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     

A Method for Designing Detection Monitoring Networks in Layered Aquifers with Non-uniform Flow

An integer programming method was devised to locate detection monitoring wells in layered aquifers. The method is applicable to aquifers with non-uniform groundwater flow, and it does not require that a compliance boundary be linear or perpendicular to the direction(s) of groundwater flow. In each layer, monitoring sites are defined along curvilinear transects that parallel equipotential lines. The model can be formulated to allocate wells to the transect with the highest detection efficiency, or to establish multiple lines of defense against contaminant migrating to a compliance boundary. Detection efficiencies of alternative monitoring transects are calculated from parameters obtained via numerical modeling of contaminant transport. These parameters include the narrowest plume that could traverse a monitoring transect, and the zone width of potential contaminant migration at the transect. Problem formulations are compact, and computational requirements are low relative to alternative approaches for designing detection monitoring networks in aquifers. An application to a glacial outwash aquifer demonstrates the utility of the method.     

Prediction of groundwater contamination with multivariate regression and probabilistic capture zones

Probabilistic capture zones are combined with a regression model and used as buffer zones around wells for Tobit regression analysis to predict contaminant concentration of groundwater in an agricultural region. A backward transport equation, which is a mathematical model based on the physical processes of solute transport, is used to delineate probabilistic capture zones. The probabilistic capture zone defines the area where contaminant discharge can have a direct influence, with pertinent probability, on the quality of groundwater pumped from a well. Tobit regression analysis is used to find the relationship between independent regression variables and a dependent variable, which is contaminant concentration in this study. The capture zone and the regression are combined into a model, and its applicability for prediction of nitrate concentration is tested in a small agricultural basin in Chuncheon, Korea, which is occupied mainly by vegetation fields, orchards, and small barns. Three cases of Model 1, Model 2, and Model 3 are compared in which buffer zones are circles, capture zones with probability over 0.1, and capture zones divided into sections with different probabilities, respectively. The resulting regression model describes nitrate concentration in terms of selected independent variables. When the concentrations are calculated with the model, the best fit with the observed concentrations was in Model 3. This result supports the applicability of the method proposed in this study to prediction of contaminant concentration of groundwater.     

Optimal water quality monitoring network design for river systems

Typical tasks of a river monitoring network design include the selection of the water quality parameters, selection of sampling and measurement methods for these parameters, identification of the locations of sampling stations and determination of the sampling frequencies. These primary design considerations may require a variety of objectives, constraints and solutions. In this study we focus on the optimal river water quality monitoring network design aspect of the overall monitoring program and propose a novel methodology for the analysis of this problem. In the proposed analysis, the locations of sampling sites are determined such that the contaminant detection time is minimized for the river network while achieving maximum reliability for the monitoring system performance. Altamaha river system in the State of Georgia, USA is chosen as an example to demonstrate the proposed methodology. The results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems.     

SELECTION OF WASTE DISPOSAL SITES USING GIS1

ABSTRACT: Geographic Information Systems (GIS) technology is used to identify candidate sites for a solid waste disposal facility in the Gölbasi region of Turkey that has suffered from the negative impact of a current but poorly-located open-dump site on the environment. The municipality of Gölbasi has noticed its deleterious effect on the environment, and has thus decided to dismiss this open-dump site and search for new landfill sites. In this study, the procedure followed under a GIS framework rejects the unacceptable sites considering environmental factors exclusively, other than economic and political issues, contained in the form of multiple layers of attribute information to select the candidate sites for landfilling wastes through an overlay analysis performed by GIS software, ARC/INFO V 7.1. For the spatial data requirements of GIS, a number of thematic map layers (ground water, wetlands and swamp areas, surface water, roads, topographic contours, ecological features, settlements, erosion susceptibility zones, and soil type) are prepared in digital form. In this application, GIS is considered as a screening tool in a site selection process to narrow the number of candidate sites, subsequently leading to one or more sites for detailed investigation. Preliminary ranking for a group of potential sites is done on the basis of simple calculations coupled with on-site field studies.     

