Modification of the GALDIT framework using statistical and entropy models to assess coastal aquifer vulnerability

Recently, groundwater vulnerability assessment of coastal aquifers using the GALDIT framework has been widely used to investigate the process of groundwater contamination. This study proposes multi-attribute decision-making (MADM) entropy and Wilcoxon non-parametric statistical test methods to improve the vulnerability index of coastal aquifers. The rates and weights of this framework were modified using Wilcoxon non-parametric and entropy methods, respectively, and a combined framework of GALDIT-entropy, Wilcoxon-GALDIT, and Wilcoxon-entropy was obtained. Pearson correlation coefficients between the mentioned vulnerability indices and total-dissolved solids (TDS) of 0.51, 0.66 and 0.75, respectively, were obtained. According to the results, the Wilcoxon-entropy index had the highest correlation with TDS. Generally, it can be concluded that the proposed frameworks provide a more accurate estimation of vulnerability distribution in coastal aquifers.     

Developing a reliable model for aquifer vulnerability

The assessment of aquifer vulnerability to pollution is crucial for planning a sound management strategy of groundwater quality protection and farmland fertilizer use. This study establishes a reliable model for aquifer vulnerability assessment with an excellent performance for predicting groundwater nitrate-N contamination in the Choushui River alluvial fan, Taiwan based on the DRASTIC method. To promote the prediction performance of aquifer vulnerability assessment, discriminant analysis (DA) was applied to determine the weights of factors in the DRASTIC model by comparing the model results with the observed nitrate-N data. Key factors influencing the presence of groundwater nitrate-N pollution were characterized for different concentration thresholds. The results of analysis reveal that the modified DRASTIC model using DA significantly improves prediction performance for aquifer vulnerability assessment, and groundwater protection zones can be determined correctly based on the modified DRASTIC index. Furthermore, the sensitivity of the factors in the modified DRASTIC model indicates that the depth to the groundwater and aquifer media are critical when the nitrate-N concentration is less than 3 mg/L, while the impact of the vadose zone plays a vital role in controlling nitrate-N pollution of over 5 mg/L.     

A supervised committee machine artificial intelligent for improving DRASTIC method to assess groundwater contamination risk: a case study from Tabriz plain aquifer,Iran

Vulnerability maps are designed to show areas of greatest potential for groundwater contamination on the basis of hydrogeological conditions and human impacts. The objective of this research is (1) to assess the groundwater vulnerability using DRASTIC method and (2) to improve the DRASTIC method for evaluation of groundwater contamination risk using AI methods, such as ANN, SFL, MFL, NF and SCMAI approaches. This optimization method is illustrated using a case study. For this purpose, DRASTIC model is developed using seven parameters. For validating the contamination risk assessment, a total of 243 groundwater samples were collected from different aquifer types of the study area to analyze \( {\text{NO}}_{ 3}^{ - } \) concentration. To develop AI and CMAI models, 243 data points are divided in two sets; training and validation based on cross validation approach. The calculated vulnerability indices from the DRASTIC method are corrected by the \( {\text{NO}}_{3}^{ - } \) data used in the training step. The input data of the AI models include seven parameters of DRASTIC method. However, the output is the corrected vulnerability index using \( {\text{NO}}_{3}^{ - } \) concentration data from the study area, which is called groundwater contamination risk. In other words, there is some target value (known output) which is estimated by some formula from DRASTIC vulnerability and \( {\text{NO}}_{3}^{ - } \) concentration values. After model training, the AI models are verified by the second \( {\text{NO}}_{3}^{ - } \) concentration dataset. The results revealed that NF and SFL produced acceptable performance while ANN and MFL had poor prediction. A supervised committee machine artificial intelligent (SCMAI), which combines the results of individual AI models using a supervised artificial neural network, was developed for better prediction of vulnerability. The performance of SCMAI was also compared to those of the simple averaging and weighted averaging committee machine intelligent (CMI) methods. As a result, the SCMAI model produced reliable estimates of groundwater contamination risk.     

