Assessment of intrinsic vulnerability to contamination for Gaza coastal aquifer, Palestine

Gaza coastal aquifer (GCA) is the major source of fresh water for the 1.5 million residents of Gaza Strip, Palestine. The aquifer is under deteriorating quality conditions mainly due to the excessive application of fertilizers. The intrinsic vulnerability of GCA to contamination was assessed using the well-known DRASTIC method. Detailed analysis of the intrinsic vulnerability map of GCA was carried out and did consider different relationships between the vulnerability indices and the on-ground nitrogen loadings and land use classes. In addition, correlation between vulnerability values and the nitrate concentrations in GCA was studied. Based on the vulnerability analysis, it was found that 10% and 13% of Gaza Strip area is under low and high vulnerability of groundwater contamination, respectively, while more than 77% of the area of Gaza Strip can be designated as an area of moderate vulnerability of groundwater contamination. It was found that the density of groundwater sampling wells for nitrate concentration is high for the moderate and high vulnerability zones. The highest first quartile, median, mean, and third quartile of nitrate concentrations are reported in the high vulnerability zones. Results of sensitivity analysis show a high sensitivity of the high vulnerability index to the depth to water table.     

Susceptibility indexing method for irrigation water management planning: applications to K. Menderes river basin, Turkey

A susceptibility indexing method was developed based on vulnerability and quality indices. The contamination susceptibility index (SI) at a given location was calculated by taking the product of the vulnerability index (VI) and the quality index (QI): SI = VI × QI. This method incorporates both hydrogeological and hydrochemical data for a comprehensive index mapping. The DRASTIC index methodology was used for the hydrogeological data evaluations. The quality index calculation procedure based on a water quality classification scheme was introduced to evaluate hydrochemical data. The suggested susceptibility indexing method was applied to the Küçük Menderes river basin located in western Turkey. The susceptibility index map shows both hydrogeological and hydrochemical data related to the contamination problem including areas that should be taken into consideration during water management planning. The index map indicates that the most susceptible groundwater is located along the river channel between Kiraz and Tire towns, in the Selçuk area and along the Fertek stream channel to the north of Torbal? town. The results indicate that the incorporation of both hydrogeological and hydrochemical datasets enables more realistic evaluations than those of an individual dataset to estimate the groundwater contamination susceptibility of an aquifer. The numerical procedure applied could be extended further by including other parameters such as retardation, potential contaminant sources, etc. that affect the water quality in a given basin.     

Groundwater vulnerability assessment for the Banyas Catchment of the Syrian coastal area using GIS and the RISKE method

Vulnerability assessment to delineate areas that are more susceptible to contamination from anthropogenic sources has become an important element for sensible resource management and landuse planning. This contribution aims at estimating aquifer vulnerability by applying the RISKE model in Banyas Catchment Area (BCA), Tartous Prefecture, west Syria. An additional objective is to demonstrate the combined use of the RISKE model and a geographical information system (GIS) as an effective method for groundwater pollution risk assessment. The RISKE model uses five environmental parameters (Rock of aquifer media, Infiltration, Soil media, Karst, and Epikarst) to characterize the hydro-geological setting and evaluate aquifer vulnerability. The elevated eastern and low western part of the study area was dominated by high vulnerability classes, while the middle part was characterized by moderate vulnerability classes. Based on the vulnerability analysis, it was found that 2% and 39% of BCA is under low and high vulnerability to groundwater contamination, respectively, while more than 52% and 5% of the area of BCA can be designated as an area of moderate and very high vulnerability to groundwater contamination, respectively. The GIS technique has provided an efficient environment for analyses and high capabilities of handling a large amount of spatial data.     

A GIS-based DRASTIC vulnerability and net recharge reassessment in an aquifer of a semi-arid region (Metline-Ras Jebel-Raf Raf aquifer, Northern Tunisia)

This paper aims to elaborate new generic DRASTIC aquifer vulnerability maps of the coastal aquifer of Metline-Ras Jebel-Raf Raf (Northeast of Tunisia) using the GIS technique, making the data analyses easier to handle and providing better capabilities of dealing with large spatial data. A similar study was carried out in 1999 in the same aquifer using a method based on the soil water balance equation to determine the net recharge parameter. Unfortunately, the lack of data in the study area made the results unsatisfactory. By applying the Williams and Kissel equation and the Rao relationship, we intend to demonstrate that we could correctly evaluate the net recharge parameter. Moreover, new data related to the aquifer hydraulic conductivity, the soil cover and the vadose zone lithology have become available, and allowed us to elaborate suitable DRASTIC maps.     

