Groundwater Quality Mapping Research Articles

Spatial Data Analysis For Ground Water Quality Assessment With Special Refrence To Iron - A Case Study Of Barna Watershed,Raisen District, Madhya Pradesh, India

Barna Watershed is a catchment of Barna River and its tributaries, lies in the Raisen district of Madhya Pradesh. The total area of Barna Watershed is approximately 1129 Sq. Km. The aim of the study was to analyze the observed ground water quality parameters and to create spatial map for drinking water purpose for Barna Watershed. For the above study ground water Samples were collected from the field and some GWQ data were collected from PHED, M.P and National Rural Development Water Programme (IMIS) website under Ministry of Drinking water & Sanitation. The GWQ layers were generated separately for each element for Both Pre-Monsoon and Post-Monsoon Season, from the well point layers with the help of Inverse Distance weighted Method (IDW) interpolation technique using ArcGIS 9.3 software. Each element wise layer has been categorized into three categories (1) potable water in Desirable limits (2) Potable water in permissible limits (3) Non-potable ground water, as per BIS standard 2012. Integrating layers of pre-monsoon; pre-monsoon Ground Water Quality map has been prepared and integrating layers of post-monsoon; post-monsoon Ground Water Quality map has been prepared. Integrating the pre & post monsoon Ground water quality map, final ground water quality class map has been prepared. The Final Ground Water Quality class map has been divided into 9 classes as the standard given by the NRSC, ISRO; Ground Water Quality, manual of RGNDWM-PH IV. The Final Ground Water Quality Class map of Barna Watershed shows, out of 75.04% Non-Potable area73.12% area is Non- Potable due to excess of Iron and out 65.51% Habitations which is falling in Non-Potable class, 56.89% habitation are severely affected by excess of Iron.

Spatial mapping of irrigation groundwater quality of the High Mekerra watershed (Northern Algeria)

The spatial assessment of water quality for irrigation is of great importance for agricultural issues. Assessing the suitability of groundwater for irrigation is carried out for the first time in the High Mekerra watershed. Groundwater samples were collected during the wet season (March 2013) and the dry season (July 2013) and analyzed for determining the physicochemical properties. The indices used in the quality assessment were the sodium adsorption ratio (SAR), residual sodium carbonate (RSC), sodium percentage (%Na+), permeability index (PI), magnesium hazard (MH), Kelly’s ratio (KR), and irrigation water quality index (IWQI), incorporating the spatial variation using the GIS-based multi-criteria system. Result showed that most of groundwater samples have low sodium hazard and high to very high salinity hazard and could be used for irrigation on almost all types of soil with little risk of exchangeable sodium. The GIS-based multi-criteria system highlighted the spatial variation of groundwater quality for irrigation in the study area. This spatial distribution indicated that groundwater is generally of moderate quality and that the Ras el Ma aquifer quality is better than for Mouley Slissen aquifer.

Mapping of Mn and Pb as Effect of Landfill Pollutant based on Ordinary Kriging Interpolation

Spatial interpolation is an important method, getting information about pollutan from landfill location in groundwater quality mapping. Ordinary kriging is used to predict the unknown values in some locations, based on the autocorrelations among the nearby locations. In this research, ordinary kriging interpolation was used to divine the chemical characteristic of Manganese (Mn) and Lead (Pb), then 22 samples, around the Integrated Waste Management (TPST) Bantar Gebang, were taken for the purpose. In conclusion, there is an autocorrelation spatial among those locations. In addition, the Gaussian variogram model gives a better result than the Exponential model and the higher of Mn and Pb is in the southeast of TPST Bantar Gebang. This location has the high chance to be an affected pollution area.

Mapping of groundwater quality using Normalized Difference Dispersal Index of Dwarka sub-city at Delhi National Capital of India

In this study, geo-statistical tool was used to map groundwater quality parameters. Groundwater samples were collected from 30 wells. In order to quantify the site-specific variations, Normalized Difference Dispersal Index (NDDI) was used to map five parameters namely pH, EC, TH, Ca, and Mg. Maximum NDDI value enrichment was exhibited by EC (−0.01) and Mg (−0.009 ≈ −0.01) it reflects accretion. In addition, for pH (−0.012), TH (−0.027), and Ca (−0.025), it outlined by dilution or minor accretion, whereas median NDDI value for EC, Ca, Mg, TH and pH is −0.02, −0.02, −0.03, −0.029, and −0.04, respectively. NDDI mapping is a functional tool for evaluation and comparative assessment of spatio-temporal variations in groundwater. Further, frequency distribution and inter correlation analysis of the data-set has displayed coherence. The results of study will help in management of water resources.