Origin of salinity in a multilayered aquifer with high salinization vulnerability

The Kaluvelly watershed is a coastal area (Tamil Nadu, India) where water abstraction has resulted in a dramatic fall in the level of the water table and a piezometric depression in the most exploited aquifer, the Vanur aquifer. In addition, intensification/mechanization of agriculture may have affected the quality of recharge water. An initial hydrodynamic study showed that the Vanur aquifer is highly vulnerable to salinization due to potential seawater intrusion, and our aim was to determine the source of salinity recorded in the groundwater of this multilayered aquifer. Our approach involved the use of existing boreholes and of a moderate number of samples, with the aim of developing appropriate water resource management techniques. Major element, ¹⁸O/¹⁶O, ²H/¹H and ⁸⁷Sr/⁸⁶Sr, ratios were measured in rainwater, surface water and groundwater collected during five sampling campaigns over a 2‐year period. Geochemical data indicate that the Vanur aquifer is recharged and that small mixings between aquifers fluctuate according to monsoon intensity. There was no evidence of seawater intrusion. The range of recorded salinity originated mainly from water–rock interaction but a disconnection of some deeper parts of the aquifer was apparent. Strontium isotopic ratios in the recharge area suggest an anthropogenic influence, possibly related to fertilizer use. A high SO₄/Cl ratio was observed in the aquifer; in the deeper parts, the influence of a formation containing lignite is hypothesized, whereas near the surface, sulphate may partly originate from fertilizer use and fossil fuel combustion. Water isotopic data suggest that the origin of precipitation in this region has been unchanged for several hundreds or thousands of years. Copyright © 2011 John Wiley & Sons, Ltd.     

A distance-drawdown aquifer test method for aquifers with areal anisotropy

A new distance-drawdown method for aquifers with anisotropy on the horizontal plane is presented. The method uses scalar transformation to convert to an equivalent, isotropic medium, thus permitting application of the Cooper-Jacob Method. The method is applicable to cases where at least one ellipse of equal drawdown can be delineated but can also be applied where no ellipse can be discerned from the data. In the latter case, a least-squares regression approach can be employed to estimate the orientation and magnitude of the anisotropy. The regression R2 value provides a quantitative assessment of the degree to which the drawdown data are indicative of a systematic areal anisotropy in the aquifer or whether the data simply reflect natural aquifer heterogeneity. In addition to confined aquifers, this methodology, like the Cooper-Jacob Method, is also applicable to unconfined aquifers either before the onset of delayed drainage or following the completion of delayed drainage provided that the u value meets the recommended criterion.     

A new method for aquifer system identification and parameter estimation

The standard practice for assessing aquifer parameters is to match groundwater drawdown data obtained during pumping tests against theoretical well function curves specific to the aquifer system being tested. The shape of the curve derived from the logarithmic time derivative of the drawdown data is also very frequently used as a diagnostic tool to identify the aquifer system in which the pumping test is being conducted. The present study investigates the incremental area method (IAM) to serve as an alternative diagnostic tool for the aquifer system identification as well as a supplement to the aquifer parameter estimation procedure. The IAM based diagnostic curves for ideal confined, leaky, bounded and unconfined aquifers have been derived as part of this study, and individual features of the plots have been identified. These features were noted to be unique to each aquifer setting, which could be used for rapid evaluation of the aquifer system. The effectiveness of the IAM methodology was investigated by analyzing field data for various aquifer settings including leaky, unconfined, bounded and heterogeneous conditions. The results showed that the proposed approach is a viable method for use as a diagnostic tool to identify the aquifer system characteristics as well as to support the estimation of the hydraulic parameters obtained from standard curve matching procedures. Copyright © 2012 John Wiley & Sons, Ltd.     

A method to assess annual average renewable groundwater reserves for large regions in Spain

Abstract

This paper proposes a method for assessing the renewable groundwater reserves of large regions for an average year, based on the integration of the recession curves for their basins' springs or the natural baseflow of their rivers. In this method, the hydrodynamic volumes (or renewable reserves), were estimated from the baseflow. It was assumed that the flow was the same as the natural recharge, and the recession coefficients were derived from the hydrogeological parameters and geometric characteristics of the aquifers and adjusted to fit the recession curves at gauging stations. The method was applied to all the aquifers of Spain, which have a total renewable groundwater reserve of 86 118 hm³—four times the mean annual recharge. However, the spatial distribution of these reserves is highly variable; 18.6% of the country's aquifers contain 94.7% of the entire reserve.

