华北平原地下水脆弱性评价

针对华北平原地域广阔,地貌和水文地质条件复杂、地下水开发利用程度高,地下水位埋深、包气带和含水层岩性差异性大等特点,基于大量钻孔和地下水位监测资料,厘定了包气带岩性和地下水位埋深变化对脆弱性评价影响,进而建立适宜华北平原的DRITC评价指标体系,并应用于华北平原地下水脆弱性评价。评价中,根据华北平原水文地质条件,划分4评价分区,剖分2 km×2 km单元34 253个,采用地下水位埋深、净补给量、包气带岩性、含水层累积厚度和渗透系数5个因子作为评价指标,求得地下水脆弱性综合指数及脆弱性分布图。结果表明,华北平原山前冲洪积扇和古黄河冲洪积平原的现代黄河影响带地下水脆弱性高或较高。野外采样7 472组地下水有机污染测试分析结果佐证,脆弱性高或较高区有机污染检出项数多,其他地区较少,由此验证评价结果的客观性。     

Groundwater vulnerability map of the Chrzanów karst-fissured Triassic aquifer (Poland)

A map shows intrinsic vulnerability to pollution of the Chrzanów karst-fissured aquifer (273 km²) in the southern part of Poland. This aquifer is intensively drained by numerous intakes and Zn-Pb ore mines. A DRASTIC-type parametric system was applied for groundwater vulnerability evaluation. Vulnerability assessment is based on six factors (depth to groundwater table, lithology of the unsaturated zone, net recharge, hydraulic conductivity of the aquifer, groundwater flow velocity, aquifer thickness). For the final vulnerability map construction at the scale of 1:50,000, a combination of the aquifer simulation model (using MODFLOW) and a geographical information system was applied. Maps of the net recharge, hydraulic conductivity of the aquifer and groundwater flow velocity were derived by aquifer modelling. Based on the vulnerability index (21-182), six relative vulnerability classes were selected. Reliability of the map has been verified.     

A comparative study of shallow groundwater level simulation with WA–ANN and ITS model in a coastal island of south China

Accurate and reliable prediction of shallow groundwater level is a critical component in water resources management. Two nonlinear models, WA–ANN method based on discrete wavelet transform (WA) and artificial neural network (ANN) and integrated time series (ITS) model, were developed to predict groundwater level fluctuations of a shallow coastal aquifer (Fujian Province, China). The two models were testified with the monitored groundwater level from 2000 to 2011. Two representative wells are selected with different locations within the study area. The error criteria were estimated using the coefficient of determination (R ²), Nash–Sutcliffe model efficiency coefficient (E), and root-mean-square error (RMSE). The best model was determined based on the RMSE of prediction using independent test data set. The WA–ANN models were found to provide more accurate monthly average groundwater level forecasts compared to the ITS models. The results of the study indicate the potential of WA–ANN models in forecasting groundwater levels. It is recommended that additional studies explore this proposed method, which can be used in turn to facilitate the development and implementation of more effective and sustainable groundwater management strategies.     

Sensitivity analysis of groundwater level in Jinci Spring Basin (China) based on artificial neural network modeling

Jinci Spring in Shanxi, north China, is a major local water source. It dried up in April 1994 due to groundwater overexploitation. The groundwater system is complex, involving many nonlinear and uncertain factors. Artificial neural network (ANN) models are statistical techniques to study parameter nonlinear relationships of groundwater systems. However, ANN models offer little explanatory insight into the mechanisms of prediction models. Sensitivity analysis can overcome this shortcoming. In this study, a back-propagation neural network model was built based on the relationship between groundwater level and its sensitivity factors in Jinci Spring Basin; these sensitivity factors included precipitation, river seepage, mining drainage, groundwater withdrawals and lateral discharge to the associated Quaternary aquifer. All the sensitivity factors were analyzed with Garson’s algorithm based on the connection weights of the neural network model. The concept of “sensitivity range” was proposed to describe the value range of the input variables to which the output variables are most sensitive. The sensitivity ranges were analyzed by a local sensitivity approach. The results showed that coal mining drainage is the most sensitive anthropogenic factor, having a large effect on groundwater level of the Jinci Spring Basin.     