Physico-chemical Analysis and Mapping of Ground Water Quality in Residential Area of Two Different Zone of Central India

Physico-chemical Analysis and Mapping of Ground Water Quality in Residential Area of Two Different Zone of Central India

Groundwater quality assessment and mapping using multivariate statistics and analytic hierarchy process in Bhubaneswar city, Odisha, India

Groundwater, the major drinking water source in an urban area, is vulnerable to deteriorate by its quality due to population pressure and developmental activities. Assessment of and understanding the groundwater chemistry is therefore imperative. Using multivariate statistics and analytic hierarchy process, the groundwater quality of Bhubaneswar, an ever-growing city in eastern India is assessed and elaborated in this paper. Samples collected from the city were found to be dominated by Na-Cl-HCO3, Na-Ca-Cl-HCO3, Na-Cl and mixed hydrochemical facies through Piper trilinear diagram. Silicate weathering had come up as a dominant process for influencing ionic constituents in bore well (> 20 m depth), while anthropogenic intervention was responsible for excess nitrate, K, sulphate and chloride contents in dug well (≤ 3-10 m depth) water. Samples were classified to four clusters using hierarchical cluster analyses and cluster-wise discriminating variables were identified through discriminant function. The discriminating variables (turbidity, Fe, Mn, NO3–, K and pH) which determine the drinkability of water were then ranked through analytic hierarchy process (AHP), A hierarchy was prepared and used to generate the vulnerability map distinguishing low to high quality groundwater endowed localities in the study area.

A method of groundwater quality assessment based on fuzzy network-CANFIS and geographic information system (GIS)

The process of water quality testing is money/time-consuming, quite important and difficult stage for routine measurements. Therefore, use of models has become commonplace in simulating water quality. In this study, the coactive neuro-fuzzy inference system (CANFIS) was used to simulate groundwater quality. Further, geographic information system (GIS) was used as the pre-processor and post-processor tool to demonstrate spatial variation of groundwater quality. All important factors were quantified and groundwater quality index (GWQI) was developed. The proposed model was trained and validated by taking a case study of Mazandaran Plain located in northern part of Iran. The factors affecting groundwater quality were the input variables for the simulation, whereas GWQI index was the output. The developed model was validated to simulate groundwater quality. Network validation was performed via comparison between the estimated and actual GWQI values. In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned. Therefore, numeric values of each pixel with geographical coordinates were entered to the Fuzzy Network-CANFIS model and thus simulation of groundwater quality was accessed in the study area. Finally, the simulated GWQI indices using the Fuzzy Network-CANFIS model were entered into GIS, and hence groundwater quality map (raster layer) based on the results of the network simulation was earned. The study’s results confirm the high efficiency of incorporation of neuro-fuzzy techniques and GIS. It is also worth noting that the general quality of the groundwater in the most studied plain is fairly low.

Groundwater resource vulnerability and spatial variability of nitrate contamination: Insights from high density tubewell monitoring in a hard rock aquifer.

Agriculture has been increasingly relying on groundwater irrigation for the last decades, leading to severe groundwater depletion and/or nitrate contamination. Understanding the links between nitrate concentration and groundwater resource is a prerequisite for assessing the sustainability of irrigated systems. The Berambadi catchment (ORE-BVET/Kabini Critical Zone Observatory) in Southern India is a typical example of intensive irrigated agriculture and then an ideal site to study the relative influences of land use, management practices and aquifer properties on NO3 spatial distribution in groundwater. The monitoring of >200 tube wells revealed nitrate concentrations from 1 to 360mg/L. Three configurations of groundwater level and elevation gradient were identified: i) NO3 hot spots associated to deep groundwater levels (30-60m) and low groundwater elevation gradient suggest small groundwater reserve with absence of lateral flow, then degradation of groundwater quality due to recycling through pumping and return flow; ii) high groundwater elevation gradient, moderate NO3 concentrations suggest that significant lateral flow prevented NO3 enrichment; iii) low NO3 concentrations, low groundwater elevation gradient and shallow groundwater indicate a large reserve. We propose that mapping groundwater level and gradient could be used to delineate zones vulnerable to agriculture intensification in catchments where groundwater from low-yielding aquifers is the only source of irrigation. Then, wells located in low groundwater elevation gradient zones are likely to be suitable for assessing the impacts of local agricultural systems, while wells located in zones with high elevation gradient would reflect the average groundwater quality of the catchment, and hence should be used for regional mapping of groundwater quality. Irrigation with NO3 concentrated groundwater induces a "hidden" input of nitrogen to the crop which can reach 200kgN/ha/yr in hotspot areas, enhancing groundwater contamination. Such fluxes, once taken into account in fertilizer management, would allow optimizing fertilizer consumption and mitigate high nitrate concentrations in groundwater.

Spatial and Temporal Mapping of Groundwater Quality using GIS based Water Quality Index (A Case Study of SIPCOT-Perundurai, Erode, Tamil Nadu, India)

Groundwater is an important source of drinking water especially in rural areas of Tamil Nadu. Over exploitation of groundwater for industrial use has become a major challenge. Therefore, it is very important to assess the quality of groundwater. The present study is about the geostatistical analysis of groundwater quality for SIPCOT Industrial estate, Perundurai, Erode, where Groundwater is the main source of water for drinking and irrigation purpose. The aim of the study is to map the current situation of groundwater quality in the study area. The groundwater samples collected from 35 wells in and around the SIPCOT industrial estate are used for this purpose. The major water quality parameters such as pH, EC, TDS, TA, TH, Ca, Mg, Na, K, F, Sulfates, Nitrites, Nitrates, Chlorine, Carbonate, Bicarbonate, Sodium absorption ratio, Residual sodium carbonate, and Sodium have been estimated for all the samples and the results were compared with the BIS standards. The spatial distribution map of these groundwater quality parameters were derived and integrated with WQI through GIS. GIS is used as a tool for analysis of spatial distribution of water quality. The resultant map shows the Water quality index for both pre monsoon and post monsoon season of the study area.