Citation Sanz, E. & Recio, B. (2010) A method to assess annual average renewable groundwater reserves for large regions in Spain. Hydrol. Sci. J. 56(1), 99–107.     

A least-squares penalty method algorithm for inverse problems of steady-state aquifer models

Based on the generalized Gauss–Newton method, a new algorithm to minimize the objective function of the penalty method in (Bentley LR. Adv Wat Res 1993;14:137–48) for inverse problems of steady-state aquifer models is proposed. Through detailed analysis of the “built-in” but irregular weighting effects of the coefficient matrix on the residuals on the discrete governing equations, a so-called scaling matrix is introduced to improve the great irregular weighting effects of these residuals adaptively in every Gauss–Newton iteration. Numerical results demonstrate that if the scaling matrix equals the identity matrix (i.e., the irregular weighting effects of the coefficient matrix are not balanced), our algorithm does not perform well, e.g., the computation cost is higher than that of the traditional method, and what is worse is the calculations fail to converge for some initial values of the unknown parameters. This poor situation takes a favourable turn dramatically if the scaling matrix is slightly improved and a simple preconditioning technique is adopted: For naturally chosen simple diagonal forms of the scaling matrix and the preconditioner, the method performs well and gives accurate results with low computational cost just like the traditional methods, and improvements are obtained on: (1) widening the range of the initial values of the unknown parameters within which the minimizing iterations can converge, (2) reducing the computational cost in every Gauss–Newton iteration, (3) improving the irregular weighting effects of the coefficient matrix of the discrete governing equations. Consequently, the example inverse problem in Bentley (loc. cit.) is solved with the same accuracy, less computational effort and without the regularization term containing prior information on the unknown parameters. Moreover, numerical example shows that this method can solve the inverse problem of the quasilinear Boussinesq equation almost as fast as the linear one.In every Gauss–Newton iteration of our algorithm, one needs to solve a linear least-squares system about the corrections of both the parameters and the groundwater heads on all the discrete nodes only once. In comparison, every Gauss–Newton iteration of the traditional method has to solve the discrete governing equations as many times as one plus the number of unknown parameters or head observation wells (Yeh WW-G. Wat Resour Res 1986;22:95–108).All these facts demonstrate the potential of the algorithm to solve inverse problems of more complicated non-linear aquifer models naturally and quickly on the basis of finding suitable forms of the scaling matrix and the preconditioner.     

Assessment of aquifer vulnerability to industrial waste water using resistivity measurements. A case study, along El-Gharbyia main drain, Nile Delta, Egypt

1D resistivity sounding and 2D resistivity imaging surveys were integrated with geological and hydrochemical data to assess the aquifer vulnerability and saltwater intrusion in the north of Nile Delta, Egypt. In the present study, the El-Gharbyia main drain was considered as a case study to map the sand bodies within the upper silt and clay aquitard. Twenty Schlumberger soundings and six 2D dipole-dipole profiles were executed along one profile close to the western side of the main drain. In addition, 14 groundwater samples and 4 surface water samples from the main drain were chemically analyzed to obtain the major and trace elements concentrations.The results from the resistivity and hydrochemical data were used to assess the protection of the groundwater aquifer and the potential risk of groundwater pollution. The inverted resistivities and thicknesses of the layers above the aquifer layer were used to estimate the integrated electrical conductivity (IEC) that can be used for quantification of aquifer vulnerability. According to the aquifer vulnerability assessment of an underlying sand aquifer, the southern part of the area is characterized by high vulnerability zone with slightly fresh to brackish groundwater and resistivity values of 11-23 Ω.m below the clay cap. The resistivity sections exhibit some sand bodies within the clay cap that lead to increase the recharging of surface waste water (650 mg/l salinity) and flushing the upper part of underlying saltwater aquifer. The region in the north has saltwater with resistivity less than 6 Ω.m and local vulnerable zones within the clay cap. The inverted 2D dipole-dipole profiles in the vulnerable zones, in combination with drilling information have allowed the identification of subsoil structure around the main drain that is highly affected by waste water.     

基于易损性的基础隔震结构地震动选取方法研究

对基础隔震结构进行动力弹塑性时程分析时,地震记录的选择是关键.提出基于基础隔震结构弹塑性动力放大系数谱进行地震记录选取的方法:首先采用动力弹塑性时程分析方法对基础隔震结构的两自由度简化模型进行分析,得到结构的动力放大系数谱;然后采用谱匹配的方法选取地震记录,对一8层混凝土框架结构的基础隔震结构进行增量动力分析、地震易损...     

