Evaluating the effects of spatial monitoring policy on groundwater quality portrayal

What size sample is sufficient for spatially sampling ambient groundwater quality? Water quality data are only as spatially accurate as the geographic sampling strategies used to collect them. This research used sequential sampling and regression analysis to evaluate groundwater quality spatial sampling policy changes proposed by California's Department of Water Resources. Iterative or sequential sampling of a hypothetical groundwater basin's water quality produced data sets from sample sizes ranging from 2.8% to 95% coverage of available point sample sites. Contour maps based on these sample data sets were compared to an original (control), mapped hypothetical data set, to determine at which point map information content and pattern portrayal are not improved by increasing sample sizes. Comparing series of contour maps of ground water quality concentration is a common means of evaluating the geographic extent of groundwater quality change. Comparisons included visual inspection of contout maps and statistical tests on digital versions of these map files, including correlation and regression products. This research demonstrated that, down to about 15% sample site coverage, there is no difference between contour maps produced from the different sampling strategies and the contout map of the original data set.     

Groundwater risk assessment at a heavily industrialised catchment and the associated impacts on a peri-urban wetland

Industrial and agricultural activities often impose significant pressures to the groundwater quality and consequently degrade wetland ecosystems that depend mostly on subsurface water flow. Groundwater vulnerability and risk mapping is a widely used approach to assess the natural protection of aquifers and the associated pollution potential from human activities. In the particular study, the relatively new Pan-European methodology (COP method) has been applied in a highly industrialized peri-urban wetland catchment, located close to Athens city, to map the intrinsic vulnerability of the aquifer and evaluate the risk potential originating from local land uses. Groundwater analysis results for various parameters, including Phenols, PCBs and nutrients, have been used to validate the vulnerability and risk estimations while a biological assessment occurred to associate the mapping results with the wetland's ecological status. The results indicated that even though the natural protection of the aquifer is relatively high due to the dominant hydrogeologic and geomorphologic conditions, the groundwater pollution risk is considerable, mainly because of the existing hazardous land uses. The water quality of the groundwater accredited these findings and the ecological status of this peri-urban wetland also indicated significant impacts from industrial effluents.     

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.     

Impact of mining industries on the groundwater level fluctuation in Singrauli coalfield area by using remote sensing and GIS,India

The coal mining industries influence hydro-geological parameters, which affect the aquifer recharge in the coal mining areas. This research aimed to evaluate the impact of various hydro-geological parameters on fluctuation of groundwater level in the study area. The various hydro-geological parameters such as soil, geology, drainage pattern, elevation and slope have been considered to accomplish the objective. A comparative analysis was performed by comparing the groundwater level fluctuation (WLF) map with the GIS-based various hydro-geological parameter maps to assess the combined influence of different hydro-geological parameters on groundwater level fluctuation. A total of eighty-six (86) dug-wells were chosen to monitor the level of the groundwater for around ten blocks of Singrauli coalfield, and these wells were examined during the months of dry and wet seasons for 2016. Based on the comparative analysis between the WLF map and thematic maps of various hydro-geological parameters, it has been found that WLF in the south-western and some portions of the north-eastern showed moderate to a higher value. This may be because most of the non-hilly areas come under gentle to moderate slope category, with lower elevation in the area forming the suitable hydro-geological condition for recharging groundwater. It was observed that the northwest, south-east and central part of the study area showed lower WLF, which may be due to the presence of overburden dump, presence of higher elevation and steep slope. Thus, the combined effect of slope, elevation, geology, drainage and mining activities on the WLF in the study region is moderate.     