WATER QUALITY MONITORING NETWORK DESIGN: A PROBLEM OF MULTI-OBJECTIVE DECISION MAKING1

ABSTRACT: Hydrologic data network design is a fairly complicated problem where questions as to the number of gages required, time frequencies to be selected, and benefits/costs of monitoring still remain unresolved. These issues are intensified in case of water quality variables as they are more error-prone, costly, and time consuming to sample. The basic difficulty underlying the design and evaluation of monitoring systems is the lack of an objective criterion to assess: (a) the efficiency, and (b) cost-effectiveness of a network. A statistical procedure based on the entropy principle of information theory is proposed to address the evaluation of both factors. Efficiency is measured quantitatively in terms of the information produced by a network. Similarly, benefits of monitoring are described by informative measures for an objective evaluation of cost-effectiveness. The study presented demonstrates the applicability of the entropy method in assessing the efficiency and the benefits of an existing water quality monitoring network. The method is applied for temporal and spatial features of monitoring, handled as both separate and combined problems. The results are shown in the case of the highly polluted Porsuk River in Turkey. The strengths and shortcomings of the proposed methodology are discussed, with recommendations for future research on the application of the entropy principle in network design.     

Geographic information systems: a tool for strategic ground water quality management

Geographically‐related information is needed for several elements of an integrated ground water quality management programme, including ground water monitoring planning, prioritization of pollution sources, usage of permits and inspections for source control, and planning and completion of remedial actions. Geographic Information Systems (GISs) can be used to support these elements along with delineating wellhead protection areas (WHPAs), prioritizing existing contaminant sources and evaluating proposed changes in land usage in such areas. Eight case studies of the use of GISs in wellhead protection programmes are summarized, including examples from Rhode Island, Mississippi, New Jersey, New York, Pennsylvania, Kansas, Massachusetts and Texas. Six additional examples are mentioned relative to the use of GISs for evaluating ground water pollution potential, facilitating data analysis for environmental restoration of a large area with numerous waste sites, evaluating trends in ground water nitrate contamination, establishing a national database for ground water vulnerability to agricultural chemicals, simulating water table altitudes from stream and drainage basin locations, and selecting radioactive waste dump sites. The applicability of GISs and their associated advantages in wellhead protection and other ground water management studies are demonstrated via the case studies. The GIS technology provides a unique opportunity for analysing and visualizing spatial data. Contaminant and source prioritization within WHPAs is needed for both extant conditions and in the evaluation of proposed land use changes. The coupling of a GIS with contaminant/source prioritization would provide a strategic tool which could be used to plan targeted ground water monitoring programmes, to identify appropriate management or mitigation measures, minimize introduction of contaminants from existing sources into the subsurface environment, and to evaluate the potential of proposed land use activities for causing ground water contamination. GISs can be useful in providing current information for policy makers, planners and managers engaged in ground water quality decision making.     

Estimating upper percentiles of surface water monitoring data with sparse samples

The estimation of upper percentiles of chemical concentrations in surface water systems within sites and regions may be necessary for the assessment of potential risk to ecosystems and human health. Limited sample sizes at monitoring sites often limit the use of direct methods to estimate upper percentiles. In such cases, upper percentiles within regions within a time frame may be estimated by pooling data across sites and years, and then deriving percentile estimates from the pooled dataset. The method uses the observations resulting from either a known probability-sampling design or a sampling design treated like one because its observations come close to matching that of a probability-sample. These observations are then weighted to ensure that estimates are representative of a target population across all the sites within the region and the range of years in the time frame. This method of estimating upper percentiles of annual site concentration profiles is demonstrated using atrazine and validated using the monitoring data from both sparsely sampled and high-frequency water monitoring programs, where point and interval estimates of the 90th, 95th, and 99th pooled population percentiles are provided. This method shows that the pooled data from multiple sparse datasets can be used to provide estimates of near-peak concentrations with greater certainty, which are consistent with those generated by high-frequency sampling monitoring programs.     

Is Standardized Precipitation Index (SPI) a Useful Indicator to Forecast Groundwater Droughts? — Insights from a Karst Aquifer

The study sought to understand the relationships between meteorological and groundwater droughts on water levels and spring discharges in Edwards Aquifer, Texas. Standardized Precipitation Index (SPI)‐styled Standardized Groundwater Index (SGI) was used to quantify groundwater droughts. SGI time series signal was delayed and damped, while SPI was volatile. SGI values correlated well with SPI values that were observed five to eight months ago. Dynamic regression models with lagged SPI terms and autoregressive integrated moving average errors indicated a statistically significant yet weak relationship between Lag‐1 SPI and SGI. The utility of SPI for groundwater drought forecasting was minimal in this aquifer. Nonseasonal and seasonal autoregressive terms played an important role in forecasting SGI and highlighted the need for long‐term, high‐resolution monitoring to properly characterize groundwater droughts. Spring flows exhibited stronger and quicker responses to meteorological droughts than changes in storage. In aquifers with spring discharges, groundwater monitoring programs must make efforts to inventory and monitor them. Groundwater drought contingency measures can be initiated using SPI but this indicator is perhaps inappropriate to remove groundwater drought restrictions.     

