Conceptual Design of a System for Selecting Appropriate Groundwater Models in Groundwater Protection Programs

/ An effective groundwater protection program requires understanding of water flow and contaminant transport processes in the subsurface. Although many mathematical models have been developed to simulate the processes, few actually are used in groundwater protection programs due to the difficulties in data collection, model selection, and model implementation. This study presents a conceptual design of a GIS-supported model selection system that evaluates available data and mathematical models to facilitate groundwater protection programs. Steady-state groundwater and contaminant transport models applied in isotropic aquifers are placed into four classes to simulate conservative or nonconservative contaminant transports in simple or complex geohydrological conditions. After analyzing specific study objectives, available data, and model requirements, the proposed system selects a class of models that can be used in simulation and recommends any need for additional data collection. This study initiates an effort to integrate GIS, mathematical models, and expert knowledge in one system to promote the application of appropriate groundwater models. The new technology of GIS and digital data-base management makes it possible to develop such a system in practice.KEY WORDS: Groundwater models; Geographic information systems     

Approaches to Evaluate Water Quality Model Parameter Uncertainty for Adaptive TMDL Implementation1

Abstract: The National Research Council recommended Adaptive Total Maximum Daily Load implementation with the recognition that the predictive uncertainty of water quality models can be high. Quantifying predictive uncertainty provides important information for model selection and decision‐making. We review five methods that have been used with water quality models to evaluate model parameter and predictive uncertainty. These methods (1) Regionalized Sensitivity Analysis, (2) Generalized Likelihood Uncertainty Estimation, (3) Bayesian Monte Carlo, (4) Importance Sampling, and (5) Markov Chain Monte Carlo (MCMC) are based on similar concepts; their development over time was facilitated by the increasing availability of fast, cheap computers. Using a Streeter‐Phelps model as an example we show that, applied consistently, these methods give compatible results. Thus, all of these methods can, in principle, provide useful sets of parameter values that can be used to evaluate model predictive uncertainty, though, in practice, some are quickly limited by the “curse of dimensionality” or may have difficulty evaluating irregularly shaped parameter spaces. Adaptive implementation invites model updating, as new data become available reflecting water‐body responses to pollutant load reductions, and a Bayesian approach using MCMC is particularly handy for that task.     

RESEARCH INTO THE EFFECTS OF ARTIFICIAL GROUNDWATER RECHARGE,LEA VALLEY,LONDON ENGLAND1

ABSTRACT: Large-scale groundwater abstraction from the Cretaceous Chalk/Lower Tertiary Basal Sands aquifer system of the London Basin in the last 150 years has developed storage of more than 1000 Mm³. Limited operational recharge was undertaken in the 1950's encouraging further detailed study of the wider possibilities. Following a comprehensive hydrogeological reappraisal, an economic and engineering study and pilot-scale experiments, the Lea Valley has been shown to have the greatest potential for recharge. Artificial recharge into the Chalk at a rate of 9000 m³/d appears possible, through acidised 900 mm diameter boreholes. An understanding of the degree of interconnection between the Chalk and Basal Sands and of the causes of changes in quality of recharged water during storage was shown to be of particular importance to the successful operation of any recharge scheme using this system. A two-layer numerical groundwater model of the 800 km² area and a surface/groundwater simulation model have been used to assist with the design of the 84,000 m³/d prototype scheme, and will also help in assessing its efficiency. The models will ultimately be used to manage the operation of the first stage development, now coming into use.     

A Conflict-Resolution Model for the Conjunctive Use of Surface and Groundwater Resources that Considers Water-Quality Issues: A Case Study

The conjunctive use of surface and groundwater resources is one alternative for optimal use of available water resources in arid and semiarid regions. The optimization models proposed for conjunctive water allocation are often complicated, nonlinear, and computationally intensive, especially when different stakeholders are involved that have conflicting interests. In this article, a new conflict-resolution methodology developed for the conjunctive use of surface and groundwater resources using Nondominated Sorting Genetic Algorithm II (NSGA-II) and Young Conflict-Resolution Theory (YCRT) is presented. The proposed model is applied to the Tehran aquifer in the Tehran metropolitan area of Iran. Stakeholders in the study area have conflicting interests related to water supply with acceptable quality, pumping costs, groundwater quality, and groundwater table fluctuations. In the proposed methodology, MODFLOW and MT3D groundwater quantity and quality simulation models are linked with the NSGA-II optimization model to develop Pareto fronts among the objectives. The best solutions on the Pareto fronts are then selected using YCRT. The results of the proposed model show the significance of applying an integrated conflict-resolution approach to conjunctive use of surface and groundwater resources in the study area.     

