Efficient Identification of Unknown Groundwater Pollution Sources Using Linked Simulation-Optimization Incorporating Monitoring Location Impact Factor and Frequency Factor

This study aims to improve the accuracy of groundwater pollution source identification using concentration measurements from a heuristically designed optimal monitoring network. The designed network is constrained by the maximum number of permissible monitoring locations. The designed monitoring network improves the results of source identification by choosing monitoring locations that reduces the possibility of missing a pollution source, at the same time decreasing the degree of non uniqueness in the set of possible aquifer responses to subjected geo-chemical stresses. The proposed methodology combines the capability of Genetic Programming (GP), and linked simulation-optimization for recreating the flux history of the unknown conservative pollutant sources with limited number of spatiotemporal pollution concentration measurements. The GP models are trained using large number of simulated realizations of the pollutant plumes for varying input flux scenarios. A selected subset of GP models are used to compute the impact factor and frequency factor of pollutant source fluxes, at candidate monitoring locations, which in turn is used to find the best monitoring locations. The potential application of the developed methodology is demonstrated by evaluating its performance for an illustrative study area. These performance evaluation results show the efficiency in source identification when concentration measurements from the designed monitoring network are utilized.     

Artificial neural network modeling for identification of unknown pollution sources in groundwater with partially missing concentration observation data

Groundwater pollution sources are characterized by spatially and temporally varying source locations, injection rates, and duration of activity. Concentration measurement data at specified observation locations are generally utilized to identify these sources characteristics. Identification of unknown groundwater pollution sources in terms of these source characteristics becomes more difficult in the absence of complete breakthrough curves of concentration history at all the time steps. If concentration observations are missing over a length of time after an unknown source has become active, it is even more difficult to correctly identify the unknown sources. An artificial neural network (ANN) based methodology is developed to identify these source characteristics for such a missing data scenario, when concentration measurement data over an initial length of time is not available. The source characteristics and the corresponding concentration measurements at time steps for which it is not missing, constitute a pattern for training the ANN. A groundwater flow and transport numerical simulation model is utilized to generate the necessary patterns for training the ANN. Performance evaluation results show that the back-propagation based ANN model is essentially capable of extracting hidden relationship between patterns of available concentration measurement values, and the corresponding sources characteristics, resulting in identification of unknown groundwater pollution sources. The performance of the methodology is also evaluated for different levels of noise (or measurement errors) in concentration measurement data at available time steps.     

Dynamic Optimal Monitoring Network Design for Transient Transport of Pollutants in Groundwater Aquifers

Optimal groundwater pollution monitoring network design models are developed to prescribe optimal and efficient sampling locations for detecting pollution in groundwater aquifers. The developed methodology incorporates a two dimensional flow and transport simulation model to simulate the pollutant concentrations in the study area. Different realizations of the pollutant plume are randomly generated by incorporating the uncertainty in both source and aquifer parameters. These concentration realizations are incorporated in the optimal monitoring network design models. Two different objectives are considered separately. The first objective function minimizes the summation of unmonitored concentrations at different potential monitoring locations. This objective function in effect minimizes the probability of not monitoring the pollutant concentrations at those locations where the probable concentration value is large. Although this probability is not explicitly incorporated in the model, a surrogate form of this objective is included as the objective function. The second objective function considered is the minimization of estimation variances of pollutant concentrations at various unmonitored locations. This objective results in a design that chooses optimal monitoring locations where the uncertainties in simulated concentrations are large. The developed optimization models are solved using Genetic Algorithm. The variances of estimated concentrations at potential monitoring locations are computed using the geostatistical tool, kriging. The designed monitoring network is dynamic in nature, as it provides time varying network designs for different management periods, to account for the transient pollutant plumes. Such a design can eliminate temporal redundancy and is therefore, economically more efficient. The optimal design incorporates budgetary constraints in the form of limits on the number of monitoring wells installed in any particular management period. The solution results are evaluated for an illustrative study area comprising of a hypothetical aquifer. The performance evaluation results establish the potential applicability of the proposed methodology for optimal design of the dynamic monitoring network for detection and monitoring of pollutant plumes in contaminated aquifers.     