Forecasting of groundwater level in hard rock region using artificial neural network

In hardrock terrain where seasonal streams are not perennial source of freshwater, increase in ground water exploitation has already resulted here in declining ground water levels and deteriorating its’ quality. The aquifer system has shown signs of depletion and quality contamination. Thus, to secure water for the future, water resource estimation and management has urgently become the need of the hour. In order to manage groundwater resources, it is vital to have a tool to predict the aquifer response for a given stress (abstraction and recharge). Artificial neural network (ANN) has surfaced as a proven and potential methodology to forecast the groundwater levels. In this paper, Feed-Forward Network based ANN model is used as a method to predict the groundwater levels. The models are trained with the inputs collected from field and then used as prediction tool for various scenarios of stress on aquifer. Such predictions help in developing better strategies for sustainable development of groundwater resources.     

地下水防污性能评价方法探讨

地下水防污性能评价是环境规划和决策的有用工具,国外已有许多研究,也提出了各种计算防污性能指数模型。文中着重介绍使用最广泛的DRASTIC模型,并指出其不足之处。根据中国情况,提出用DRTA模型评价潜水的防污性能,用DLCT模型评价承压含水层的防污性能。DRTA模型包含有地下水埋深、包气带评分介质、包气带评分介质的厚度和含水层厚度4 个因子;DLCT模型包含有承压含水层埋深、隔水层岩性、隔水层的连续性和隔水层厚度4个因子。     

浅层地下水氮污染的影响因素分析--以松嫩盆地松花江北部高平原为例

研究区浅层地下水中的NO-3质量浓度在时间分布上与降雨(包括降雨期、降雨量)和施肥(包括施肥期、施肥量)存在较大的相关性.同一年内9月份(丰水期末)浅层地下水中NO-3质量浓度大于5月份(枯水期末)的质量浓度.年际间总体变化趋势随年降雨量的变化而变化.在空间分布上主要受地下水水位埋深、水力坡度、含水层岩性及厚度的影响,水位埋深越大、含水层渗透性越强、水力坡度越小,浅层地下水中NO-3质量浓度增高的趋势越明显.为验证上述定性分析所得结论的可靠性,采用因子分析法对上述时空变量进行了定量评价.结果表明,研究区浅层地下水中的氮污染主要是上述时空变量共同影响的结果,其中降雨和水位埋深对其影响程度相对较大.     

Hydrochemical facies in parts of the Nigerian basement complex

 Water analyses usually involve large amounts of data that require sorting to aid in interpretation. One method that could be used is the hydrochemical facies diagrams. The hydrochemical facies of groundwater from four drainage basins of the Nigerian basement complex, Ife, Asa, Shika, and Kan Gimi, are evaluated using trilinear and Stiff diagrams similar to methods used in lithofacies and geochemical studies. The hydrochemical facies for the basins studied are influenced, aside from the lithology, by the rainfall and their proximity to the sea. In general, no single cation–anion pair exceeds 50%, hence an appreciable percentage of the groundwater in the study areas is of the nondominant type. Within the overburden aquifer of the basement complex, with limited regional flow, a rainfall of about 1150 mm per annum is arbitrarily set as the boundary between alkaline and saline groundwater. Received: 11 August 1995 · Accepted: 6 November 1995     

Hydrogeochemical characterization of major factors affecting the quality of groundwater in southern Iran,Janah Plain

The Janah alluvial aquifer is located in southern Iran with an arid climate. The type of groundwater in this aquifer is dominantly of sodium chloride and total dissolved solid of groundwater samples range from 1.63 to 335 g/L which confirms that groundwater quality has been severely degraded by salinization. Hydrogeochemical and isotopic investigations were conducted to identify the source of salinity. Total dissolved solids and major ion concentrations were measured at 51 selected sampling sites including springs, wells and surface waters. In addition stable isotopic composition (oxygen-18 and deuterium) was measured in 6 sampling points.The study indicates that the sources of salinity of the Janah aquifer include dissolution of salt diapir and evaporite rocks, a geothermal spring and intrusion of the river water which function individually or together in different parts of the aquifer. Based on the hydrogeochemical and geological studies conceptual flow models were prepared for different parts of the aquifer which illustrate how each source of salinity deteriorates the quality of the alluvial aquifer. We proposed few remediation methods including construction of cemented channel and sealed basins to improve groundwater quality. These methods would prevent infiltration of low quality water into the alluvial aquifer.     