Sound Survey Designs Can Facilitate Integrating Stream Monitoring Data Across Multiple Programs1

Abstract: Multiple agencies in the Pacific Northwest monitor the condition of stream networks or their watersheds. Some agencies use a stream “network” perspective to report on the fraction or length of the network that either meets or violates particular criteria. Other agencies use a “watershed” perspective to report on the health or condition of watersheds. The agencies often use the same indicators and measurement protocols for data collection and often conduct monitoring in overlapping geographic regions. In these situations, agencies would like to combine data across different monitoring studies in a statistically sound manner to make regional estimates of condition. Three statistical survey design principles will facilitate combining such studies: (1) a clearly specified statistical target population of interest, including elements that comprise the population, (2) a consistent representation of that target population (such as a digital map of the stream network and watersheds), and (3) rules that incorporate randomization to guide the selection of the sample of sites on which measurements will be made. A case study illustrates the application of these design principles using two agency monitoring programs interested in combining stream channel data for different purposes: one for making network summaries and the other for evaluating watershed condition.     

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.     

MODELING CONCENTRATION VARIATIONS IN HIGH-CAPACITY WELLS: IMPLICATIONS FOR GROUNDWATER SAMPLING1

ABSTRACT: High-capacity wells are used as a convenient and economical means of sampling groundwater quality. Although the inherent limitations of using these wells are generally recognized, little has been done to investigate how these wells actually sample groundwater. A semi-analytical particle tracking model is used to illustrate the influence of variable vertical contaminant distributions and aquifer heterogeneity on the composition of water samples from these wells during short pumping periods. The hypothetical pumping well used in the simulations is located in an unconfined, alluvial aquifer with a shallow water table and concentration gradients of nitrate-nitrogen contamination. This is a typical setting for many irrigated areas in the United States. The main conclusions are: (1) high-capacity wells underestimate the average amount of contamination within an aquifer; (2) shapes of concentration-time curves for high-capacity wells appear to be governed by the distribution of the contaminant and travel times to the well; (3) variables such as well construction, pumping rate, and hydrogeologic properties contribute to the magnitude of the concentration-time curves at individual high-capacity wells; and (4) a sampling strategy using concentration-time curves based on the behavioral characteristics of the well rather than individual samples will provide a much better framework for interpreting spatial contaminant distributions.     

Artificial Groundwater Recharge Zones Mapping Using Remote Sensing and GIS: A Case Study in Indian Punjab

Artificial groundwater recharge plays a vital role in sustainable management of groundwater resources. The present study was carried out to identify the artificial groundwater recharge zones in Bist Doab basin of Indian Punjab using remote sensing and geographical information system (GIS) for augmenting groundwater resources. The study area has been facing severe water scarcity due to intensive agriculture for the past few years. The thematic layers considered in the present study are: geomorphology (2004), geology (2004), land use/land cover (2008), drainage density, slope, soil texture (2000), aquifer transmissivity, and specific yield. Different themes and related features were assigned proper weights based on their relative contribution to groundwater recharge. Normalized weights were computed using the Saaty’s analytic hierarchy process. Thematic layers were integrated in ArcGIS for delineation of artificial groundwater recharge zones. The recharge map thus obtained was divided into four zones (poor, moderate, good, and very good) based on their influence to groundwater recharge. Results indicate that 15, 18, 37, and 30 % of the study area falls under “poor,” “moderate,” “good,” and “very good” groundwater recharge zones, respectively. The highest recharge potential area is located towards western and parts of middle region because of high infiltration rates caused due to the distribution of flood plains, alluvial plain, and agricultural land. The least effective recharge potential is in the eastern and middle parts of the study area due to low infiltration rate. The results of the study can be used to formulate an efficient groundwater management plan for sustainable utilization of limited groundwater resources.     

Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States

Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro--ethyl--(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro--(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate that variability in the concentration of atrazine residues (atrazine plus DEA) in groundwater underlying agricultural areas is more strongly controlled by the history of atrazine use in relation to the timing of recharge (groundwater age) than by processes that control the dispersion, adsorption, or degradation of these compounds in the saturated zone. Current (1990s) atrazine use was found to be a weak explanatory variable, perhaps because it does not represent the use of atrazine at the time of recharge of the sampled groundwater and because the likelihood that these compounds will reach the water table is affected by other factors operating within the unsaturated zone, such as soil characteristics, artificial drainage, and water movement. Results show that only about 5% of agricultural areas have greater than a 10% probability of exceeding the USEPA maximum contaminant level of 3.0 μg L. These models are not developed for regulatory purposes but rather can be used to (i) identify areas of potential concern, (ii) provide conservative estimates of the concentrations of atrazine residues in deeper potential drinking water supplies, and (iii) set priorities among areas for future groundwater monitoring.     

