Evaluation of groundwater monitoring network of Kodaganar River basin from Southern India using entropy

A discrete entropy-based approach is used to assess the groundwater monitoring network that exists in Kodaganar River basin of Southern India. Since any monitoring system is essentially an information collection system, its technical design and evaluation require a quantifiable measure of information and this measure can be derived using entropy. The use of information-based measures of groundwater table shows that the existing monitoring network contains a sufficient number of wells but is not well designed for the measurement of groundwater level. Entropy-based results show that 15 wells are vital to measure regional groundwater level, not 28 wells which are being monitored effectively in this basin.     

应用信息熵方法对区域地下水观测网的优化研究

数据冗余是观测网优化需要解决的主要问题之一, 冗余数据既造成数据噪音又增加观测网运行成本.减少数据冗余的主要手段是减少观测孔的数量, 但前提是不影响原有观测网提供信息的能力.作者基于信息熵概念和随机技术的结合, 提出了一种优化观测孔数量的方法, 这种方法的基本原理是利用信息熵理论来评价每一个观测孔数据信息含量大小, 计算观测网中每一对观测孔之间的信息流交换, 并建立观测孔之间信息传递与距离的统计关系, 这种关系是判断冗余性观测孔的基础.这种方法被用来优化河北平原区域地下水观测网, 不仅解决了数量问题, 同时也可确定具体冗余性观测孔.最后结果对比证明, 将河北平原地下水观测孔的数量减少2 6%, 几乎没有影响现有观测网提供数据信息的能力.      

Spatial assessment and redesign of a groundwater quality monitoring network using entropy theory, Gaza Strip, Palestine

Using entropy theory, a methodology was developed for the evaluation and redesign of groundwater quality monitoring wells in the Gaza Strip in Palestine. Essential to the methodology is the development of a Transinformation Model (TM) which yields the amount of information transfer and the dependency between the wells as a function of distance. The TM parameters, such as the minimum transinformation and the range, were employed for evaluating the network which revealed that most of the distances between wells were less than the range. It also indicated that a high percentage of redundant information existed in the network. Therefore, the network was reduced by superimposing a square pattern over the monitored area and selecting one well per square block in a stratified pattern. The methodology was tested using the chloride data collected from 1972–2000 from 417 groundwater quality monitoring wells in the Gaza Strip. The number of the groundwater quality monitoring wells in the Gaza Strip was reduced by 53%, while there was 26% redundant information based on the minimum existing distance between wells. This methodology is meant to help monitor the groundwater quality (salinity) in the Gaza Strip.     

Designing an optimal multivariate geostatistical groundwater quality monitoring network using factorial kriging and genetic algorithms

The optimal selection of monitoring wells is a major task in designing an information-effective groundwater quality monitoring network which can provide sufficient and not redundant information of monitoring variables for delineating spatial distribution or variations of monitoring variables. This study develops a design approach for an optimal multivariate geostatistical groundwater quality network by proposing a network system to identify groundwater quality spatial variations by using factorial kriging with genetic algorithm. The proposed approach is applied in designing a groundwater quality monitoring network for nine variables (EC, TDS, Cl⁻, Na, Ca, Mg, SO ₄ ²⁻ , Mn and Fe) in the Pingtung Plain in Taiwan. The spatial structure results show that the variograms and cross-variograms of the nine variables can be modeled in two spatial structures: a Gaussian model with ranges 28.5 km and a spherical model with 40 km for short and long spatial scale variations, respectively. Moreover, the nine variables can be grouped into two major components for both short and long scales. The proposed optimal monitoring design model successfully obtains different optimal network systems for delineating spatial variations of the nine groundwater quality variables by using 20, 25 and 30 monitoring wells in both short scale (28.5 km) and long scale (40 km). Finally, the study confirms that the proposed model can design an optimal groundwater monitoring network that not only considers multiple groundwater quality variables but also monitors variations of monitoring variables at various spatial scales in the study area.     

应用信息熵方法对地下水观测网的层次分类——以河北平原地下水观测网为例

本文主要针对目前地下水观测网存在的层次不清问题，提出了基于信息熵理论新的分类方法。文章列举了观测网层次问题的表现，原因和可能造成的后果，提出地下水观测网的层次性应该对应地下水流动系统的层次性。认为地下水观测网就是一种信号通讯网，水位信号具有可传递性、差异性以及衰减性等特征，可以运用信息熵理论中的互信息概念，定量刻画观测孔之间的信息联系，并以这种信息联系程度作为观测孔层次分类的主要依据。作者以河北平原地下水观测网为实例，研究了区域尺度观测网的分类，结果表明信息熵方法可以很好地解决此类问题。     

