An Approach for Classification of Groundwaters by Synchronous Fluorescence Spectroscopy and Discriminant Analysis

Monitoring and evaluation of groundwater quality in drinking water protectorates is of particular interest if the uncontrolled entry of pollutants, for example by infiltrating river water, cannot be excluded. A fluorescence spectroscopic method is presented as possible alternative to the conventional expensive hydrochemical investigations. This method uses the information yielded by synchronous fluorescence spectra. After a Fourier transformation of the original spectra and a following discriminant analysis, the samples can be classified in different groups corresponding to the different types of groundwater. The method was tested in the drinking water protectorate of a waterworks of a German metropolis (Halle, Sachsen-Anhalt). We found a prediction rate of about 90% in the investigated case.     

灰色系统GM模型在地下水动态异常识别中的应用

本应用灰色系统理论的ＧＭ模型对地下水动态资料进行了异常识别，发现在１９８１年河北宁晋ＭＳ５．８级地震、１９８３年荷泽ＭＳ５．９级地震、１９８５年河北任县ＭＳ５．０级地震前，有明显的异常显示，通过选择不同建模数据个数及外推个数，发现对豫０１井五日均值资料建模处理，选择２个月的数据１０天滑动逐次建模识别的异常较清楚。同时对所建模型的精度进行了分析，证明该方法在本区豫０１井、鲁０５井资料处理及前兆异常     

Migration and contamination of major and trace elements in groundwater of Madras city,India

Groundwater samples collected from both open and bore wells in an area of about 270 km² from Madras City, India, have been analyzed for major ions (HCO₃, Cl, Si, Na, Ca, and Mg) and trace elements (As, Se, B, V, Cr, Fe, Co, Pb, Cu, Zn, Cd, Mn, Ni, Mo, and Ba). The study reveals that the quality of potable water has deteriorated to a large extent. Seawater intrusion into the aquifer has been observed in nearly 50 percent of the study area. The toxic elements (As and Se) have already exceeded the maximum permissible limits of drinking water in almost the entire city. A positive correlation of As and Se with other toxic metals such as V, Cr, Fe, B, etc., indicates that all these elements are anthropogenic in origin. Applying multivariate analysis, the source for trace elements in groundwater has been grouped into two major factors: pollution and mobilization factors. The groundwater in the study area is largely contaminated by organic effluents and reflects the intensity of pollution caused by the overlying soil sediment and rapid infiltration of the pollutants.     

Quantitative analysis of springs

Growing demand for groundwater resources and stringent environmental concerns has led to large groundwater investigations, including characterization of aquifer systems that are hydraulically connected to springs. A pumping test is one of the most reliable means of quantifying hydraulic characteristics and the response of natural springs to pumping because it yields results that, in general, are representative of a larger area than are results from a single point observation. Recharge to the aquifer sustaining discharge from springs must be evaluated prior to the utilization of springs. The spring hydrograph is analyzed, as the shape of a hydrograph is a reflection of the response of the aquifer to recharge. The form and rate of recession provide significant information on the storage, lithological composition, and structural characteristics of the aquifer system sustaining the spring. Water tracing techniques have been developed and used over a period of centuries to delineate catchment boundaries, estimate groundwater flow velocities, determine areas of recharge, and identify sources of pollution of spring water.     

地下水对工程和环境的作用

地下水对上程建设和地质环境的作用与影响日趋显著,人们认识日益深化。实践表明,这类问题不完伞是纯水文地质问题。实质上,它是介乎于水文地质与工程地质之间,暂定名为工程水文地质学。专门进行在工程建设和环境地质中由于地下水作用而产生的各类工程地质问题或水文地质问题。为充分阐明问题,本文从水与岩土相互作用、基坑排水与潜蚀流沙、地基沉降与黄土湿陷、道路冻害与隧道涌水、矿抗突水与竖井破坏、坝基渗漏与稳定、坝基抗滑稳定以及与地下水有关的地质灾害问题等方面,进行了举例阐述,初步论证了重要性、问题和某些实质。目的在于,向人们揭示一个值得研究的方向,并给予充分的重视。     

逸出气体的监测及其与地震活动的关系

地下流体能较好地反映地壳应力的变化,对地震前兆的监测预报有一定的意义。本文通过对地下热矿水中逸出气的组分、总量及其与溶解气量比的观测和试验,表明地下水中的逸出气体有良好的震兆作用,其中逸气总量以及逸出氦等组分可望成为映震的灵敏测项,有必要深入开展观测研究。本文还介绍了自行设计的集气装置及效果较好的现场简易测量方法。     