Integrated environmental monitoring and simulation system for use as a management decision support tool in urban areas

Leachates are generated as a result of water or other liquid passing through waste at a landfill site. These contaminated liquids originate from a number of sources, including the water produced during the decomposition of the waste as well as rain-fall which penetrates the waste and dissolves the material with which it comes into contact. The penetration of the rain-water depends on the nature of the landfill (e.g. surface characteristics, type and quantity of vegetation, gradient of layers, etc). The uncontrolled infiltration of leachate into the vadose (unsaturated) zone and finally into the saturated zone (groundwater) is considered to be the most serious environmental impact of a landfill. In the present paper the water flow and the pollutant transport characteristics of the Ano Liosia Landfill site in Athens (Greece) were simulated by creating a model of groundwater flows and contaminant transport. A methodology for the model is presented. The model was then integrated into the Ecosim system which is a prototype funded by the EU, (Directorate General XIII: Telematics and Environment). This is an integrated environmental monitoring and modeling system, which supports the management of environmental planning in urban areas.     

Network design for water quality monitoring of surface freshwaters: a review

To date, many water quality monitoring networks for surface freshwaters have been rather haphazardly designed without a consistent or logical design strategy. Moreover, design practices in recent years indicate a need for cost-effective and logistically adaptable network design approaches. There are many variables that need to be included in a comprehensive yet practical monitoring network: a holistic appraisal of the monitoring objectives, representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples. In order to investigate the factors which affect the development of an effective water quality monitoring network design methodology, a review of past and current approaches is presented.     

都江堰市GIS环境监测信息管理系统研究

GIS在环境中的应用越来越广泛,本文采用GIS专业软件(Maplnfo Professional 6．5)和快速软件开发平台(Delphi 7．0),并利用MapX控件技术,研制了都江堰市GIS环境监测信息管理系统。该系统具有对都江堰地表水环境、环境空气、环境噪声、工业废水等环境要素进行监测管理,同时具有都江堰市环境监测信息的空问查询、表达、统计和绘图等功能,可使都江堰市环境监测站直观、有效地进行环境监测信息管理。     

Integrating Stressor and Response Monitoring into a Resource-Based Water-Quality Assessment Framework

Following a global trend, the new policy goals emphasize the need to protect rather than to use the ability of ecosystems to recover from disturbances. This necessitates the adoption of response measurements to quantify ecological condition and monitor ecological change. Response monitoring focuses on properties that are essential to the sustainability of the ecosystem. These monitoring tools can be used to establish natural ranges of ecological change within ecosystems, as well as to quantify conceptually acceptable and unacceptable ranges of change. Through a framework of biological criteria and biological impairment standards, the results of response monitoring can become an integral part of future water resource management strategies in South Africa.     

Relationships Between Landscape Characteristics and Nonpoint Source Pollution Inputs to Coastal Estuaries

The model can help in examining the relative sensitivity of water-quality variables to alterations in land use made at varying distances from the stream channel. The model also shows the importance of streamside management zones, which are key to maintenance of stream water quality. The linkage model can be considered a first step in the integration of GIS and ecological models. The model can then be used by local and regional land managers in the formulation of plans for watershed-level management.     

Hospital site selection using fuzzy AHP and its derivatives

Environmental managers are commonly faced with sophisticated decisions, such as choosing the location of a new facility subject to multiple conflicting criteria. This paper considers the specific problem of creating a well-distributed network of hospitals that delivers its services to the target population with minimal time, pollution and cost. We develop a Multi-Criteria Decision Analysis process that combines Geographical Information System (GIS) analysis with the Fuzzy Analytical Hierarchy Process (FAHP), and use this process to determine the optimum site for a new hospital in the Tehran urban area. The GIS was used to calculate and classify governing criteria, while FAHP was used to evaluate the decision factors and their impacts on alternative sites. Three methods were used to estimate the total weights and priorities of the candidate sites: fuzzy extent analysis, center-of-area defuzzification, and the α-cut method. The three methods yield identical priorities for the five alternatives considered. Fuzzy extent analysis provides less discriminating power, but is simpler to implement and compute than the other two methods. The α-cut method is more complicated, but integrates the uncertainty and overall attitude of the decision-maker. The usefulness of the new hospital site is evaluated by computing an accessibility index for each pixel in the GIS, defined as the ratio of population density to travel time. With the addition of a new hospital at the optimum site, this index improved over about 6.5 percent of the geographical area.