http://www.sciencedirect.com/science/article/pii/S1674987112000400

Monitoring of regional groundwater levels provides important information for quantifying groundwater depletion and assessing impacts on the environment Historically,groundwater level monitoring wells in Beijing Plain,China,were installed for assessing groundwater resources and for monitoring the cone of depression.Monitoring wells are clustered around well fields and urban areas.There is urgent need to upgrade the existing monitoring wells to a regional groundwater level monitoring network to acquire information for integrated water resources management.A new method was proposed for designing a regional groundwater level monitoring network.The method is based on groundwater regime zone mapping.Groundwater regime zone map delineates distinct areas of possible different groundwater level variations and is useful for locating groundwater monitoring wells.This method was applied to Beijing Plain to upgrade a regional groundwater level monitoring network.     

基于信息熵技术对地下水观测网的层次分类--以河北平原地下水观测网为例

针对目前地下水观测网存在的层次不清问题，提出了基于信息熵技术的新的分类方法。列举了观测网层次混乱问题的表现、原因和可能造成的后果，提出地下水观测网具有层次性，而且这种层次性必须与地下水流动系统的层次性对应；认为地下水观测网就是一种信号通讯网，水位信号具有可传递性、差异性以及衰减性等特征，可以运用信息熵理论中的互信息概念定量刻画观测孔之间的信息联系，并以这种信息联系程度作为观测孔层次分类的主要依据；以河北平原地下水观测网为例，研究了区域尺度和局部尺度观测网的分类，结果表明信息熵方法可以很好地解决此类问题。     

Identifying influencing wells for gradient estimation in the confined portion of the Gulf Coast aquifer near Kingsville,TX

Hydraulic gradient is a fundamental aquifer characteristic required to estimate groundwater flow and quantify advective fluxes of pollutants. Graphical and local estimation schemes using potentiometric head information from three or four wells are used to compute hydraulic gradients but suffer from imprecision and subjectivity. The use of linear regression is recommended when hydraulic head data from a groundwater monitoring network consisting of several wells are available. In such cases, statistical influence analysis can be carried out to evaluate how each well within the network impacts the gradient estimate. A suite of five metrics, namely—(1) the hat-values, (2) studentized residuals, (3) Cook’s distance, (4) DFBETAs and (5) Covariance ratio (COVRATIO) are used in this study to identify influential wells within a regional groundwater monitoring network in Kleberg County, TX. The hat-values indicated that the groundwater network was reasonably well balanced and no well exerted an undue influence on the regression. The studentized residuals and Cook’s distance indicated the wells with the highest influence on the regression predictions were those that were close to high groundwater production centers or affected by coastal-aquifer interactions. However, the wells in the proximity of the production centers had the highest impact on the estimated gradient values as ascertained using DFBETAs. The covariance ratio which indicates the sensitivity of a monitoring well on the estimated standard error of regression was noted to be significant at most wells within the network. Therefore, networks seeking to address changes in groundwater gradients due to climate and anthropogenic influences need to be denser than those used to ascertain synoptic gradient estimates alone. The magnitude of the groundwater velocity was greatly underestimated when the influential wells were excluded from the network. The direction of flow was affected to a lesser extent, but a complete gradient reversal was noted when the network consisted of only four peripheral wells. The influence analysis therefore provides a valuable tool to assess the importance of individual wells within a monitoring network and can therefore be useful when existing networks are to be pruned due to fiscal constraints.     

塔里木与扬子新元古代热-构造事件特征、序列和时代——扬子与塔里木连接(YZ-TAR)假设

淄博市大武水源地是中国北方罕见的特大型岩溶-裂隙地下水水源地,地下水开采量为52×10~4m~3/d。为了对岩溶地下水进行有效监测,需要建立最优的地下水监测网。文中在对岩溶地下水流系统分析的基础上,建立了地下水流系统确定性-随机性数学模型,运用有限元与卡尔曼滤波耦合的模拟递推算法,对大武水源地地下水监测网进行了优化设计,结果显示:现有地下水位动态监测网难以达到监测目标,最优地下水位监测网由14个监测井,每月监测一次的监测频率组成,比现有地下水位监测网减少了2个监测井。     

北京平原地下水水位监测网优化

文章在北京市地下水水位监测现状基础上,分潜水和承压水对北京平原地下水监测网的监测密度和监测频率进行了优化设计。主要采用编制地下水动态类型图的方法进行了地下水水位监测网的优化,克里金插值法能定量评价依据监测网观测值绘制的地下水水位等高线的精度,因而可以用来评价监测优化结果。并根据时间序列分析和统计检验提供的定量标准优化了地下水水位监测频率。优化后,北京平原共有监测孔400眼,其中利用原有监测孔300眼,新设计监测孔100眼,手工监测频率由原来的每月6次优化为每月1次,专项高频率监测可以由地下水自动监测仪实现。文中还对地下水自动监测仪(DIVER)的监测结果和手工监测结果进行了对比评价,提出了地下水水位监测网的维护、管理措施和信息发布方式。     