一种新型的地下含水层涌水量预测模型

针对目前电法勘探预测地下含水层单孔单位涌水量方法中存在要求大样本、易出现过学习和局部极小等缺陷,基于支持向量回归机(Support vector regression,SVR)具有小样本、推广能力强、全局最优算法等优点,又可避免现有预测模型中的过学习和推广能力差等问题.本文利用支持向量回归机模型,由电测深法观测到的电阻率和激发极化等参数建立了预测地下含水层单孔单位涌水量模型,在已知抽水试验的井孔上与以往预测模型对比表明,该预测模型不但提高了预测精度,而且还具有很好推广能力和应用前景.     

A probability-weighted moment test to assess simple scaling

We present a statistically robust approach based on probability weighted moments to assess the presence of simple scaling in geophysical processes. The proposed approach is different from current approaches which rely on estimation of high order moments. High order moments of simple scaling processes (distributions) may not have theoretically defined values and consequently, their empirical estimates are highly variable and do not converge with increasing sample size. They are, therefore, not an appropriate tool for inference. On the other hand we show that the probability weighted moments of such processes (distributions) do exist and, hence, their empirical estimates are more robust. These moments, therefore, provide an appropriate tool for inferring the presence of scaling. We illustrate this using simulated Levystable processes and then draw inference on the nature of scaling in fluctuations of a spatial rainfall process.     

A probability-weighted moment test to assess simple scaling

We present a statistically robust approach based on probability weighted moments to assess the presence of simple scaling in geophysical processes. The proposed approach is different from current approaches which rely on estimation of high order moments. High order moments of simple scaling processes (distributions) may not have theoretically defined values and consequently, their empirical estimates are highly variable and do not converge with increasing sample size. They are, therefore, not an appropriate tool for inference. On the other hand we show that the probability weighted moments of such processes (distributions) do exist and, hence, their empirical estimates are more robust. These moments, therefore, provide an appropriate tool for inferring the presence of scaling. We illustrate this using simulated Levystable processes and then draw inference on the nature of scaling in fluctuations of a spatial rainfall process.     

A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment

Abstract

Groundwater vulnerability assessment based on the DRASTIC index has been widely used since the 1980s to map potential risks of groundwater contamination. However, its applicability and usefulness are affected by two uncertain and subjective factors. One is the discretization of continuous input variables and the other is the assignment of different weights to the index variables. In this study, an entropy-weighted fuzzy-optimization approach was developed to augment and improve the classic DRASTIC method by reducing the uncertainties associated with variable discretization and weight assignment. The modified DRASTIC method was applied to a study site in Shandong, north China. The entropy-weighted fuzzy-optimization approach is shown to provide a more rigorous delineation of the relative vulnerability distribution. Meanwhile, the new approach does not require the use of more parameters. The results suggest that this approach significantly improves and enhances the ability of the classic DRASTIC method in a more systematic and rigorous way.

Editor D. Koutsoyiannis

Citation Yu, C., Zhang, B.X., Yao, Y.Y., Meng, F.H., and Zheng, C.M., 2012. A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment. Hydrological Sciences Journal, 57 (7), 1420–1432.     

Identification of heterogeneous aquifer transmissivity using an AE-based method

Determination of hydraulic head, H, as a function of spatial coordinates and time, in ground water flow is the basis for aquifer management and for prediction of contaminant transport. Several computer codes are available for this purpose. Spatial distribution of the transmissivity, T(x,y), is a required input to these codes. In most aquifers, T varies in an erratic manner, and it can be characterized statistically in terms of a few moments: the expected value, the variance, and the variogram. Knowledge of these moments, combined with a few measurements, permits one to estimate T at any point using geostatistical methods. In a review of transmissivity data from 19 unconsolidated aquifers, Hoeksema and Kitanidis (1985) identified two types of the logtransmissivity Y= ln(T) variations: correlated variations with variance sigma2Yc and correlation scale, I(Y), on the order of kilometers, and uncorrelated variations with variance sigma2Yn. Direct identification of the logtransmissivity variogram, Gamma(Y), from measurements is difficult because T data are generally scarce. However, many head measurements are commonly available. The aim of the paper is to introduce a methodology to identify the transmissivity variogram parameters (sigma2Yc, I(Y), and sigma2Yn) using head data in formations characterized by large logtransmissivity variance. The identification methodology uses a combination of precise numerical simulations (carried out using analytic element method) and a theoretical model. The main objective is to demonstrate the application of the methodology to a regional ground water flow in Eagle Valley basin in west-central Nevada for which abundant transmissivity and head measurements are available.     