Tools for Groundwater Protection Planning: An Example from McHenry County, Illinois, USA

/ This paper presents an approach for producing aquifer sensitivity maps from three-dimensional geologic maps, called stack-unit maps. Stack-unit maps depict the succession of geologic materials to a given depth, and aquifer sensitivity maps interpret the successions according totheir ability to transmit potential contaminants. Using McHenry County, Illinois, as a case study, stack-unit maps and an aquifer sensitivity assessment were made to help land-use planners, public health officials, consultants, developers, and the public make informed decisions regarding land use. A map of aquifer sensitivity is important for planning because the county is one of the fastest growing counties in the nation, and highly vulnerable sand and gravel aquifers occur within 6 m of ground surface over 75% of its area. The aquifer sensitivity map can provide guidance to regulators seeking optimal protection of groundwater resources where these resources are particularly vulnerable. In addition, the map can be used to help officials direct waste-disposal and industrial facilities and other sensitive land-use practices to areas where the least damage is likely to occur, thereby reducing potential future liabilities. KEY WORDS: Geologic mapping; Groundwater; Aquifers; Aquifer sensitivity; Land-use planning     

Geomorphological and geophysical approach for locating favorable groundwater zones in granitic terrain, Andhra Pradesh, India

The increasing demand for fresh water has necessitated the exploration for new sources of groundwater, particularly in hard rock terrain, where groundwater is a vital source of fresh water. A fast, cost effective and economical way of exploration is to study and analyze remote sensing data. Interpreted remote sensing data was used to select sites for carrying out surface geophysical investigations. Various geomorphologic units were demarcated and the lineaments were identified by interpretation of remote sensing satellite images. The potential for occurrence of groundwater in the watershed areas was classified as very good, good, moderate and poor by interpreting the images. Sub-surface geophysical investigations, namely vertical electrical soundings, were carried out to delineate potential water-bearing zones. Integrated studies of interpretation of geomorphologic and geophysical data were used to prepare a groundwater potential map. The studies reveal that the groundwater potential of shallow aquifers is due to geomorphologic features and the potential of deeper aquifers is determined by lineaments such as faults and joints.     

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.     

Land Evaluation in a Salt-Affected Irrigated District Using an Index of Productive Potential

2 semiarid irrigated area with salt-affected soils. The available soil map is at 1:100,000 scale and its mapping units are used for the land evaluation with the FAO framework. These data are then elaborated using the index value method. This procedure gives a map of land evaluation units and a table that rates the productive potential of these units for six crops: alfalfa, barley, maize, rice, sunflower, and wheat.     

An Aquifer Vulnerability Assessment of the Paluxy Aquifer, Central Texas, USA, Using GIS and a Modified DRASTIC Approach

D epth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, and Conductivity of the aquifer). Using such an approach allows one to investigate the potential for groundwater contamination on a regional, rather than site-specific, scale. Based upon data from variables such as soil permeability, depth to water, aquifer hydraulic conductivity, and topography, subjective numerical weightings have been assigned according to the variable's relative importance in regional groundwater quality. The weights for each variable comprise a GIS map layer. These map layers are combined to formulate the final groundwater pollution potential map. Using this method of investigation, the pollution potential map for the study area classifies 47% of the area as having low pollution potential, 26% as having moderate pollution potential, 22% as having high pollution potential, and 5% as having very high pollution potential.     

Groundwater Vulnerability Assessment Combining the Drastic and Dyna-Clue Model in the Argentine Pampas

Vulnerability assessment is considered an effective tool in establishing monitoring networks required for controlling potential pollution. The aim of this work is to propose a new integrated methodology to assess actual and forecasted groundwater vulnerability by including land-use change impact on groundwater quality. Land-use changes were simulated by applying a spatial dynamics model in a scenario of agricultural expansion. Groundwater vulnerability methodology DRASTIC-P, was modifyed by adding a land-use parameter in order to assess groundwater vulnerability within a future scenario. This new groundwater vulnerability methodology shows the areas where agricultural activities increase the potential level of groundwater vulnerability to pollution. The Dulce Creek Basin was the study case proposed for the application of this methodology. The study revealed that the area with Very High vulnerability would increase 20% by the year 2020 in the Dulce Creek Basin. This result can be explained by analyzing the land-use map simulated by the Dyna-CLUE model for the year 2020, which shows that the areas with increments in crop and pasture coincide with the area defined by the Very High aquifer vulnerability category in the year 2020. Through scenario analysis, land-use change models can help to identify medium or long term critical locations in the face of environmental change.     