Evaluating factors influencing groundwater vulnerability to nitrate pollution: developing the potential of GIS

The 1991 EU Nitrate Directive was designed to reduce water pollution from agriculturally derived nitrates. England and Wales implemented this Directive by controlling agricultural activities within their most vulnerable areas termed Nitrate Vulnerable Zones. These were designated by identifying drinking water catchments (surface and groundwater), at risk from nitrate pollution. However, this method contravened the Nitrate Directive because it only protected drinking water and not all waters. In this paper, a GIS was used to identify all areas of groundwater vulnerable to nitrate pollution. This was achieved by constructing a model containing data on four characteristics: the quality of the water leaving the root zone of a piece of land; soil information; presence of low permeability superficial (drift) material; and aquifer properties. These were combined in a GIS and the various combinations converted into a measure of vulnerability using expert knowledge. Several model variants were produced using different estimates of the quality of the water leaving the root zone and contrasting methods of weighting the input data. When the final models were assessed all produced similar spatial patterns and, when verified by comparison with trend data derived from monitored nitrate concentrations, all the models were statistically significant predictors of groundwater nitrate concentrations. The best predictive model contained a model of nitrate leaching but no land use information, implying that changes in land use will not affect designations based upon this model. The relationship between nitrate levels and borehole intake depths was investigated since there was concern that the observed contrasts in nitrate levels between vulnerability categories might be reflecting differences in borehole intake depths and not actual vulnerability. However, this was not found to be statistically important. Our preferred model provides the basis for developing a new set of groundwater Nitrate Vulnerable Zones that should help England and Wales to comply with the EU Nitrate Directive.     

Streamflow Depletion Modeling: Methods for an Adaptable and Conjunctive Water Management Decision Support Tool

Groundwater pumping depletes streamflow, which can have significant ecological impacts depending on the magnitude of depletion relative to environmental flow needs. Streamflow depletion estimates from groundwater pumping have been quantified using both analytical and numerical methods, but are not routinely compared to environmental flow needs or used in practical water management tools. Decision support tools that incorporate groundwater dynamics are becoming increasingly necessary for water managers as groundwater regulations become more important in environmental policy, particularly concerning the preservation of environmental flow needs. We develop and apply methods for a web‐based decision support tool for conjunctive groundwater and surface water management, demonstrated using a case study watershed in British Columbia, Canada. Open‐source data are analyzed with a combination of spatial algorithms and previously developed analytical models, such that the tool can be applied to other regions. Streamflow depletion estimates are calculated in four regions in the largely undeveloped Bulkley Valley, British Columbia. Our transparent methodology has geographic and data input flexibility which is a significant improvement on currently existing water management tool methods.     

Groundwater Vulnerability,Brownfield Redevelopment and Land Use Planning

An understanding of groundwater vulnerability in urban watersheds is important for the prevention of both surface water and groundwater contamination and can therefore be a useful tool in brownfield redevelopment and land use planning. Although industrial activity in southeastern Michigan has historically been restricted to the urbanized sections of metropolitan Detroit, new industrial development is rapidly taking place in rural and undeveloped areas. Although environmentalists and urban planners agree that industrial site recycling in urban centres (a.k.a. brownfield redevelopment) is preferable to developing green areas, many older sites remain undeveloped due to real and perceived risks. Using a PC-based geographic information system, a conceptual model of solute transport in soil was developed to evaluate potential impacts to both groundwater and surface water quality resulting from industrial development. The model was used to create a map of groundwater vulnerability within the Rouge River watershed of southeastern Michigan. The map has been used to pin-point several rural and undeveloped areas where groundwater quality is threatened by proposed development. It has also clearly demonstrated that many older brownfield sites, within the City of Detroit, are located on materials that have a much lower vulnerability to groundwater contamination and may therefore be far less costly to redevelop than greenfield sites in undeveloped areas of the watershed.     