Conditioning mean steady state flow on hydraulic head and conductivity through geostatistical inversion

Nonlocal moment equations allow one to render deterministically optimum predictions of flow in randomly heterogeneous media and to assess predictive uncertainty conditional on measured values of medium properties. We present a geostatistical inverse algorithm for steady-state flow that makes it possible to further condition such predictions and assessments on measured values of hydraulic head (and/or flux). Our algorithm is based on recursive finite-element approximations of exact first and second conditional moment equations. Hydraulic conductivity is parameterized via universal kriging based on unknown values at pilot points and (optionally) measured values at other discrete locations. Optimum unbiased inverse estimates of natural log hydraulic conductivity, head and flux are obtained by minimizing a residual criterion using the Levenberg-Marquardt algorithm. We illustrate the method for superimposed mean uniform and convergent flows in a bounded two-dimensional domain. Our examples illustrate how conductivity and head data act separately or jointly to reduce parameter estimation errors and model predictive uncertainty.This work is supported in part by NSF/ITR Grant EAR-0110289. The first author was additionally supported by scholarships from CONACYT and Instituto de Investigaciones Electricas of Mexico. Additional support was provided by the European Commission under Contract EVK1-CT-1999-00041 (W-SAHaRA-Stochastic Analysis of Well Head Protection and Risk Assessment).     

Stochastic estimation of facies using ground penetrating radar data

Explicitly defining large-scale heterogeneity is a necessary step of groundwater model calibration if accurate estimates of flow and transport are to be made. In this work, neural networks are used to estimate radar facies probabilities from ground penetrating radar (GPR) images, yielding stochastic facies-based models that honour the large-scale architecture of the subsurface. For synthetic GPR images, a neural network was able to correctly identify radar facies with an accuracy of approximately 90%. Manual interpretation of a set of 450 MHz GPR field data from the Borden aquifer resulted in the identification of four radar facies. Of these, a neural network was able to identify two facies with an accuracy of near 80% and one with an accuracy of 44%. The neural network was not able to identify the fourth facies, likely due to the choice of defining facies characteristics. Sequential indicator simulation was used to generate facies realizations conditioned to the radar facies probabilities. Numerical simulations indicate that significant improvements in the prediction of solute transport are possible when GPR is used to constrain the facies model compared to using well data alone, especially when data are sparse.This work was supported by funding to R. Knight under Grant No. DE-FG07–00ER15118-A000, Environmental Management Science Program, Office of Science and Technology, Office of Environment Management, United States Department of Energy (DOE). However, any opinions, findings, conclusions, or recommendations expressed herein are those of the authors and do not necessarily reflect the views of DOE. Further support was provided by a Stanford Graduate Fellowship to S. Moysey. The authors would also like to thank James Irving for his assistance with processing of the radar data.     

Potential pollution of groundwater in the valley of the Seybouse River,north-eastern Algeria

In north-eastern Algeria, the Seybouse River is an important source of water used mainly for irrigation of large agricultural areas extending from the Guelma region to Annaba city. Industrial activities in this region contribute substantial water pollution to the river and the groundwater. Based on the different sources of pollution, mapping of areas vulnerable to groundwater pollution has been accomplished by combining land use and data on groundwater levels. The resulting maps show that the most vulnerable areas are those with large industrial activities—in Meboudja, Bouchegouf and Guelma. Infiltration and runoff contribute to pollution, and the highest infiltration rate is generally observed in areas of agricultural and industrial activities. Pollution of the aquifers in this area is of concern. Mountains, such as the Edough and Gelaat Bou Sbaa, contribute high runoff that carries pollutants towards the groundwater.     

GIS-based determination of the mean long-term groundwater recharge in Lower Saxony

This paper presents the findings of a collaborative research project of the Geological Survey of Lower Saxony (NLfB) and the Programme Group Systems Analysis and Technology Evaluation (STE) of Research Centre Jülich on the GIS-based determination of the mean long-term groundwater recharge in Lower Saxony using high-resolution digital data (Dörhöfer and others 2001). The model calculations were performed on the basis of the water-balance model GROWA (Kunkel and Wendland 2002) with a spatial resolution of 100x100 m². The accuracy of the calculated groundwater recharge values for the period 1961–1990 was verified on the basis of data from gauging stations and displayed a good agreement between observed runoff values and model results.