秦皇岛沿海地下水脆弱性评价

在介绍地下水脆弱性及其评价方法的基础上，分析了秦皇岛沿海地区地下水脆弱性的影响因素。应用DRASTIC方法与GIS技术耦合的模型，对该区地下水脆弱性进行评价，并进行了脆弱性分区。     

Groundwater Vulnerability Assessment Using Fuzzy Logic: A Case Study in the Zayandehrood Aquifers, Iran

Groundwater is an important source of water, especially in arid and semi-arid regions where surface water is scarce. Groundwater pollution in these regions is consequently a major concern, especially as pollution control and removal in these resources are not only expensive but at times impossible. It is, therefore, essential to prevent their contamination in the first place by properly identifying vulnerable zones. One method most commonly used for evaluating groundwater pollution is the DRASTIC method, in which the Boolean logic is used to rank and classify the parameters involved. Problems arise, however, in the application of the Boolean logic. In this paper, the fuzzy logic has been used to avoid the problems. For this purpose, three critical cases of minimum, maximum, and mean values have been considered for the net recharge parameter. The process has been performed on the Zayandehrood river basin aquifers. The fuzzy-DRASTIC vulnerability map thus obtained indicates that the western areas of the basin generally have the maximum pollution potential followed by the areas located in the east. The central parts of the study area are found to have a low pollution potential. Finally, two sensitivity analyses are performed to show the significance of each value of the net recharge parameter in the calculation of vulnerability index.     

A GIS-BASED MODELING APPROACH FOR EVALUATING GROUNDWATER VULNERABILITY TO PESTICIDES1

ABSTRACT: The Attenuation Factor (AF), a screening model, was used to evaluate the relative degree of vulnerability of groundwater to pesticide contamination in Louisa County, Virginia. For evaluating the contamination potential of pesticides, three scenarios of pesticide leaching represented by high, moderate, and low cases of degradation and sorption in the soil were considered. Data layers were overlaid within a Geographic Information System (GIS) for spatial computation of AF for the actual and 2m groundwater depths. This spatial database was divided into five contamination potential categories namely high, medium, low, very low, and unlikely, based on the numerical values of the AF for each cell (119 ha). The results for the three most mobile pesticides are presented in this paper. The performance of the AF model was evaluated by comparing its predicted results with the field data from an experimental watershed. The AF model was able to identify most of the frequently detected pesticides in the watershed. A sensitivity analysis was also performed. The results of this study provide information about the potential groundwater threat by pesticides to the citizens ahd decision-makers in the County and can be used for formulating an appropriate land use management plan to protect the groundwater quality.     

层次分析法在环境质量评价中的不足与改进

本文针对应用层次分析法进行环境质量评价中存在的不足作了必要的改进, 并应用于环境空气质量与土壤重金属污染的评价中。评价结果表明;改进层次分析比一般层次分析法更为合理。     

Vulnerability and risk evaluation of agricultural nitrogen pollution for Hungary's main aquifer using DRASTIC and GLEAMS models