Optimal Dynamic Monitoring Network Design and Identification of Unknown Groundwater Pollution Sources

The identification of unknown pollution sources is a prerequisite for designing of a remediation strategy. In most of the real world situations, it is difficult to identify the pollution sources without a scientifically designed efficient monitoring network. The locations of the contaminant concentration measurement sites would determine the efficiency of the unknown source identification process to a large extent. Therefore coupled and iterative sequential source identification and dynamic monitoring network design framework is developed. The coupled approach provides a framework for necessary sequential exchange of information between monitoring network and source identification methodology. The preliminary identification of unknown sources, based on limited concentration data from existing arbitrarily located wells provides the initial rough estimate of the source fluxes. These identified source fluxes are then utilized for designing an optimal monitoring network for the first stage. Both the monitoring network and source identification process is repeated by sequential identification of sources and design of monitoring network which provides the feedback information. In the optimal source identification model, the Jacobian matrix which is the determinant for the search direction in the nonlinear optimization model links the groundwater flow-transport simulator and the optimization method. For the optimal monitoring network design, the integer programming based optimal design model requires as input, simulated sets of concentration data. In the proposed methodology, the concentration measurement data from the designed and implemented monitoring network are used as feedback information for sequential identification of unknown pollution sources. The potential applicability of the developed methodology is demonstrated for an illustrative study area.     

Reconstructing the release history of a groundwater contaminant based on AT123D

The reconstruction of the source release history for groundwater contamination provides useful environmental forensic information in identifying the responsible parties for a contaminant plume at a known source location if its owner changed several times in the past. The objective of this study is to develop a novel method consisting of function-fitting technique, simulated annealing, and a fundamental solution of the contaminant transport equation given in AT123D (Yeh, 1981) to recover the source release history of a groundwater contamination. AT123D is an analytical model for simulating transient, one-, two-, and three-dimensional groundwater contaminant transport in aquifer systems. The method developed herein is for recovering the release history of a continuous and finite release duration source and therefore can handle a great variety of realistic problems. Cases with various types of source geometry and aquifer configuration are considered. The influence of contaminant biodegradation, degree of dispersion, location of monitoring well, use of temporal concentration data or spatial concentration data, and presence of two contaminated sources are also investigated. Finally, a few guidelines for the optimal sampling strategy on the reconstruction of the source release history are recommended.     

Multiobjective Design of Groundwater Monitoring Network Under Epistemic Uncertainty

A methodology is proposed for optimal design of groundwater quality monitoring networks under epistemic uncertainty. The proposed methodology considers spatiotemporal pollutant concentrations as fuzzy numbers. It incorporates fuzzy ordinary kriging (FOK) within the decision model formulation for spatial estimation of contaminant concentration values. A multiobjective monitoring network design model incorporating the objectives of fuzzy mass estimation error and spatial coverage of the designed network is developed. Nondominated Sorting Genetic Algorithm-II (NSGA-II) is used for solving the monitoring network design model. Performances of the proposed model are evaluated for hypothetical illustrative system. Evaluation results indicate that the proposed methodology perform satisfactorily under uncertain system conditions. These performance evaluation results demonstrate the potential applicability of the proposed methodology for optimal groundwater contaminant monitoring network design under epistemic uncertainty.     

A groundwater perspective on the river basin management plan for central Portugal - developing a methodology to assess the potential impact of N fertilizers on groundwater bodies

The Water Framework Directive establishes that the river basin management plans must have a summary of the pressures and impacts of human activities, such as agriculture, on the chemical and quantitative status of groundwater bodies. In order to identify those areas where a potential impact from agricultural activities on groundwater bodies exists, but currently lacking groundwater monitoring data, a methodology was developed that combines the use of gross nitrogen balance values with the results of a specific vulnerability assessment index. A farm management efficiency parameter is added, to identify the factors that contribute to nitrogen use efficiency and to assess the near-future scenarios. This methodology allows the identification of significant pressures that may be responsible for a groundwater body failing good status where there is no representative monitoring network.     