Linking Riparian Dynamics and Groundwater: An Ecohydrologic Approach to Modeling Groundwater and Riparian Vegetation

The growing use of global freshwater supplies is increasing the need for improved modeling of the linkage between groundwater and riparian vegetation. Traditional groundwater models such as MODFLOW have been used to predict changes in regional groundwater levels, and thus riparian vegetation potential attributable to anthropogenic water use. This article describes an approach that improves on these modeling techniques through several innovations. First, evapotranspiration from riparian/wetland systems is modeled in a manner that more realistically reflects plant ecophysiology and vegetation complexity. In the authors’ model programs (RIP-ET and PRE-RIP-ET), the single, monotonically increasing evapotranspiration flux curve in traditional groundwater models is replaced with a set of ecophysiologically based curves, one for each plant functional group present. For each group, the curve simulates transpiration declines that occur both as water levels decline below rooting depths and as waters rise to levels that produce anoxic soil conditions. Accuracy is further improved by more effective spatial handling of vegetation distribution, which allows modeling of surface elevation and depth to water for multiple vegetation types within each large model cell. The use of RIP-ET in groundwater models can improve the accuracy of basin scale estimates of riparian evapotranspiration rates, riparian vegetation water requirements, and water budgets. Two case studies are used to demonstrate that RIP-ET produces significantly different evapotranspiration estimates than the traditional method. When combined with vegetation mapping and a supporting program (RIP-GIS), RIP-ET also enables predictions of riparian vegetation response to water use and development scenarios. The RIP-GIS program links the head distribution from MODFLOW with surface digital elevation models, producing moderate- to high-resolution depth-to-groundwater maps. Together with information on plant rooting depths, these can be used to predict vegetation response to water allocation decisions. The different evapotranspiration outcomes produced by traditional and RIP-ET approaches affect resulting interpretations of hydro-vegetation dynamics, including the effects of groundwater pumping stress on existing habitats, and thus affect subsequent policy decisions.     

REGIONAL SEWERING AND GROUNDWATER QUALITY IN THE SOUTHERN SAN JOAQUIN VALLEY1

ABSTRACT: Sewage effluent is commonly disposed of on land in arid regions, and the majority usually recharges the groundwater. Few evaluations have been made of the effect of effluent disposal on groundwater quality in the west. Groundwater hydrologists are rarely involved with treatment plant design and operation or effluent disposal in the San Joaquin Valley, California. The author's purpose is to evaluate the effect of regional sewering programs on groundwater quality in this valley. Research was conducted on past studies of sewage effluent disposal. An extensive water sampling program was undertaken near the Fresno Sewage Treatment Plant. Chloride contents were used to trace recharged effluent. The extent of recharged effluent was delineated and traced for about ten miles. Sampling between the plant and the urban Fresno area indicated a high probability of large-scale leakage of raw sewage into the groundwater.     

The effect of model structure and data in modeling land conditions in disturbed complex ecosystems

Off-road vehicles increase soil erosion by reducing vegetation cover and other types of ground cover, and by changing the structure of soil. The investigation of the relationship between disturbance from off-road vehicles and the intensity of the activities that involve use of vehicles is essential for water and soil conservation and facility management. Models have been developed in a previous study to predict disturbance caused by off-road vehicles. However, the effect of data on model quality and model performance, and the appropriate structure of models have not been previously investigated. In order to improve the quality and performance of disturbance models, this study was designed to investigate the effects of model structure and data. The experiment considered and tested: (1) two measures of disturbance based on the Vegetation Cover Factor (C Factor) of the Revised Universal Soil Loss Equation (RUSLE) and Disturbance Intensity; (2) model structure using two modeling approaches; and (3) three subsets of data. The adjusted R-square and residuals from validation data are used to represent model quality and performance, respectively. Analysis of variance (ANOVA) is used to identify factors which have significant effects on model quality and performance. The results of the ANOVA show that subsets of data have significant effects on both model quality and performance for both measures of disturbance. The ANOVA also detected that the C Factor models have higher quality and performance than the Disturbance models. Although modeling approaches are not a significant factor based on the ANOVA tests, models containing interaction terms can increase the adjusted R-squares for nearly all tested conditions and the maximum improvement can reach 31%.     

SIMULATION OF SPATIAL AND TEMPORAL CHANGES IN WATER QUALITY WITHIN A HYDROLOGIC UNIT1

Water quality must be considered in the development and planning aspects of water resource management. To accomplish this, the decision-maker needs to have at his disposal a systematized procedure for simulating water quality changes in both time and space. The simulation model should be capable of representing changes in several parameters of water quality as they are influenced by natural and human factors impinging on the hydrologic system. The objective of this work is two-fold. The first goal is to demonstrate the feasibility of developing and utilizing a water quality simulation model in conjunction with a hydrologic simulation model. The model represents water quality changes in both time and space in response to changing atmospheric and hydrologic conditions and time-varying waste discharges at various points in the system. This model has been developed from and verified with actual field data from a prototype system selected for this purpose. The second aim is to set forth procedural guidelines to assist in the development of water quality simulation models as tools for use in the quality-quantity management of a hydrologic unit.     