Surveying and mapping of natural resources by remote sensing

Sustainable economic development requires detailed knowledge of the natural resources of any nation. Acquiring the needed information by conventional means may require a large investment in time, personnel, and therefore, in cost. A viable alternative is space-age technology which provides the necessary tools to conduct surveys of natural resources in a timely manner. Such technologies can obtain the required data by means of digital sensors, radar imaging systems and stereo cameras. These data can be utilized to map structures that may contain oil and gas deposits, recognize high concentrations of economic minerals, and discover regions with fertile soils and good potential for groundwater. Those applications warrant greater use of remote sensing methods and techniques by the international scientific community, particularly for the development of natural resources in the Third World. This paper represents a general review of the available, and easily interpretable, space-borne data that are useful in the mapping of natural resources.     

Sampling and Mapping a Soil Erosion Cover Factor by Integrating Stratification,Model Updating and Cokriging with Images

Cost-efficient sample designs for collection of ground data and accurate mapping of variables are required to monitor natural resources and environmental and ecological systems. In this study, a sample design and mapping method was developed by integrating stratification, model updating, and cokriging with Landsat Thematic Mapper (TM) imagery. This method is based on the spatial autocorrelation of variables and the spatial cross-correlation among them. It can lead to sample designs with variable grid spacing, where sampling distances between plots vary depending on spatial variability of the variables from location to location. This has potential cost-efficiencies in terms of sample design and mapping. This method is also applicable for mapping in the case in which no ground data can be collected in some parts of a study area because of the high cost. The method was validated in a case study in which a ground and vegetation cover factor was sampled and mapped for monitoring soil erosion. The results showed that when the sample obtained with three strata using the developed method was used for sampling and mapping the cover factor, the sampling cost was greatly decreased, although the error of the map was slightly increased compared to that without stratification; that is, the sample cost-efficiency quantified by the product of cost and error was greatly increased. The increase of cost-efficiency was more obvious when the cover factor values of the plots within the no-significant-change stratum were updated by a model developed using the previous observations instead of remeasuring them in the field.     

Application of a weights-of-evidence method and GIS to regional groundwater productivity potential mapping

The aim of this study is to analyze the relationship among groundwater productivity data including specific capacity (SPC) and transmissivity (T) as well as its related hydrogeological factors in a bedrock aquifer, and subsequently, to produce the regional groundwater productivity potential (GPP) map for the area around Pohang City, Korea using a geographic information system (GIS) and a weights-of-evidence (WOE) model. All of the related factors, including topography, lineament, geology, forest, and soil data were collected and input into a spatial database. In addition, SPC and T data were collected from 83 and 81 well locations, respectively. Four dependent variables including SPC values of ≥6.25 m3/d/m (Case 1) and T values of ≥3.79 m2/d (Case 3) corresponding to a yield (Y) of ≥500 m3/d, and SPC values of ≥3.75 m3/d/m (Case 2) and T values of ≥2.61 m2/d (Case 4) corresponding to a Y of ≥300 m3/d were also input into a spatial database. The SPC and T data were randomly selected in an approximately 70:30 ratio to train and validate the WOE model. Tests of conditional independence were performed for the used factors. To assess the regional GPP for each dependent variable, W+ and W- of each factor's rating were overlaid spatially. The results of the analysis were validated using area under curve (AUC) analysis with the existing SPC and T data that were not used for the training of the model. The AUC of Cases 1, 2, 3 and 4 showed 0.7120, 0.6893, 0.6920, and 0.7098, respectively. In the case of the dependent variables, Case 1 had an accuracy of 71.20% (AUC: 0.7120), which is the best result produced in this analysis. Such information and the maps generated from it could be used for groundwater management, a practice related to groundwater resource exploration.     

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.     