区域地下水位监测网优化设计方法

区域地下水位监测提供了定量评价含水层地下水位持续下降及其对环境影响必不可少的信息。历史上的地下水位监测网是为了评价地下水资源或监测水源地降落漏斗而设立的,目前它们已经不能适应为流域水资源综合管理提供必需的信息。本文在综述国际地下水位监测现状的基础上,介绍了区域地下水位监测网优化设计的方法。采用地理信息系统编制的地下水动态类型图为地下水位监测井位置的选择提供了坚实的水文地质基础;克里金插值法能定量评价监测网观测值绘制的地下水位等高线的精度,因而可以用来定量设计地下水位监测网;时间序列分析和统计检验提供了优化地下水位监测频率的定量标准。这些方法已被应用于北京平原、乌鲁木齐河流域和济南岩溶泉域,其成果将在本刊分期发表。     

Delaunay方法的改进及其在地下水污染监测网设计中的应用

地下水污染监测网的设计包括取样点在空间上的采样位置和时间上的取样频率这两方面的确定,其目的是为了准确刻画污染羽在含水层中随时间的变化状况。介绍了一种新的基于Delaunay三角形剖分方法用于地下水污染监测网在空间上的去冗余设计。同时,针对Delaunay方法没有考虑含水层参数变化和不能新增必要监测点的缺陷,提出了改进措施。改进的Delaunay方法可以直接与污染物的运移模型耦合,通过获取的含水层参数能够比较好地检验监测网在空间上的去冗余设计效果。实例研究表明,该方法在保证监测精度的基础上,能够找到最优的空间取样位置点,同时与改进前相比,利用该方法得到的地下水污染监测网能更加客观地反映污染物在含水层中的空间分布特征。     

Optimal design of a groundwater monitoring network in Daqing,China

In the Daqing region of China there are 34 groundwater well fields with a groundwater withdrawal of 81.9×10⁴ m³/d. Due to over-abstraction of the groundwater resources from the 1960s to present, a cone of depression up to 4,000 km² has formed in the area. To monitor the change in the groundwater environment, it is necessary to design an effective groundwater-monitoring network. The sites for monitoring groundwater level were selected by applying the finite-element method coupled with Kalman filtering to the area in which the groundwater resources have been extensively exploited. The criterion is a threshold value of the standard deviation of estimation error. This threshold value is determined by the tradeoff between maximum information and minimum cost, in which the maximum information is characterized by the standard deviation and the minimum cost is equivalent to the number of observation wells. The groundwater flow model was calibrated by an optimal algorithm coupled the finite-element method with Kalman filtering by using the data from 16 observation wells from 1986 to 1993. A simulation algorithm coupled with the finite-element method with Kalman filtering analyzed the location data obtained from the existing 38 observation wells in the same region. The spatial distribution of standard deviation of estimation error is computed and the locations that have the maximum standard deviation are selected as additional sites for augmenting the existing observational well network at a given threshold value of the standard deviation surface. Based on the proposed method for selecting a groundwater level monitoring network, an optimal monitoring network with 88 observation wells with the measurement frequency of 12 times per year is selected in the Daqing region of China.     

On the equivalence of kriging and maximum entropy estimators

This study compares kriging and maximum entropy estimators for spatial estimation and monitoring network design. For second-order stationary random fields (a subset of Gaussian fields) the estimators and their associated interpolation error variances are identical. Simple lognormal kriging differs from the lognormal maximum entropy estimator, however, in both mathematical formulation and estimation error variances. Two numerical examples are described that compare the two estimators. Simple lognormal kriging yields systematically higher estimates and smoother interpolation surfaces compared to those produced by the lognormal maximum entropy estimator. The second empirical comparison applies kriging and entropy-based models to the problem of optimizing groundwater monitoring network design, using six alternative objective functions. The maximum entropy-based sampling design approach is shown to be the more computationally efficient of the two.     