In recent years, the significant improvement in point source depuration technologies has highlighted problems regarding, in particular, phosphorus and nitrogen pollution of surface and groundwater caused by agricultural non-point (diffuse) sources (NPS). Therefore, there is an urgent need to determine the relationship between agriculture and chemical and ecological water quality.This is a worldwide problem, but it is particularly relevant in countries, such as Hungary, that have recently become members of the European Community. The Italian Foreign Ministry has financed the PECO (Eastern Europe Countries Project) projects, amongst which is the project that led to the present paper, aimed at agricultural sustainability in Hungary, from the point of view of NPS. Specifically, the aim of the present work has been to study nitrates in Hungary's main aquifer. This study compares a model showing aquifer intrinsic vulnerability to pollution (using the DRASTIC parameter method; Aller et al. [Aller, L., Truman, B., Leher, J.H., Petty, R.J., 1986. DRASTIC: A Standardized System for Evaluating Ground Water Pollution Potential Using Hydrogeologic Settings. US NTIS, Springfield, VA.]) with a field-scale model (GLEAMS; Knisel [Knisel, W.G. (Ed.), 1993. GLEAMS—Groudwater Leaching Effects of Agricultural Management Systems, Version 3.10. University of Georgia, Coastal Plain Experimental Station, Tifton, GA.]) developed to evaluate the effects of agricultural management systems within and through the plant root zone. Specifically, GLEAMS calculates nitrate nitrogen lost by runoff, sediment and leachate.Groundwater monitoring probes were constructed for the project to measure: (i) nitrate content in monitored wells; (ii) tritium (³H) hydrogen radioisotope, as a tool to estimate the recharge conditions of the shallow groundwater; (iii) nitrogen isotope ratio δ¹⁵N, since nitrogen of organic and inorganic origin can easily be distinguished.The results obtained are satisfactory, above all regarding the DRASTIC evaluation method, which is shown to satisfactorily explain both low and high aquifer vulnerability, and furthermore proves to be a good tool for zoning hydrogeological regions in terms of natural system susceptibility to pollution. The GLEAMS model, however, proves not to be immediately usable for predictions, above all due to the difficulty in finding sufficient data for the input parameters. It remains a good tool, but only after an accurate validation, for decision support systems, in the specific case to integrate intrinsic vulnerability, from DRASTIC (or similar methods), with land use nitrate loads from GLEAMS, or similar methods.The PECO project has proved a positive experience to highlight the fundamental points of a decision support system, aimed to mitigate the nitrate risk for groundwater coming from Hungarian agricultural areas.     

Reliability of groundwater vulnerability maps obtained through statistical methods

Statistical methods are widely used in environmental studies to evaluate natural hazards. Within groundwater vulnerability in particular, statistical methods are used to support decisions about environmental planning and management. The production of vulnerability maps obtained by statistical methods can greatly help decision making. One of the key points in all of these studies is the validation of the model outputs, which is performed through the application of various techniques to analyze the quality and reliability of the final results and to evaluate the model having the best performance. In this study, a groundwater vulnerability assessment to nitrate contamination was performed for the shallow aquifer located in the Province of Milan (Italy). The Weights of Evidence modeling technique was used to generate six model outputs, each one with a different number of input predictive factors. Considering that a vulnerability map is meaningful and useful only if it represents the study area through a limited number of classes with different degrees of vulnerability, the spatial agreement of different reclassified maps has been evaluated through the kappa statistics and a series of validation procedures has been proposed and applied to evaluate the reliability of the reclassified maps. Results show that performance is not directly related to the number of input predictor factors and that is possible to identify, among apparently similar maps, those best representing groundwater vulnerability in the study area. Thus, vulnerability maps generated using statistical modeling techniques have to be carefully handled before they are disseminated. Indeed, the results may appear to be excellent and final maps may perform quite well when, in fact, the depicted spatial distribution of vulnerability is greatly different from the actual one. For this reason, it is necessary to carefully evaluate the obtained results using multiple statistical techniques that are capable of providing quantitative insight into the analysis of the results. This evaluation should be done at least to reduce the questionability of the results and so to limit the number of potential choices.     

Spatially explicit sensitivity and uncertainty analysis for multicriteria-based vulnerability assessment

This research analyses the application of spatially explicit sensitivity and uncertainty analysis for GIS (Geographic Information System) multicriteria decision analysis (MCDA) within a multi-dimensional vulnerability assessment regarding flooding in the Salzach river catchment in Austria. The research methodology is based on a spatially explicit sensitivity and uncertainty analysis of GIS-CDA for an assessment of the social, economic, and environmental dimensions of vulnerability. The main objective of this research is to demonstrate how a unified approach of uncertainty and sensitivity analysis can be applied to minimise the associated uncertainty within each dimension of the vulnerability assessment. The methodology proposed for achieving this objective is composed of four main steps. The first step is computing criteria weights using the analytic hierarchy process (AHP). In the second step, Monte Carlo simulation is applied to calculate the uncertainties associated with AHP weights. In the third step, the global sensitivity analysis (GSA) is employed in the form of a model-independent method of output variance decomposition, in which the variability of the different vulnerability assessments is apportioned to every criterion weight, generating one first-order (S) and one total effect (ST) sensitivity index map per criterion weight. Finally, in the fourth step, an ordered weighted averaging method is applied to model the final vulnerability maps. The results of this research demonstrate the robustness of spatially explicit GSA for minimising the uncertainty associated with GIS-MCDA models. Based on these results, we conclude that applying the variance-based GSA enables assessment of the importance of each input factor for the results of the GIS-MCDA method, both spatially and statistically, thus allowing us to introduce and recommend GIS-based GSA as a useful methodology for minimising the uncertainty of GIS-MCDA.     