对地下水动态监测工作的思考

地下水动态监测,对于水量和水质评价,以及水资源的合理开发利用,有非常重要的意义。简要说明唐山市地下水动态监测工作的现状,并以唐山市地下水动态监测工作为例,阐述地下水动态监测工作中存在的主要问题,提出解决办法,以保证地下水动态监测工作的正常顺利进行。最后,从加强地下水管理、优化地下水动态监测站网、实现自动化地下水动态监测提出一定建议。     

A nitrate biosensor based methodology for monitoring anoxic activated sludge activity.

An improved methodology based on a nitrate biosensor is developed and applied successfully for in-depth monitoring and study of anoxic activated sludge activities. The major advantages of the methodology are its simplicity, reliability and high data quality. The resulting data allowed for the first time to monitor anoxic respiration rate of activated sludge (nitrate uptake rate (NUR)) at a high time resolution making it clearly comparable with high frequency oxygen uptake rate (OUR) measurements obtained under aerobic conditions. Further, the anoxic respiration data resulting from a pulse addition of carbon source to endogenously respiring anoxic activated sludge shows a clear start-up phenomenon and storage tail that is usually also observed in high-frequency OUR measurements. Finally, the improved methodology can be expected to serve as an anoxic respirometer for activated sludge treatment plants where denitrification process occurs in single-step. Further, it can be used for a variety of purposes e.g. for toxicity and activity monitoring, process control and parameter estimation of the activated sludge process, similar to the aerobic respirometers.     

水源热泵影响下地下水温度主控因素关联度分析

为研究地下水源热泵长期影响下,地下水温度主控因素的变化特征,选择安阳市第五人民医院为研究区,将地下水温度作为典型的灰色系统进行研究,采用灰色关联度的计算方法进行地下水温度、地下水位埋深、气温、降水量以及回水井水温之间的关联度分析,获取地下水温变化的主控因素。研究结果表明:在不受水源热泵影响时,地下水位埋深是地下水温度的主控因素。在水源热泵影响下,地下水温受气温、降水量、地下水位埋深和回水井水温的共同影响:在垂向上,回水井水温对监测井水温的影响程度随着深度的增大而逐渐降低,地下水温度的主控因素由回水井水温转变为地下水位埋深,在水平方向上,回水井水温对监测井水温的影响程度随着距离的增大而逐渐减小,地下水温度的主控因素由回水井水温转变为气温和地下水位埋深。     

Estimation of Groundwater Balance Using Soil-Water-Vegetation Model and GIS

This study concerns the development of a methodology using modern techniques of data generation (Modeling) and interpretation (GIS) to compute groundwater plausibly at regional scale, alternate to previously established norms. The approach is centered on quantitative estimation of two main parameters-input and output. GIS techniques along with soil vegetation model (CropSyst) have been demonstrated for the calculation of groundwater balance components. Using the developed methodology water resources of the Ludhiana district for the period between, 2000 and 2010 were estimated. The temporal changes in water balance components indicated that the major inputs to the hydrologic system are rainfall and canal water and the major out component are evapotranspiration (ET). Multi-annual (2000 to 2010) average of 719 mm rainfall, 88 mm canal water, 74 mm of groundwater inflow, with annual loss 974 mm as ET, caused 123 mm of net negative groundwater recharge in Ludhiana district. The annual computed rise/fall with the developed methodology closely matched the observed values.     

渭河平原地下水质演化规律及评价研究

在分析渭河平原地质和水文地质条件的基础上,利用近20年地下水质监测数据,探讨了地下水水质随时间的变化规律并进行了地下水质综合评价,对其主要影响因子进行了分析。结果表明:渭河平原区域地下水质量总体尚好,秦岭山前和渭河上游局部地区水质综合评价为优良等级,渭北黄土塬部分地区及渭河下游卤泊滩地区水质综合评价为较差或极差等级;不同地区超标物质各有不同,主要超标项归纳总硬度、硫酸盐、氯化物、三氮、氟化物等;主要城市集中开采区地下水质受开采量影响较大,水位埋深与硫酸根、硝酸根、总硬度等污染物质含量高度正相关。地下水水质变化的主要影响因素为人工开采、天然背景值、局部污染、大气降水等。研究结果对渭河平原地下水水质保护及其合理开发利用有重要的意义。     

