground motions are characterized by spatial correlation and correlation between different intensity measures, known as cross‐correlation. This study proposes a new spatial cross‐correlation model for within‐event spectral acceleration residuals that uses a combination of principal component analysis (PCA) and geostatistics. Records from 45 earthquakes are used to investigate earthquake‐to‐earthquake trends in application of PCA to spectral acceleration residuals. Based on the findings, PCA is used to determine coefficients that linearly transform cross‐correlated residuals to independent principal components. Nested semivariogram models are then fit to empirical semivariograms to quantify the spatial correlation of principal components. The resultant PCA spatial cross‐correlation model is shown to be accurate and computationally efficient. A step‐by‐step procedure and an example are presented to illustrate the use of the predictive model for rapid simulation of spatially cross‐correlated spectral accelerations at multiple periods.     

Extracting water-related features using reflectance data and principal component analysis of Landsat images

This study aimed to map water features using a Landsat image rather than traditional land cover. We involved the original bands, spectral indices and principal components (PCs) of a principal component analysis (PCA) as input data, and performed random forest (RF) and support vector machine (SVM) classification with water, saturated soil and non-water categories. The aim was to compare the efficiency of the results based on various input data. Original bands provided 93% overall accuracy (OA) and bands 4–5–7 were the most informative in this analysis. Except for MNDWI (modified normalized differenced water index, with 98% OA), the performance of all water indices was between 60 and 70% (OA). The PCA-based approach conducted on the original bands resulted in the most accurate identification of all classes (with only 1% error in the case of water bodies). We therefore show that both water bodies and saturated soils can be identified successfully using this approach.     

2012年江苏扬州M 4.9地震前地磁垂直分量日变双低点异常

2012年6月13日和7月10日华东地区部分地磁台垂直分量日变形态出现双低点异常,首次异常出现后37天,于7月20日发生江苏扬州M 4.9地震,震中位于低点位移分界线附近。分析认为,在强震前由于应力变化,引起孕震体环境中介质电导率等电磁性质发生改变,区域地磁场垂直分量日变曲线出现相位和幅度变化,说明地磁垂直分量日变双低点异常与地震的孕育和发生相关。     

改进的多道预测算子压制浅水多次波方法

在浅水情况下,由于观测数据中缺少近偏移距信息,水层多次波的压制面临挑战.利用多道预测算子压制水层多次波是浅水环境下压制多次波的重要方法之一,这种方法先从输入数据中估计出多道预测算子,再将预测算子和输入数据做褶积预测出水层相关多次波.然而,估计的多道预测算子很容易受噪声污染,从而影响多次波模型的精度.所以,我们提出了改进的多道预测算子压制浅水多次波方法.该方法先从数据中估计出多道预测算子,并利用估计的算子构建出精确的水层模型;然后,通过计算算子的走时信息、估计振幅信息、合成新算子三个步骤来修正原始的多道预测算子.修正的算子不仅不受噪声影响,还含有精确的走时信息、可靠的振幅信息;最后,该方法用修正的算子来预测多次波,并结合自适应相减,将预测的多次波从输入数据中去除.通过合成数据和实际资料的验证表明,相比于原始的多道预测算子压制多次波方法,改进的方法能够取得更好的压制效果.     

选主元矩阵原位替换解算方法

矩阵行列式、矩阵方程未知数和矩阵逆阵元素,可采用矩阵原位替换解算方法,利用矩阵元素约化值进行解算,但矩阵元素约化值计算过程中要求矩阵主元约化值不能等于零,在没有确认矩阵是否满秩的情况下,其值等于零有可能由矩阵元素排列结构引起,也有可能由矩阵秩亏引起,如何判别矩阵主元约化值为零的成因,在排除矩阵秩亏的情况下,如何利用选主元矩阵原位替换解算方法继续完成相应矩阵解算,是本文研究的内容。该研究可使矩阵原位替换解算方法得到更加广泛的应用。