Multivariate statistical analysis and environmental isotopes of Amman/Wadi Sir (B2/A7) groundwater,Yarmouk River Basin,Jordan

Multivariate statistical techniques, cluster and factor analyses were applied on the Amman/Wadi Sir groundwater chemistry, Yarmouk River basin, north Jordan. The main objective was to investigate the main processes affecting the groundwater chemical quality and its evolution. The k‐means cluster analysis yields three groups with distinct ionic concentrations. Cluster 1 comprises the vast majority of the sampled wells, and the water that belongs to this cluster can be classified as freshwater. Cluster 2 comprises only 2% of the sampled wells; it has the highest ionic concentration. The water of this cluster can be classified as brackish water. Cluster 3 involves 23% of the sampled wells, and it has total ionic concentration intermediate to that of clusters 1 and 2. Factor analysis yields a three‐factor model, which explains 76.77% of the groundwater quality variation. Factor 1 ‘salinity factor’ involves EC, Na⁺, Cl^‐, SO₄^‐2, K⁺ and Mg⁺² and reflects groundwater salinization because of overpumping. Factor 2 ‘hardness factor’ includes Ca⁺², HCO₃^‐ and the pH value and signifies soil–water/rock interaction. Factor 3 ‘nitrate factor’ involves only NO₃^‐ and points to groundwater contamination because of human activities, mainly untreated wastewater, and crops and animal cultivation in the unconfined portion of the aquifer. Factors 1 and 3 can be described as human‐induced factors, whereas factor 2 can be described as geogenic factor. Factors' scores were mapped to deduce the controlling processes on the groundwater chemistry. Stable isotope composition of ¹⁸O and ²H has revealed that the groundwater is a mixture of two water types. The radioactive isotopes tritium and ¹⁴ C were used to evaluate present day recharge to the aquifer and to estimate the groundwater age, respectively. Present day recharge to the groundwater is taking place in the unconfined portion of the aquifer as it is indicated by the measurable tritium content and low groundwater age. Copyright © 2012 John Wiley & Sons, Ltd.     

Agricultural land use and hydrology affect variability of shallow groundwater nitrate concentration in South Florida

South Florida's Miami‐Dade agricultural area is located between two protected natural areas, the Biscayne and Everglades National Parks, subject to the costliest environmental restoration project in history. Agriculture, an important economic activity in the region, competes for land and water resources with the restoration efforts and Miami's urban sprawl. The objective of this study, understanding water quality interactions between agricultural land use and the shallow regional aquifer, is critical to the reduction of agriculture's potentially negative impacts. A study was conducted in a 4‐ha square field containing 0·9 ha of corn surrounded by fallow land. The crop rows were oriented NW–SE along the dominant groundwater flow in the area. A network of 18 monitoring wells was distributed across the field. Shallow groundwater nitrate–nitrogen concentration [N‐NO₃^?] was analyzed on samples collected from the wells biweekly for 3 years. Detailed hydrological (water table elevation [WTE] at each well, groundwater flow direction [GwFD], rainfall) and crop (irrigation, fertilization, calendar) data were also recorded in situ. Flow direction is locally affected by seasonal regional drainage through canal management exercised by the local water authority. The data set was analyzed by dynamic factor analysis (DFA), a specialized time series statistical technique only recently applied in hydrology. In a first step, the observed nitrate variation was successfully described by five common trends representing the unexplained variability. By including the measured hydrological series as explanatory variables the trends were reduced to only three. The analysis yields a quantification of the effects of hydrological factors over local groundwater nitrate concentration. Furthermore, a spatial structure across the field, matching land use, was found in the five remaining common trends whereby the groundwater [N‐NO₃^?] in wells within the corn rows could be generally separated from those in fallow land NW and SE of the crop strip. Fertilization, masked by soil/water/plant‐delayed processes, had no discernible effect on groundwater nitrate levels. Copyright © 2006 John Wiley & Sons, Ltd.     