An Integrated Groundwater Management Mode Based on Control Indexes of Groundwater Quantity and Level

Groundwater is an important source of freshwater throughout the world. Due to over-exploitation of groundwater over many years, a number of potential adverse hydrogeological problems have raised. To reduce such adverse effects, it is necessary to carry out strict groundwater management in over-exploited areas. In this study, quantity-level binary control management mode has been developed in Tianjin. Initially, the management is the key to determine control levels of groundwater including the blue line levels (proper levels) and red line levels (warning levels), the blue line levels can be determined by the ground settlement recovery scenario, and the red line levels can be determined through planning groundwater exploitation scenarios. By comparing the real-time observed groundwater data with the blue levels and red levels the management grade of groundwater levels which are present, can thus be identified. Secondly, the corresponding management strategies would be determined by the management grade. On this basis reasonable groundwater levels and mining schemes can be made. Finally, the water quota for each sector can be optimized and adjusted in real time according to the binary groundwater management methodology established in this study. Thus, the exploitation of groundwater can be monitored and dynamically managed by the real-time monitoring levels and the sustainable utilization of groundwater resources can be achieved. To achieve all the objectives mentioned above, it is necessary to provide a powerful tool through the utilization of a numerical model for groundwater management. Based on geological and hydrogeological conditions in Tianjin city, a three-dimensional numerical groundwater flow model was established by coupling a one-dimensional soil consolidation model with MODFLOW model. Through calibration and verification, the model showed good simulation accuracy. It proved that the new management mode can provide a scientific basis for groundwater management.     

王赫生，李燕，周锴锷，张庆

为系统了解沙颖河流域地下水含水系统的补给源以及水化特征,在取样测试、现场监测的基础上,分别采用同位素、水文地球化学等方法,深入分析了沙颍河流域地下水含水系统特征。研究发现：沙颖河流域浅层地下水水化学类型自流域上游到下游呈HCO3-Ca+Mg型向HCO3+Cl-Ca+Mg型变化的趋势,中深层水以HCO3-Na型为主,局部呈HCO3+Cl型可能是浅层水混入的结果。采用铀不平衡方法识别地下水补给源,结果表明：浅层地下水补给源除降水外,还包括深层地下水的贡献;深层水来源包括大气降水、潜水和深层地下水3个补给源。各方法所得结论互相验证,研究结果可为流域内水循环模式研究、水污染防治等提供科学依据。     

Groundwater quality monitoring overview

A study was made to develop an approach to designing a groundwater-quality network for implementation by Mexico's Comisión Nacional del Agua (CNA) under support funding from The World Bank's (1996) PROMMA program. The network-design conceptualization and guidelines were based in part upon review of CNA's past and existing monitoring programs in measurement of water levels as well as measurements and analyses of groundwater quality. The principal focus used for this network-design framework rather was derived from identification of specific monitoring-program information needs. Also, a detailed review has been made of available reports and technical materials describing the nature, extent, and management of Mexico's groundwater resources and groundwater-quality impacts. This physical-based approach complemented a socioeconomic-based methodology being developed concurrently. Specific selection criteria and recommendations were made regarding network design components, in terms of monitoring locations, scheduling, and variables (parameters). Understandably, this preliminary design methodology, when implemented, should take into consideration somewhat realistic levels of effort that are judged to be fiscally sustainable by CNA over the near term. Moreover, some guidance also is provided in the case of fiscal or capacity-building limits of monitoring-program efforts.     

Application of Information Theory to Groundwater Quality Monitoring Networks

Using the criteria of maximizing information and minimizing cost,a methodology is developed for design of an optimal groundwater-monitoring network for water resources management. A monitoring system is essentially an information collection system. Therefore, its technical design requires a quantifiablemeasure of information which can be achieved through applicationof the information (or entropy) theory. The theory also providesinformation-based statistical measures to evaluate the efficiencyof the monitoring network. The methodology is applied to groundwater monitoring wells in a portion of Gaza Strip in Palestine.     