GROUNDWATER ZONING IN WATER RESOURCES MANAGEMENT1

In today's society the planned management of groundwater resources has played an increasingly greater role. One means of insuring the protection of groundwater quantity and quality is a regional zoning of groundwater resources. Regional zoning means to classify a given region with regard to hydrogeological characteristics and to evaluate and determine the possible use of each zone. The necessary assumption is the appropriate knowledge of geological structure (compiled in a geological map) and of hydrogeological conditions (compiled in a hydrogeological map). The basis for subdivision is a hydrogeological unit distinguished and delineated on the basis of lithological, stratigraphical, structural, and hydrogeological characteristics. It should have its own distinct hydrological system. The hydrogeological region is the basic unit. Regions may be grouped into larger units: hydrogeological provinces and realms. The subdivision of regions into hydrogeological zones, or subzones when applicable, forms the basis for a groundwater development plan.     

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.     

Demonstrating Floodplain Uncertainty Using Flood Probability Maps1

Abstract: The U.S. Federal Emergency Management Agency (FEMA) flood maps depict the 100‐year recurrence interval floodplain boundary as a single line. However, because of natural variability and model uncertainty, no floodplain extents can be accurately defined by a single line. This article presents a new approach to floodplain mapping that takes advantage of accepted methodologies in hydrologic and hydraulic analysis while including the effects of uncertainty. In this approach, the extents of computed floodplain boundaries are defined as a continuous map of flood probabilities, rather than as a single line. Engineers and planners can use these flood probability maps for viewing the uncertainty of a floodplain boundary at any recurrence interval. Such a flood probability map is a useful tool for visualizing the uncertainty of a floodplain boundary and represents greater honesty in engineering technologies that are used for flood mapping. While institutional barriers may prevent adoption of such definitions for use in graduated flood insurance rates (as most other insurance industries use to account for relative risks), the methods open the door technically to such a reality.     

Cluster analysis of structural stage classes to map wildland fuels in a Madrean ecosystem

Geospatial information technology is changing the nature of fire mapping science and management. Geographic information systems (GIS) and global positioning system technology coupled with remotely sensed data provide powerful tools for mapping, assessing, and understanding the complex spatial phenomena of wildland fuels and fire hazard. The effectiveness of these technologies for fire management still depends on good baseline fuels data since techniques have yet to be developed to directly interrogate understory fuels with remotely sensed data. We couple field data collections with GIS, remote sensing, and hierarchical clustering to characterize and map the variability of wildland fuels within and across vegetation types. One hundred fifty six fuel plots were sampled in eight vegetation types ranging in elevation from 1150 to 2600 m surrounding a Madrean 'sky island' mountain range in the southwestern US. Fuel plots within individual vegetation types were divided into classes representing various stages of structural development with unique fuel load characteristics using a hierarchical clustering method. Two Landsat satellite images were then classified into vegetation/fuel classes using a hybrid unsupervised/supervised approach. A back-classification accuracy assessment, which uses the same pixels to test as used to train the classifier, produced an overall Kappa of 50% for the vegetation/fuels map. The map with fuel classes within vegetation type collapsed into single classes was verified with an independent dataset, yielding an overall Kappa of 80%.     

Evidence of hydrocarbon contamination from the Burgan oil field, Kuwait: interpretations from thermal remote sensing data

The paper presents the application of thermal remote sensing for mapping hydrocarbon polluted sites. This has been achieved by mono-window algorithm for land surface temperature (LST) measurements, using multi-date band 6 data of Landsat Thematic Mapper (TM). The emissivity, transmittance and mean atmospheric temperature were used as critical factors to estimate LST. The changes in the surface emissivity due to oil pollution alter the apparent temperature, which was used as a recognition element to map out oil polluted surfaces. The LST contrast was successfully used to map spatial distribution of hydrocarbon pollution in the Burgan Oil field area of Kuwait. The methodology can be positively used to detect waste dumping, oil spills in oceans and ports, besides environmental management of oil pollution at or near the land surface.