Using multivariate statistical techniques and geochemical modelling to identify factors controlling the evolution of groundwater chemistry in a typical transitional area between Taihang Mountains and North China Plain

Identifying the key factors controlling groundwater chemical evolution in mountain-plain transitional areas is crucial for the security of groundwater resources in both headwater basins and downstream plains. In this study, multivariate statistical techniques and geochemical modelling were used to analyse the groundwater chemical data from a typical headwater basin of the North China Plain. Groundwater samples were divided into three groups, which evolved from Group A with low mineralized Ca-HCO₃ water, through Group B with moderate mineralized Ca-SO₄-HCO₃ water, to Group C with highly saline Ca-SO₄ and Ca-Cl water. Water-rock interaction and nitrate contamination were mainly responsible for the variation in groundwater chemistry. Groundwater chemical compositions in Group A were mainly influenced by dissolution of carbonates and cation exchange, and suffered less nitrate contamination, closely relating to their locations in woodland and grassland with less pronounced human interference. Chemical evolution of groundwater in Groups B and C was gradually predominated by the dissolution of evaporites, reverse ion exchange, and anthropogenic factors. Additionally, the results of the inverse geochemical model showed that dedolomitization caused by gypsum dissolution, played a key role in the geochemical evolution from Group A to Group B. Heavy nitrate enrichment in most groundwater samples of Groups B and C was closely associated with the land-use patterns of farmland and residential areas. Apart from the high loads of chemical fertilizers in irrigation return flow as the main source for nitrate contamination, the stagnant zones, flood irrigation pattern, mine drainage, and groundwater-exploitation reduction program were also important contributors for such high mineralization and heavy NO₃⁻ contents in Group C. The important findings of this work not only provide the conceptual framework for the headwater basin but also have important implications for sustainable management of groundwater resources in other headwater basins of the North China Plain.     

Serial dependence properties in multivariate streamflow simulation with independent decomposition analysis

Stochastic simulation of multivariate hydrologic variables has a key role in evaluating alternative designs and operation rules of hydrologic facilities. The recently developed decomposition analysis, Independent Component Analysis (ICA), allows us to apply the simple univariate time series model to each extracted component by: (1) decomposing multivariate time series into independent components with ICA; (2) modelling and generating each component independently; and (3) mixing the generated components to come back to observational domain. However, we illustrate in the current study that fitting a univariate time series model to each extracted component might end up with the underestimation of the serial dependence that the observation data might contain. A alternative for parameter estimation is suggested to preserve the serial dependence of the observation variable using the relationship between the observation variable and the decomposed variable. The case study of the Upper Colorado River basin shows that some improvement is made through the suggested alternative. Copyright © 2011 John Wiley & Sons, Ltd.     

基于三种多变量不安定指数分析模型的汶川县地质灾害易发性评价

采用多变量不安定指数分析法模型并加以改进,应用于汶川县地质灾害易发性评价。选取坡度、坡向、地层岩性、距断层距离、植被覆盖率及距水系距离六项影响因子,结合四川省自然资源厅发布的汶川县地质灾害隐患点数据,以幂次相乘、线性累加、幂次累加这三种不同的不安定指数分析法模型分别得到了研究区地质灾害易发性分区图,并用接受者操作特性曲线（Receiver Operating Characteristic curve, ROC curve）验证了各种模型的评价性能。结果表明:（1）对本案例而言,幂次相乘模型相较其它两种模型具有最高的精度;（2）汶川县地质灾害“极高”“高”“中”“低”“极低”易发区的面积占比分别为:19.3%、24.6%、19.2%、19.3%、17.6%,且研究区地质灾害易发性较高的区域多分布在断裂带附近。本研究成果可为区域地质灾害防治工作提供理论借鉴和技术参考。     