Parallel simulation of groundwater non-point source pollution using algebraic multigrid preconditioners

The simulation of non-point source pollution in agricultural basins is a computationally demanding process due to the large number of individual sources and potential pollution receptors (e.g., drinking water wells). In this study, we present an efficient computational framework for parallel simulation of diffuse pollution in such groundwater basins. To derive a highly detailed velocity field, we employed algebraic multigrid (AMG) preconditioners to solve the groundwater flow equation. We compare two variants of AMG implementations, the multilevel preconditioning provided by Trilinos and the BoomerAMG provided by HYPRE. We also perform a sensitivity analysis on the configuration of AMG methods to evaluate the application of these libraries to groundwater flow problems. For the transport simulation of diffuse contamination, we use the streamline approach, which decomposes the 3D transport problem into a large number of 1D problems that can be executed in parallel. The proposed framework is applied to a 2,600-km² groundwater basin in California discretized into a grid with over 11 million degrees of freedom. Using a Monte Carlo approach with 200 nitrate loading realizations at the aquifer surface, we perform a stochastic analysis to quantify nitrate breakthrough prediction uncertainty at over 1,500 wells due to random, temporally distributed nitrate loading. The results show that there is a significant time lag between loading and aquifer response at production wells. Generally, typical production wells respond after 5–50 years depending on well depth and screen length, while the prediction uncertainty for nitrate in individual wells is very large—approximately twice the drinking water limit for nitrate.     

Identification of groundwater potential zones within an area with various geomorphological units by using several field parameters and a GIS approach in Kulon Progo Regency, Java, Indonesia

A case study was conducted to find the groundwater potential zones in an area between the Serang and Bogowonto rivers, Kulon Progo Regency, Java, Indonesia. The objectives of this study were to delineate the groundwater potential zone based on a number of groundwater parameters that can be surveyed in the field and to incorporate the geomorphological conditions into these data. The geomorphology interpretation was conducted using the landform approach. This approach begins by preparing supporting data such as an Indonesian Topographic Map containing contour and land use data; a regional geology map containing lithology type and geology structures; and soil, climate, and hydrological data. The determination of the geomorphology unit was conducted manually by the visual interpretation of Digital Landsat ETM⁺ with some image interpretation keys. Four groundwater parameters were surveyed in the field: (a) depth to the water table, (b) water table fluctuation, (c) fluid electrical conductivity to represent groundwater quality, and (d) aquifer thickness. The groundwater potential zones were obtained by overlaying all the groundwater field parameters in terms of weighted overlay methods using the spatial analysis tool in ArcGIS 9.2. During the weighted overlay analysis, rankings were produced for each individual parameter of each groundwater field parameter, and weights were assigned based on the amount of influence they had (i.e., depth to the water table—30 %, water table fluctuation—20 %, aquifer thickness—30 %, and fluid conductivity—20 %). We then found the good, moderate, and poor zones in terms of groundwater potential, which had areas of 5.83, 4.53, and 2.36 km², respectively. Areas with good groundwater potential are located largely within sand dunes, beach ridges, beaches, and fluviomarine plain landforms, which are characterized by a shallow water table, low fluctuation, thick aquifer, and low EC value. Moderate groundwater zones are generally characterized by poor water quality (high EC value), which is found to some degree in the alluvial plain. The regions with poor groundwater potential are spread mainly across the landforms composed of igneous rock (thin aquifers), such as denudational hills, which act as run-off zones due to their steep slope.     

Community vulnerability to hazards: introducing local expert knowledge into the equation

The accuracies of three different evolutionary artificial neural network (ANN) approaches, ANN with genetic algorithm (ANN-GA), ANN with particle swarm optimization (ANN-PSO) and ANN with imperialist competitive algorithm (ANN-ICA), were compared in estimating groundwater levels (GWL) based on precipitation, evaporation and previous GWL data. The input combinations determined using auto-, partial auto- and cross-correlation analyses and tried for each model are: (i) GWL _t?1 and GWL _t?2; (ii) GWL _t?1, GWL _t?2 and P _t ; (iii) GWL _t?1, GWL _t?2 and E _t ; (iv) GWL _t?1, GWL _t?2, P _t and E _t ; (v) GWL _t?1, GWL _t?2 and P _t?1 where GWL _t , P _t and E _t indicate the GWL, precipitation and evaporation at time t, individually. The optimal ANN-GA, ANN-PSO and ANN-ICA models were obtained by trying various control parameters. The best accuracies of the ANN-GA, ANN-PSO and ANN-ICA models were obtained from input combination (i). The mean square error accuracies of the ANN-GA and ANN-ICA models were increased by 165 and 124% using ANN-PSO model. The results indicated that the ANN-PSO model performed better than the other models in modeling monthly groundwater levels.     