Groundwater Allocation Using a Groundwater Level Response Management Method—Gnangara Groundwater System, Western Australia

The Gnangara groundwater system (Gnangara system) is an important source of groundwater for Perth, Western Australia: in the order of 350 GL of groundwater is abstracted annually. The Gnangara system also sustains groundwater dependent ecosystems (GDEs), mostly wetlands and native vegetation. Declining groundwater levels across the system have led to impacts on a number of key GDEs. Western Australia’s Department of Water recently prepared a Water Management Plan for the Gnangara system. Allocation limits were reviewed as part of the plan preparation. To assist in reviewing allocation limits, an adaptive Groundwater Level Response Management (GWLRM) methodology was developed and implemented. This paper describes the methodology and its application to the Gnangara system. The methodology was developed to be used as a corrective tool for the short- and medium-term, to assist in achieving long-term sustainability of groundwater management in the context of changing climate and declining groundwater levels. The GWLRM methodology is based on groundwater storage depletion and can be applied to existing allocation limits as an interim tool to assist in making management decisions aimed at recovering groundwater resources. The key to the GWRLM correction is that it will direct water allocation towards sustainable levels on the basis of measured trends. Allocations corrected through application of the GWRLM would therefore represent interim and improved water allocation figures. GWLRM can also identify potential problem areas where the principles or calculations used for long-term sustainable groundwater allocation would need to be reviewed. For the Gnangara system, the calculated storage changes or GWLRM corrections were considered together with results of predictive modelling as part of an expert panel process to derive a more sustainable interim groundwater allocation regime while further research is being completed.     

Identification of Pollution Sources in Transient Groundwater Systems

A methodology using a nonlinear optimization model is presentedfor estimating unknown magnitude, location and duration ofgroundwater pollution sources under transient flow and transportconditions. The proposed optimization model incorporates thegoverning equations of flow and solute transport as binding equalityconstraints, and thus essentially simulates the physical processes oftransient flow and transient transport in the groundwater systems.The proposed inverse model identifies unknown sources of pollution byusing measured values of pollutant concentration at selectedlocations. Performance of the proposed model for the identificationof unknown groundwater pollution sources is evaluated for anillustrative study area in a hypothetical confined aquifer underdifferent cases of data availability. The effect of observation welllocation vis-à-vis pollution source location on identificationaccuracy is also investigated. Performance of the developedidentification model is also evaluated for a condition whenconcentration measurements are missing during few initial timeperiods after the pollution sources become active. The effect ofspecified initial guesses of the variable values on the optimalsolutions are also investigated. These performance evaluation resultsdemonstrate the limitations and potential applicability of theproposed optimization model for identifying the sources of pollutionin transient groundwater systems.     

Entropy and Multi-Objective Based Approach for Groundwater Quality Monitoring Network Assessment and Redesign

Selection of the number and location of groundwater quality monitoring wells may require the consideration of different aspects such as: monitoring objectives, temporal frequency of monitoring, and monitoring costs. These aspects were examined using observations of groundwater quality variables made twice a year in 124 wells in the northern part of the Gaza Strip, where groundwater is of the best quality. Considering these features the groundwater quality monitoring network was assessed and redesigned using entropy. The assessment procedure was based on expressing transinformation as a function of distance between wells. It was found that the number and location of groundwater quality monitoring wells varied if these aspects were embedded in the assessment and redesign procedure.     

同水源项目对地下水动态预测的影响研究

地下水资源的利用日趋成熟化,预测某一项目对地下水动态的影响时,其他同水源项目是否会对预测结果产生影响,这关系到预测的准确性。以安徽省亳州市涡阳县为例,其用水大户和农饮工程具有相同地下水供水水源,通过对比分析,探讨农饮工程对地下水的影响程度是否因用水大户取水而产生改变,为合理评价地下水资源开采提供依据。