河套平原浅层地下水动态监测网优化设计

河套平原的地下水动态监测网存在监测井空间布局不合理的问题,限制了地下水研究工作的进一步深入.采用水文地质分析法和克里金插值法,并结合实际情况对河套平原的浅层地下水监测网络进行了优化设计.地下水动态影响因素分区图的编制主要考虑了地貌、包气带岩性、浅水位埋深、含水层渗透系数、年均降水量、年均蒸发量以及地下水开采模数7个因子.结果表明,优化设计的监测网共有监测井428眼,优化后Kriging插值误差标准差为2.53~10.99 m,比优化前(2.75~27.00 m)显著降低,这说明优化设计的监测网精度有很大提高.此外,优化后的监测网不仅能够对河岸带、断裂带、咸淡水交互带、地下水降落漏斗区等关键地段的水位实施监测,还能够满足不同地区对监测井密度的需求,具有一定的参考和实践价值.     

乌鲁木齐河流域地下水水质监测网设计

文章运用地下水易污性编图及污染源分布图法进行了乌鲁木齐河流域地下水水质监测网设计。共设计了130监测孔,现有46个监测孔,另需要84个新的监测孔。按监测类型分为面源监测点22个,点源监测点87个,重点水源地与泉水监测点21个。按监测运行分长期监测点55个,流域普查监测点75个。普查监测点监测频率为1次/5年,长期监测点监测频率为1次/年。首期有针对性地在污染严重的柴窝堡新化厂排污区、乌鲁木齐河谷老排污区、米泉污灌区、米泉工业污染区、老龙河污染区取了25个污染水样测试分析,结果显示地下水已经受到严重污染。     

鄯善县地下水监测网优化研究

分析鄯善县地下水监测网的现状和存在的问题,用水文地质分析法对现有监测网进行优化。根据存在地下监测井太少且局部监测井偏大,提出优化方案封堵原有两眼监测井,保留原有16眼监测井,新增加51眼监测井。     

A statistical power analysis approach to estimate groundwater-monitoring network size in Victoria County Groundwater Conservation District,Texas

A properly designed groundwater-monitoring network is critical to evaluate groundwater management policies and regulations and establish a scientifically credible, risk-informed approach towards management of aquifer resources. To achieve proper design, the network must comprise a sufficient number of wells that comprehensively covers the area of interest. In this study, statistical power analysis is utilized to define the size of a proposed monitoring network within the Victoria County Groundwater Conservation District (VCGCD). In particular, the network seeks to provide empirical information to evaluate whether the VCGCD is meeting the criteria of the desired future conditions (DFC) established by the Groundwater Management Area 15 (GMA 15) through the joint planning process, as required by the statutes of Texas. The evaluation of DFCs is expressed as a hypothesis-testing problem with the null hypothesis stating that the VCGCD complies with the DFC, and the alternative hypothesis stating that the VCGCD does not comply with the DFC. The power analysis quantifies the ability of the statistical test to correctly reject the null hypothesis. The power of the statistical test is a function of the sample size and this relationship can be exploited to determine the size of the required groundwater-monitoring network if the effect size can be specified. However, prior to establishing a monitoring network, the groundwater level monitoring tends to be ad hoc; therefore, the statistical moments required for characterizing the effect size are not likely to be known with a high degree of certainty. As such, an innovative framework that integrates power analysis with bootstrap resampling protocols was developed to estimate monitoring network size under uncertainty. The results of the study indicated that a minimum set of approximately 70 wells is required within the VCGCD to statistically evaluate the compliance with DFCs with 90 % reliability and at a significance level of 10?% and 90 % power. The number of wells increased to about 85 when the significance level was reduced to 5 %. Geostatistical analysis indicated that these monitoring wells must be at least 3 miles apart to ensure statistically independent information. The developed methodology provides a practical framework to size a groundwater-monitoring network under data sparse situations.     

宁夏地下水监测现状调查及对策

[目的]针对地下水监测存在问题,提出改进地下水监测工作的对策和建议。[方法]调查地下水监测历史沿革及现状,理出存在主要问题,研究应对策略。[结果]宁夏地下水监测范围小,监测层位浅,监测井标准低老化严重,井网布局和监测项目与面临任务不适应,难以满足地下水管理与开发保护要求,亟需完善地下水监测井网。[结论]做好宁夏地下水监测站网总体规划,建立稳定资金投入机制,加强与国土部门合作,逐年完善地下水监测站网,是做好地下水监测工作主要举措。     

乌鲁木齐河流域地下水水位监测网设计

文章阐述了乌鲁木齐河流域区域地下水水位监测网的优化设计。基于ARCGIS技术,运用水文地质学方法在叠加合成地下水动态类型分区图的基础上优化设计了区域地下水水位监测网密度;采用时间序列分析方法确定了地下水水位监测频率。首期施工安装了11个新的长期专门监测孔;对73个现有监测孔进行了维修并安装了孔口保护装置,安装了28套水位自动监测仪,初步实现了地下水水位的自动监测。