Sensitivity of the Gravity Recovery and Climate Experiment (GRACE) to the complexity of aquifer systems for monitoring of groundwater

The Gravity Recovery and Climate Experiment (GRACE) satellite mission is aimed at assessment of groundwater storage under different terrestrial conditions. The main objective of the presented study is to highlight the significance of aquifer complexity to improve the performance of GRACE in monitoring groundwater. Vidarbha region of Maharashtra, central India, was selected as the study area for analysis, since the region comprises a simple aquifer system in the western region and a complex aquifer system in the eastern region. Groundwater-level-trend analyses of the different aquifer systems and spatial and temporal variation of the terrestrial water storage anomaly were studied to understand the groundwater scenario. GRACE and its field application involve selecting four pixels from the GRACE output with different aquifer systems, where each GRACE pixel encompasses 50–90 monitoring wells. Groundwater storage anomalies (GWSA) are derived for each pixel for the period 2002 to 2015 using the Release 05 (RL05) monthly GRACE gravity models and the Global Land Data Assimilation System (GLDAS) land-surface models (GWSA_GRACE) as well as the actual field data (GWSA_Actual). Correlation analysis between GWSA_GRACE and GWSA_Actual was performed using linear regression. The Pearson and Spearman methods show that the performance of GRACE is good in the region with simple aquifers; however, performance is poorer in the region with multiple aquifer systems. The study highlights the importance of incorporating the sensitivity of GRACE in estimation of groundwater storage in complex aquifer systems in future studies.     

Groundwater geochemistry of a small reservoir catchment in Central Tunisia

Due to the scarcity of water resources in semiarid sedimentary basins, hill reservoirs are often constructed to recharge groundwater and limit runoff induced water loss. The impact of such reservoirs on groundwater chemistry is investigated in the aquifers of the El Gouazine watershed, Central Tunisia. Three groundwater types are recognised, Ca–HCO₃, Na–Cl and Ca–SO₄. The strong similarity between host rock and groundwater chemistries indicates significant rock–water interaction. A flowpath, along which the chemical composition of the groundwater evolves, can be identified using the contrast in stable isotope signature between upstream and downstream groundwater. Shallow upstream groundwater is recharged by the infiltration of rainwater with the rate of recharge strongly linked to the permeability of the host lithology. Calcium and HCO₃ are supplied to an alluvial aquifer from a more rapidly recharged limestone aquifer with the concentration of Ca and HCO₃ ions decreasing by dilution. The alluvial aquifer is also enriched in Ca and SO₄ during the downstream flow of groundwater through gypsiferous materials. There is evidence of mixing between meteoric groundwater and evaporated reservoir water. Below the reservoir and partly responsible for reservoir leakage is a sandy aquifer, formed by weathering and erosion of a sandstone host which also supplies water to the alluvial aquifer.     

岩溶区地表水与地下水资源及环境统一评价的流域边界划分研究

岩溶地区地表水流域与地下水流域边界的分异形式有三类,即:地表分水岭与地下水流域边界在平面分布上基本一致;地表分水岭超出了地下水流域边界;地下水流域边界超出了地表分水岭。岩溶区地表水与地下水耦合流域的顶界为地表水流域的水面及下垫面,底界为浅循环潜水含水层或潜水—承压含水层下伏的隔水层顶面,在大厚度岩溶含水层分布区,可以弱岩溶发育带的顶面作为底界。其中地表水与地下水两个子系统间的次级边界,为地表水流域的下垫面。结合专门调查（勘查）评价和区域调查评价的特性,提出评价单元划分的原则及方法。这有助于在新一轮自然资源调查评价中,以流域为单元系统地开展水资源及环境调查评价,实行地表水和地下水资源及环境的统一管理。      

The gravity method in groundwater exploration in crystalline rocks: a study in the peninsular granitic region of Hyderabad, India