Air‐Water Temperature Relationships in the Trout Streams of Southeastern Minnesota's Carbonate‐Sandstone Landscape

Carbonate‐sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface‐water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater‐fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air‐water temperature relationships for 40 GWFS in southeastern Minnesota. A 40‐stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R² of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface‐water dominated streams. Regression models for streams with high R² values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater‐fed systems, but will do so at a slower rate than surface‐water dominated systems. A regression model of intercept vs. slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs. management strategies to protect trout streams.     

Testing of a GIS model ofEucalyptus Iargiflorens health on a semiarid,saline floodplain

Irrigated agriculture has resulted in substantial changes in water flows to the lower reaches of the River Murray. These changes have led to large-scale occurrences of dieback inEucalyptus largiflorens (black box) woodlands as well as increased inputs of salt to the river. Management options to address problems of this scale call for the use of spatial data sets via geographic information systems (GIS). A GIS exists for one floodplain of the River Murray at Chowilla, and a simple model predicted six health classes ofEucalyptus largiflorens based on groundwater salinity, flooding frequency, and groundwater depth.To determine the usefulness of the model for vegetation management, the quality of both the model and the GIS data sets were tested. Success of the testing procedure was judged by the degree of spatial matching between the model's predictions of health and that assessed from aerial photographs and by field truthing. Analyses at 80 sites showed that tree health was significantly greater where groundwater salinity was less than 40 dS/m or flooding occurred more frequently than 1 in 10 years or depth to groundwater exceeded 4 m. Testing of the GIS data sets found that vegetation was misclassified at 15% of sites. Association was shown between GIS-predicted values and field-truthed values of groundwater salinity but not groundwater depth. The GIS model of health is a useful starting point for future vegetation management and can be further improved by increasing the quality of the data coverages and further refining of the model to optimize parameters and thresholds.     

土壤中污染物迁移模型在油田环境影响评价中的应用

在石油的生产、运输、贮存以及炼制等过程中都存在泄油、漏油风险,各生产过程中的废弃物,如油类、重金属等各种化学物质也会危害水土环境,进而危及当地地下水源。文章分析了油田企业污染物对土壤及地下水的主要污染途径,提出了将污染物在土壤中的迁移模型用于预测污染物浓度的方法。建立了污染物由土壤迁至室内空气、地下水、农作物及由地下水转移到地表水的迁移数学模型,该模型可以运用于油田环境影响评价。     

INTEGRATION OF A BASIN-SCALE WATER QUALITY MODEL WITH GIS1

ABSTRACT: Geographic Information Systems (GIS) have been successfully integrated with distributed parameter, single-event, water quality models such as AGNPS (AGricultural NonPoint Source) and ANSWERS (Areal Nonpoint Source Watershed Environmental Response Simulation). These linkages proved to be an effective way to collect, manipulate, visualize, and analyze the input and output date of water quality models. However, for continuous-time, basin large-scale water quality models, collecting and manipulating the input data are more time-consuming and cumbersome due to the method of disaggregation (subdivisions are based on topographic boundaries). SWAT (Soil and Water Assessment Tool), a basin-scale water quality model, was integrated with a GIS to extract input data for modeling a basin. This paper discusses the detailed development of the integration of the SWAT water quality model with GRASS (Geographic Resources Analysis Support System) GIS, along with an application and advantages. The integrated system was applied to simulated a 114 sq. km upper portion of the Seco Creek Basin by subdividing it into 37 subbasins. The average monthly predicted streamflw is in agreement with measured monthly streamflw values.     