Complementary use of dating and hydrochemical tools to assess mixing processes involving centenarian groundwater in a geologically complex alpine karst aquifer

Environmental dating tracers (³H, ³He, ⁴He, CFC-12, CFC-11, and SF₆) and the natural spring response (hydrochemistry, water temperature, and hydrodynamics) were jointly used to assess mixing processes and to characterize groundwater flow in a relatively small carbonate aquifer with complex geology in southern Spain. Results evidence a marked karst behaviour of some temporary outlets, with sharp and rapid responses to precipitation events, while some perennial springs show buffer and delayed variations with respect to recharge periods. The general geochemical evolution shows a pattern, from higher to lower altitudes, in which mineralization and the Mg/Ca ratio rise, evidencing longer water–rock interaction. The large SF₆ concentrations in groundwater suggest terrigenic production, whereas CFC-11 values are affected by sorption or degradation. The groundwater age in the perennial springs—as deduced from CFC-12 and ³H/³He—points to mean residence times of several decades, although the large amount of radiogenic ⁴He in samples indicate a contribution of old groundwater (free of ³H and CFC-12). Lumped parameter models and shape-free models were created based on ³H, tritiogenic ³He, CFC-12, and radiogenic ⁴He data in order to interpret the age distribution of the samples. Results evidence the existence of two mixing components, with an old fraction ranging between 160 and 220 years in age. The correlation of physicochemical parameters with some dating parameters, derived from the mixing models, serves to explain the hydrogeochemical processes occurring within the system. Altogether, long residence times are shown to be possible in small alpine systems with a clearly karst behaviour if the geological setting features highly tectonized media including units with diverse hydrogeological characteristics. These findings highlight the importance of applying different approaches, including groundwater dating techniques, when studying such groundwater flow regimes.     

利用Push-over方法评价桥梁的抗震安全性

建立了桥梁破损极限状态的定量准则,对Ｐｕｓｈ－ｏｖｅｒ方法涉及的若干技术环节,包括约束钢筋混凝土截面弯矩曲率关系、位移延性系数与曲率延性系数的关系以及评价反应谱进行了分析,并给出了一个利用Ｐｕｓｈ－ｏｖｅｒ方法评价桥梁抗震安全性的应用实例。     

配筋砌体结构地震易损性评价方法初探

本文首先简要介绍了考虑空间协同的配筋砌体结构弹塑性地震反应分析程序EDAPSC；然后提出了一种利用空间协同时程分析结果，对配筋砌体结构地震易损性进行定量评价的方法，并以上海园南小区住宅楼为例进行了地震易损性分析，说明本文提出的地震易损性评价方法是可行和合理的；另外作者还对设计人员提出了提高结构抗震安全性的建议。     

A stability analysis of the geostatistical approach to aquifer transmissivity identification

In recent years, geostatistical concepts have been applied to the inverse problem of transmissivity estimation from piezometric head data. It has been claimed that such methods overcome various difficulties encountered in other approaches. However, the reconstruction of transmissivity from head measurements is ill-posed as it depends on derivatives of the head field. Consequently, any accurate method for its solution is likely to encounter numerically ill-conditioned systems. This paper reviews the geostatistical approach, and uses the stability analyses of linear algebra to show that, as the amount of available data increases and the discretization of the system is refined, both a numerically ill-conditioned parameter estimation problem and ill-conditioned cokriging equations may appear. Therefore, while the geostatistical approach does have conceptual appeal, it does not avoid the fundamental difficulties arising out of the ill-posed nature of transmissivity identification. Instead, the method is likely to be quite sensitive to these difficulties, so care must be taken in its formulation to minimize their effects. A means to stabilize the geostatistical method is suggested and numerical experiments that highlight key points of our analysis are given.