The application of variations in the earth's gravity in groundwater exploration on a regional scale, especially in sedimentary basins, metamorphic terrains, valley fills, and for buried alluvial channels, is well established. However, its use in hard crystalline rocks is little known. In granite, for example, the upper weathered layer is a potential primary aquifer, and the underlying fractured rock can form a secondary aquifer. Fracturing and weathering increases the porosity of a rock, thereby reducing the bulk density. Changes in gravity anomalies of 0.1–0.7 mGal for granites, due to weathering or variations in lithology, can be detected. To test the use of gravity as a groundwater exploration tool for crystalline rocks, a gravity survey of the peninsular shield granites underlying Osmania University Campus, Hyderabad, India, was undertaken. At the site, gravity anomalies reflect variations in the lithology and in the thickness of weathered zones. These anomalies also define the position of intrusives and lineaments. Areas of more deeply weathered granite that contain wells of higher groundwater yield are represented by negative gravity values. In the weathered zone, well yield has an inverse relation to the magnitudes of residual gravity. The study confirms the feasibility of gravity as a tool for groundwater exploration in crystalline rocks. Electronic Publication     

巴丹吉林沙漠潜水蒸发的数值模拟研究

为了确定巴丹吉林沙漠潜水蒸发强度与地下水埋深的关系,基于巴丹吉林沙漠的气候背景、砂土特征和不同地下水埋深时的典型植被特点设计了54种情景,利用Hydrus-1D建立不同情景下的SPAC水分运移模型,对周期性气象条件驱动下的潜水蒸发开展数值模拟。模拟结果表明:多年平均潜水蒸发量有着随地下水埋深增大而非线性减小的趋势;不同情景的极限埋深都大于3m,在埋深等于3m时潜水蒸发量都小于最大值的5%;当地下水埋深为0.5~1.5m时,潜水蒸发量对地下水埋深的变化最为敏感;当地下水埋深为1m时,潜水蒸发量对包气带岩性的变化也很敏感;在地下水埋深小于0.5m和大于1.5m的区间,气候、岩性、地下水埋深的变化对潜水蒸发量的影响变得微弱。另外,多年平均潜水蒸发量和地下水埋深的这种非线性关系可以用一个新提出的经验公式进行较为准确的拟合,将这个研究结果用于评价巴丹吉林沙漠湖泊集中区地下水的蒸发消耗,发现潜水蒸发总量显著大于湖面蒸发总量,前者约为后者的2.5~2.6倍,必须在沙漠水分平衡的分析中加以考虑。     

基于GIS应用DATUW模型评价地下水环境脆弱性

地下水环境脆弱性是当前地下水研究领域中的一个热点,其评价结果对于城市规划、垃圾堆放场址建设、地下水源选取与保护等具有非常重要的作用。本文是在MapGIS平台上,基于DRASTIC评价技术,选取地下水位埋深、含水层介质、地形坡度、含水层上覆地层、单井涌水量五个因子,利用DATUW模型,评价哈尔滨市区的地下水环境脆弱性。根据评价结果,将研究区的地下水环境划分为高、中、低三个脆弱性区,并就分区结果,提出了防护建议。     

GIS-based subsurface databases and 3-D geological modeling as a tool for the set up of hydrogeological framework: Nabeul–Hammamet coastal aquifer case study (Northeast Tunisia)

The subsurface data are a basic requirement for the set up of hydrogeological framework. Geographic information systems (GIS) tools have proved their usefulness in hydrogeology over the years which allow for management, synthesis, and analysis of a great variety of subsurface data. However, standard multi-layered systems are quite limited for modeling, visualizing, and editing subsurface data and geologic objects and their attributes. This paper presents a methodology to support the implementation of hydrogeological framework of the multi-layered aquifer system in Nabeul–Hammamet (NH) coastal region (NE, Tunisia). The methodology consists of (1) the development of a complete and generally accepted hydrogeological classification system for NH aquifer system (2) the development of relational databases and subsequent GIS-based on geological, geophysical and hydrogeological data, and (3) the development of meaningful three-dimensional geological and aquifer models, using GIS subsurface software, RockWorks 2002. The generated 3-D geological models define the lithostratigraphy and the geometry of each depositional formation of the region and delineate major aquifers and aquitards. Where results of the lithologic model revealed that there is a wide range of hydraulic conductivities in the modeled area, which vary spatially and control the groundwater flow regime. As well, 17 texturally distinct stratigraphic units were identified and visualized in the stratigraphic model, while the developed aquifer model indicates that the NH aquifer system is composed of multi-reservoir aquifers subdivided in aquifers units and separated by sandy clay aquitards. Finally, this study provides information on the storing, management and modeling of subsurface spatial database. GIS has become a useful tool for hydrogeological conceptualization and groundwater management purposes and will provide necessary input databases within different groundwater numerical models.