Groundwater Vulnerability Assessment for Organic Compounds: Fuzzy Multicriteria Approach for Mexico City

This study was based on a groundwater vulnerability assessment approach implemented for the Mexico City Metropolitan Area (MCMA). The approach is based on a fuzzy multicriteria procedure integrated in a geographic information system. The approach combined the potential contaminant sources with the permeability of geological materials. Initially, contaminant sources were ranked by experts through the Analytic Hierarchy Process. An aggregated contaminant sources map layer was obtained through the simple additive weighting method, using a scalar multiplication of criteria weights and binary maps showing the location of each source. A permeability map layer was obtained through the reclassification of a geology map using the respective hydraulic conductivity values, followed by a linear normalization of these values against a compatible scale. A fuzzy logic procedure was then applied to transform and combine the two map layers, resulting in a groundwater vulnerability map layer of five classes: very low, low, moderate, high, and very high. Results provided a more coherent assessment of the policy-making priorities considered when discussing the vulnerability of groundwater to organic compounds. The very high and high vulnerability areas covered a relatively small area (71 km² or 1.5% of the total study area), allowing the identification of the more critical locations. The advantage of a fuzzy logic procedure is that it enables the best possible use to be made of the information available regarding groundwater vulnerability in the MCMA.     

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.     

Quality and sustainability in the production process: A study of bakeries using an integrated multi-criteria method based on fuzzy AHP and fuzzy TOPSIS

The objective of the present study is to evaluate, determine, and apply alternatives for improving the quality of the process and the product, with an emphasis on sustainable practices, using an integrated multi-criteria method. For this purpose, an analysis was conducted at a chain of bakeries, aiming to highlight bottlenecks in the production process and in the product. With the support of a literature review, four criteria and seven alternatives were defined to overcome these bottlenecks and, at the same time, contribute to the sustainability of the organization. For data analysis, six decision makers were interviewed and, following their evaluations, an integrated method based on fuzzy AHP and fuzzy TOPSIS was created. The fuzzy AHP was adopted to establish the importance of the criteria, while the fuzzy TOPSIS was used to evaluate and classify the alternatives developed to bypass the bottlenecks. The results revealed that of the criteria, Criterion “Cr1 – Quality” was prioritized. On the other hand, the alternative with the best performance was “A3 – Physical Layout Reorganization”. Applying this alternative, the study demonstrates the results achieved such as reduction of errors and accident risks, as well as greater fluidity in the productive space. the present study also makes theoretical and managerial contributions to the field, bringing the theory closer to the reality of companies that operate in the food sector.     

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.     

Identifying crop vulnerability to groundwater abstraction: modelling and expert knowledge in a GIS

Water use is expected to increase and climate change scenarios indicate the need for more frequent water abstraction. Abstracting groundwater may have a detrimental effect on soil moisture availability for crop growth and yields. This work presents an elegant and robust method for identifying zones of crop vulnerability to abstraction. Archive groundwater level datasets were used to generate a composite groundwater surface that was subtracted from a digital terrain model. The result was the depth from surface to groundwater and identified areas underlain by shallow groundwater. Knowledge from an expert agronomist was used to define classes of risk in terms of their depth below ground level. Combining information on the permeability of geological drift types further refined the assessment of the risk of crop growth vulnerability. The nature of the mapped output is one that is easy to communicate to the intended farming audience because of the general familiarity of mapped information. Such Geographic Information System (GIS)-based products can play a significant role in the characterisation of catchments under the EU Water Framework Directive especially in the process of public liaison that is fundamental to the setting of priorities for management change. The creation of a baseline allows the impact of future increased water abstraction rates to be modelled and the vulnerability maps are in a format that can be readily understood by the various stakeholders. This methodology can readily be extended to encompass additional data layers and for a range of groundwater vulnerability issues including water resources, ecological impacts, nitrate and phosphorus.     