Protection strategies for drinking groundwater sources in small Quebec municipalities

Awareness of groundwater protection has increased substantially in recent decades. In the Province of Quebec, Canada, the Groundwater Catchment Regulation (GWCR) was promulgated in 2002 to protect water quality in public wells. The goal of the present study was to document groundwater protection in the context of emerging regulations and identify factors explaining the propensity of municipalities applying protection strategies. Two types of information were used in this study: data from a questionnaire-based survey conducted among 665 municipalities in the Province of Quebec and complementary information gathered from various sources. Data from the survey revealed that fewer than half of the municipalities have been able to comply with the GWCR, mainly because of financial limitations. Also, close to half of the municipalities have either identified or are expecting land use conflicts to arise between protection areas required by the GWCR and other land usage, with agriculture being the main conflicting activity. Multivariate logistic regression models served to identify factors explaining the likelihood of municipalities to take groundwater protection measures. Those factors were municipality revenue, history of water contamination in distribution systems, land use near wellheads, location of municipalities within a provincial priority watershed and the importance of groundwater use in a region. Results of the study may prove helpful for government authorities in better understanding the groundwater protection issue and in implementing strategies that improve the ability of municipalities to protect groundwater.     

Dynamic Modeling of Ground‐Water Quality Using Bayesian Techniques1

Abstract: Water industry experts have been arguing that the traditional techniques are not an accurate means of measuring water contamination. This is mainly because these techniques emphasize neither the stochastic nature of the water contamination process nor the precision and the accuracy of the tested methods used by environmental laboratories. In this work, we describe the development and application of prototype Dynamic Bayesian Networks (DBNs) that model ground‐water quality to determine the impact of chemical contaminants on ground‐water quality in the Salalah area, which is allocated to the south of Oman. We also present a new technique for data pre‐processing because it is needed for the treatment of ground‐water datasets that are used as the data source to learn the probabilities for dynamic decision models. Among more than 20 wells in area, only four wells were selected to be analyzed and the results show that we achieved an acceptable level of efficiency.     

Phreatophytic Vegetation and Groundwater Fluctuations: A Review of Current Research and Application of Ecosystem Response Modeling with an Emphasis on Great Basin Vegetation

Although changes in depth to groundwater occur naturally, anthropogenic alterations may exacerbate these fluctuations and, thus, affect vegetation reliant on groundwater. These effects include changes in physiology, structure, and community dynamics, particularly in arid regions where groundwater can be an important water source for many plants. To properly manage ecosystems subject to changes in depth to groundwater, plant responses to both rising and falling groundwater tables must be understood. However, most research has focused exclusively on riparian ecosystems, ignoring regions where groundwater is available to a wider range of species. Here, we review responses of riparian and other species to changes in groundwater levels in arid environments. Although decreasing water tables often result in plant water stress and reduced live biomass, the converse is not necessarily true for rising water tables. Initially, rising water tables kill flooded roots because most species cannot tolerate the associated low oxygen levels. Thus, flooded plants can also experience water stress. Ultimately, individual species responses to either scenario depend on drought and flooding tolerance and the change in root system size and water uptake capacity. However, additional environmental and biological factors can play important roles in the severity of vegetation response to altered groundwater tables. Using the reviewed information, we created two conceptual models to highlight vegetation dynamics in areas with groundwater fluctuations. These models use flow charts to identify key vegetation and ecosystem properties and their responses to changes in groundwater tables to predict community responses. We then incorporated key concepts from these models into EDYS, a comprehensive ecosystem model, to highlight the potential complexity of predicting community change under different fluctuating groundwater scenarios. Such models provide a valuable tool for managing vegetation and groundwater use in areas where groundwater is important to both plants and humans, particularly in the context of climate change.     

RECYCLING INPUT DATA DURING ANALYTIC ELEMENT MODELING NEAR INDIANAPOLIS,INDIANA1

ABSTRACT: Overlapping and adjacent ground water investigations are common in areas where aquifers are threatened by industrial development. In the Indianapolis area in Marion County, Indiana, a patchwork of ground water flow models have been used during the past 20 years to evaluate ground water resources and to determine the effects of local contamination. In every case these ground water models were constructed from scratch. Site specific finite difference grids or finite element meshes inhibit the direct reuse of input data when the area of interest shifts. Because the aquifer is not discretized into a grid or mesh with analytic element models, there are unique opportunities for direct reuse of model input data. In two applications of this principle we illustrate how the newly emerging analytic element method allows a fairly straightforward reuse of model input data from previous models in the same general area. In analytic element models of Central Indiana, streams and their tributaries are represented in different resolutions. Input data items of several modeling studies are stored and cataloged on disk in such a manner that they can be selectively retrieved by a data management program PREPRO. In this manner, a new ground water model can be set up quickly with input data which have been previously defined and tested during model calibration.