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。     

Entropy-Based Approach to Remove Redundant Monitoring Wells from Regional-Scale Groundwater Network

An entropy-based approach is applied to identify redundant wells in the network. In the process of this research, groundwater-monitoring network is considered as a communication system with a capability to transfer information, and monitoring wells are taken as information receivers. The concepts of entropy and mutual information are then applied to measure the information content of individual monitoring well and information relationship between monitoring well pairs. The efficiency of information transfer among monitoring wells is the basis to judge the redundancy in the network. And the capacity of the monitoring wells to provide information on groundwater is the point of evaluation to identify redundant monitoring wells. This approach is demonstrated using the data from a regional-scale groundwater network in Hebei plain, China. The result shows that the entropy-based method is recommendable in optimizing groundwater networks, especially for those within media of higher heterogeneities and anisotropies.     

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。     

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.     

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。     

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。     

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.      

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。     

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.     

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.     

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。     

气压对观测井水位的影响及校正方法

地下水监测能为有效管理地下水资源提供重要信息。大气压力对观测井水位有着重要影响,正确地分析这种影响可以有效判别地下水的流向,判断含水层的性质、识别井筒存储效应（well bore storage effects）和井薄壁效应(well skin effects), 计算包气带中空气的扩散度等。随着现代化监测仪器的推广使用,高质量的监测数据为分析气压对观测井水位的影响提供了基础和保障。系统分析了不同类型含水层中井水位对大气压力的响应模式,并对校正气压对水位影响的方法进行了分析和讨论。最后,以北京平原区两口监测井为例,运用多元回归反卷积方法分析了气压对井水位的影响,并对井水位进行校正。结果表明该方法能有效地分析和校正观测井水位中的气压影响。     

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.     

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.     

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.     

Analysis of groundwater level trend in Jakham River Basin of Southern Rajasthan

Groundwater accounts for about half of the water use for irrigation in India.The fluctuation pattern of the groundwater level is examined by observing rainfall replenishment and monitoring wells.The southern part of Rajasthan has experienced abrupt changes in rainfall and has been highly dependent on groundwater over decades.This study presents the impact of over-dependence on groundwater usage for irrigation and other purposes,spatially and temporally.Hence,the objective of this study is to examine the groundwater level trend by using statistical analysis and geospatial technique.Rainfall factor was also studied in groundwater level fluctuation during 2009-2019.To analyze the influence of each well during recharge or withdrawal of groundwater,thiessien polygonswere generated from them.In the Jakham River basin,75 wells have been identified for water level trend study using the Mann-Kendall statistical test.The statistics of trend analysis show that 15%wells are experiencing water level decline in pre-monsoon,while very low percentage of wells have such trend during post-monsoon season.The average rate of water level decline is 0.245 m/a in pre-monsoon and 0.05 m/a in post-monsoon.The aquifer recharge potential is also decreasing by year.it is expected that such type of studies will help the policy makers to adopt advanced management practices to ensure sustainable groundwater resource management.     

淮北平原浅层地下水多年动态变化及监测统测评估

【研究目的】变化环境下地下水时空规律的研究有助于水资源精细化管理和区域水资源安全保障。【研究方法】本文基于淮北平原区典型气象站1953—2019年月降雨数据,采用小波分析及M-K检验法,研究多年尺度降雨周期性变化及趋势规律;结合395个国家级监测井及地下水统测数据,采用主成分分析法进行监测井优化评价。【研究结果】淮北平原多年降雨量呈现多时空尺度变化特征,南部地区主周期较北部地区偏小,但周期尺度较多,变化更为复杂;西北部的浅层地下水位持续下降,其余区域水位处于有升有降的波动状态;南部区域浅层地下水水位在1970年、2003年及2019年3个时段呈现出先降低再恢复,北部部分区域地下水水位则呈现先升高再降低的特征,研究区水位总体存在下降趋势,但2000年以来水位总体有所回升;经主成分分析优化后的277个监测井（221个水利井和56个自然资源井）能代表395个原国家监测井的总体水位变化情况。【结论】国家地下水监测工程长序列监测数据能够很好地服务于流域尺度水资源评价及管理,但省市级尺度或重点区域还需要进行优化和加密,地下水位统测可有效填补,该工作应在重要河湖两侧、淮河北岸一带、东北部山前平原等高水力梯度区域进行加密。     

昆明翠湖九龙池泉群断流原因及恢复措施

九龙池岩溶水系统分布于昆明盆地北部,岩溶含水层由蛇山裸露岩溶山区延伸至盆地底部松散土层覆盖区,在翠湖一带因上覆松散盖层薄,下游存在碎屑岩地层阻水,使地下水位壅高呈股状溢出地表,形成九龙池泉群。九龙池泉群是翠湖的源泉,也是滇池水源之一。九龙池泉群的断流,反映出滇池水环境的急剧变化。通过20世纪60年代以来地下水观测资料的分析研究,结合钻井开采地下水、工程开挖疏排地下水、地下水补给山区石漠化演化等对比评价,得出不合理的人类开发建设活动是导致九龙池泉群断流的主要原因。封停开采井、人防工程封闭止水、调水入滇池等直接或间接的措施,已经取得了明显的效果,使泉群周围地区地下水位呈现持续上升的态势。      

Groundwater recharge and discharge processes in the Jakarta groundwater basin, Indonesia

Proper management of groundwater resources requires knowledge of the processes of recharge and discharge associated with a groundwater basin. Such processes have been identified in the Jakarta groundwater basin, Indonesia using a theory that describes the simultaneous transfer of heat and fluid in a porous medium. Temperature-depth profiles in monitoring wells are used to determine the geothermal gradient. To examine the rules of groundwater flow in the distortion of the isotherms in this area, several methods are compared. Subsurface temperature distribution is strongly affected by heat advection due to groundwater flow. Under natural flow conditions, the recharge area is assumed to occur in the hills and uplands, which are located on the periphery of the Jakarta basin, and the discharge area is located in the central and northern part of the Jakarta groundwater basin. A transition area, which could act as local recharge and discharge areas, occupies the middle of the lowland. Subsurface temperatures show good correlation with the groundwater flow conditions, and the data yield important information on the location of recharge and discharge areas.