APPLICATION OF GEOGRAPHIC INFORMATION SYSTEMS TO GROUNDWATER MONITORING NETWORK DESIGN1

ABSTRACT: Effective monitoring configurations for contaminant detection in groundwater can be designed by analyzing the spatial relationships between candidate sampling sites and aquifer zones susceptible to contamination. Examples of such zones are the domain underlying the contaminant source, zones of probable contaminant migration, and areas occupied by water supply wells. Geographic information systems (GIS) are well-suited to performing key groundwater monitoring network design tasks, such as calculating values for distance variables which quantify the proximity of candidate sites to zones of high pollution susceptibility, and utilizing these variables to quantify relative monitoring value throughout a model domain. Through a case study application, this paper outlines the utility of GIS for detection-based groundwater quality monitoring network design. The results suggest that GIS capabilities for analyzing spatially referenced data can enhance the field-applicability of established methodologies for groundwater monitoring network design.     

Integrating the AHP and TOPSIS decision processes for evaluating the optimal collection strategy in reverse logistic for the TPI

This study presents processes to evaluate the optimal collecting strategy (CS) in reverse logistic (RL) for the downstream part of the Taiwan photovoltaic industry (TPI). It combines the analytic hierarchy process (AHP) with the technique for ordering preference by similarity to the ideal solution (TOPSIS). The criteria and sub-criteria were initially established to assess the related benefits, opportunities, costs, and risks (BOCR). AHP was then used to obtain the weightings of the criteria and sub-criteria and TOPSIS was used to rank the optimal collection strategy in terms of its overall evaluation criteria. The AHP and TOPSIS method provides decision makers with a valuable reference for assessing the optimal collection strategy of TPI downstream. The results of the study should provide decision makers in the downstream TPI with academic support and valuable guidance for evaluating their collection program and obtain optimal strategies for administering RL practices.     

SUSCEPTIBILITY OF INDIANA WATERSHEDS TO HERBICIDE CONTAMINATION1

ABSTRACT: An index of watershed susceptibility to surface water contamination by herbicides could be used to improve source water assessments for public drinking water supplies, prioritize watershed restoration projects, and direct funding and educational efforts to areas where the greatest environmental benefit can be realized. The goal of this study is to use streamflow and herbicide concentration data to develop and evaluate a method for estimating comparative watershed susceptibility to herbicide loss. United States Geological Survey (USGS) concentration data for five relatively water soluble herbicides (alachlor, atrazine, cyanazine, metolachlor, and simazine) were analyzed for 16 Indiana watersheds. Correlation was assessed between observed herbicide losses and: (1) a herbicide runoff index using GIS‐based land use, soil type, SCS runoff curve number, tillage practice, herbicide use estimates, and combinations of these factors; and (2) predicted herbicide losses from a non‐point source pollution model (NAPRA‐Web, an Internet‐based interface for GLEAMS). The highest adjusted R²value was found between herbicide concentration and the runoff curve number alone, ranging from 0.25 to 0.56. Predictions from the simulation model showed a poorer correlation with observed herbicide loss. This indicates potential for using the runoff curve number as a simple herbicide contamination susceptibility index.     

Developing the interaction matrix technique as a tool assessing the impact of traffic on air quality

This paper develops a technique which can be used as a preliminary tool for assessing air quality related to urban traffic. It combines a Geographic Information System (GIS) with an interaction matrix-type methodology based on a system analysis approach. The matrix identifies and quantifies interactions between all selected variables involved in a system as well as their interaction with the system as a whole. This matrix is used to determine the weightings to apply to spatial datasets within a GIS to develop a pollution vulnerability map. The focus of the paper is to introduce and assess a more versatile coding of the interaction matrix with respect to previously used coding. A case study is presented in which the modified interaction methodology is applied to data for a busy urban location. The resulting vulnerability map, in terms of pollution vulnerable hot spots, was compared to a pollution map derived from an advanced dispersion model. The interaction matrix technique with GIS can be used as a tool complementary to sophisticated numerical modelling and has potential as an analytical tool to evaluate multidisciplinary systems.