基于多元资料的成都市2049远景发展战略规划气候可行性论证

配合2015年成都市2049远景发展战略规划编制,利用成都市气象和空气质量观测数据、卫星遥感、地理信息及城市规划土地利用资料,对该市风、热/冷环境和大气环境进行计算分析,结果表明:①成都市主导风向为NE,年平均风速为1.2m/s,静风频率高达34%,冬季风速最小。市域内风速总体呈东北向西南递减趋势,西部沿龙门山岷江口和湔江口为市域2处主要通风口。21世纪00年代城市集中区风速较20世纪80、90年代显著减少,NE和NW风向上减少可达0.5m/s。②该市较强等级以上热岛面积由1992年的53.6km~2发展至2014年的798km~2,且热岛中心呈现多极化。高级别生态冷源集中于龙门山和龙泉山,大规模城市扩张与沿山坡耕地是热/冷环境恶化的重要原因。③成都大气环境状况不佳,空气污染程度呈现城区—近郊—远郊递减特征。2007—2014年城区PM10和NO2平均浓度分别为0.116mg/m~3和0.054mg/m~3,均未达国家环境空气质量二级标准。④绘制了成都市城市气候分析图,并结合实地调查、土地利用现状以及发展诉求,形成了城市规划气候建议图,将全市划分为6类规划分区,明确了对气候影响程度不同的各类空间,进而为成都市2049远景发展战略规划提出了气候可行性建议。     

大气校正对SPOT卫星遥测水质的影响

藉由卫星遥测进行河川水质监测，目前尚没有较明确可行之方法，如何利用较为简单且适当的SPOT卫星遥测大气校正方法，正确辨识水体水质，是本研究的主要目的。利用SPOT卫星作两阶段非监督式及监督式自动分类，确认卫星影像中水质测站对应之水体样本，并将所有样本依季节分群，俾让卫星监测水体水质样本较为均质。模拟方式采用多变量回归、类神经网络及判别分析3种模式，并比较4种不同之大气校正程序。结果发现。以水质及其指标整体预测来看，类神经网络预测结果较优于多变量回归及判别分析的结果，大气校正方法以直接采用灰度值并消除最暗像元灰度值之校正方法，即可达到不错之预测结果。综合而言，以SPOT或分辨率更高之卫星光谱遥测水质是简单可行，但仍需更多数据以验证其精确度。     

多元变化检测的相对辐射校正方法研究

基于多元变化检测的相对辐射校正方法通过阈值获取校正点,该方法的校正结果优于传统人工参与的校正方法。文章对方法中阈值选择以及自然景观特征等影响因素做了进一步研究,选择北京市平原区和山区的各2期TM影像作为数据源,运用均方根误差和变异系数2个统计特征参数比较和评价校正结果,结果表明:基于多元变化检测的相对辐射校正方法获得的结果有利于后续数据分析;不同阈值获得的校正结果没有明显差异;不同自然景观特征对该方法影响程度不同。     

多因素灰色G(1,N)模型及其在基坑位移预测中的应用

G(1,1)模型只利用单点已测数据预测该点的位移,而不管别的因素影响。而事实上该点位移和围护桩上其他点的位移及锚索拉力是耦合的。针对传统的单因素灰色模型在基坑预测中的不足之处,本文提出采用多因素的G(1,N)灰色模型对基坑位移进行预测研究。计算实例表明,该模型预测精度高,所需数据少,简单实用,值得在基坑预测中推广。     

吉林省工业化、城镇化与农业现代化关系实证分析

工业化、城镇化和农业现代化相互影响,三者相互促进、相辅相成,有着内在的逻辑关系。通过建立吉林省工业化、城镇化和农业现代化评价指标体系,基于1991-2009年时间序列数据利用因子分析法计算了吉林省工业化、城镇化和农业现代化的发展指数,三条发展指数曲线相互交错,趋势基本相同,尤其是工业化和城镇化水平都在不断进步。但从三者对比来看,三化之间不同步现象明显,出现脱节现象。进而对其进行多变量协整检验,结果表明:"三化"在时间上并非同步而生,工业化的进步会滞后一期引起城镇化水平和农业现代化水平提高,工业化对"三化"的拉动作用在短期内立即体现,长期内需要工业化水平的不断提高才能为"三化"的进步提供源源不断的动力。农业现代化水平的提高也会促进城镇化水平提高,但是需要滞后三期才会体现。据此提出"三化"统筹的基本思路是"用农业化范式发展工业化","用工业化范式发展农业现代化","用工农业融合集聚发展城镇化"。