Application of Dempster–Shafer theory, spatial analysis and remote sensing for groundwater potentiality and nitrate pollution analysis in the semi-arid region of Khuzestan, Iran

Effective management and sustainable development of groundwater resources of arid and semi-arid environments require monitoring of groundwater quality and quantity. The aim of this paper is to develop a reasonable methodological framework for producing the suitability map for drinking water through the geographic information system, remote sensing and field surveys of the Andimeshk-Dezful, Khozestan province, Iran as a semi-arid region. This study investigated the delineation of groundwater potential zone based on Dempster–Shafer (DS) theory of evidence and evaluate its applicability for groundwater potentiality mapping. The study also analyzed the spatial distribution of groundwater nitrate concentration; and produced the suitability map for drinking water. The study has been carried out with the following steps: i) creation of maps of groundwater conditioning factors; ii) assessment of groundwater occurrence characteristics; iii) creation of groundwater potentiality map (GPM) and model validation; iv) collection and chemical analysis of water samples; v) assessment of groundwater nitrate pollution; and vi) creation of groundwater potentiality and quality map. The performance of the DS was also evaluated using the receiver operating characteristic (ROC) curve method and pumping test data to ensure its generalization ability, which eventually, the GPM showed 87.76% accuracy. The detailed analysis of groundwater potentiality and quality revealed that the ‘non acceptable’ areas covers an area of about 1479km2 (60%). The study will provide significant information for groundwater management and exploitation in areas where groundwater is a major source of water and its exploration is critical to support drinking water need.

Analysis and Spatial Mapping of Groundwater Quality in Puducherry, India

Analysis and Spatial Mapping of Groundwater Quality in Puducherry, India

Evaluation of Groundwater Quality at Oragadam –A GIS Approach

Background/Objectives: In recent years, an increasing threat to groundwater quality due to human activities has become of great importance. This study aims to investigate the effect of industrial discharge of waste water on groundwater quality using GIS. Methods/Statistical Analysis: Oragadam Industrial area which is part of Sriperumbudur Taluk in Tamil Nadu has been chosen as study area owing to presence of about 35 industries. 25 physico-chemical parameters governing the water quality are determined from 50 samples collected in the study area. These have been mapped and spatial analysis has been carried out using GIS. Findings: Groundwater quality maps have been prepared using GIS. Effectiveness of GIS in evaluating the groundwater quality of the study area is determined. Turbidity of all 50 samples was within BIS standards. TDS of 43 samples (86%), electrical conductivity of 46 samples, alkanity of 41 samples (82%), hardness of 41 samples (82%), chloride levels of 26 samples, iron content of 3 samples, fluoride levels of 3 samples, pH of two samples exceeded the BIS Standards. Pollution concentration maps were prepared for all 25 parameters in all 50 sampling stations. Applications/Improvements: Spatial distribution of water quality parameters has been represented through ground water quality maps in and around industrial area of Oragadam, Sriperumbudur Taluk. This study has shown increased salinity levels of groundwater. This study will serve as an aid to Government authorities in groundwater quality monitoring.

Spatiotemporal mapping of groundwater quality for irrigation using geostatistical analysis combined with a linear regression method

Spatiotemporal assessment of groundwater quality for irrigation is essential for agricultural management. This study was conducted to quantify the spatiotemporal changes of Kerman groundwater irrigation quality during 1999–2010 using geostatistical analysis combined with a new method established based on regression coefficient (RC). Result showed that among the main soluble ions, Na+ and Cl− had the highest concentrations. Except Ca+2, the average concentration of all other soluble ions and also EC were higher than the maximum permissible levels for drinking, however, Na+, SO 4 −2 and EC showed no limitations for agricultural irrigation. Based on the proposed RC, soluble Na+, Ca+2, Cl−, total cations, total anions and EC have gradually increased over the years. Soluble Cl− with 0.18 meq l−1 y−1 showed averagely the highest value of RC. Also, EC exhibited an increasing trend with an average value of 16.8 µS cm−1 y−1. In contrast, Mg+2, SO 4 −2 and SAR exhibited negative values of RC, while the value for HCO3 − was zero. Based on nugget-to-sill ratios, the groundwater variables had moderate to strong spatial structure. Finally, the spatiotemporal changes of groundwater salinity (EC) and sodicity (SAR) have been mainly controlled by Na+ and Cl−.

Analysis and Spatial Mapping of Groundwater Quality in Puducherry,India

Analysis and Spatial Mapping of Groundwater Quality in Puducherry,India

Geo-Spatial Ground Water Quality Mapping and Assessment of Mining Region

Geo-Spatial Ground Water Quality Mapping and Assessment of Mining Region

IMPLEMENTATION OF OPEN-SOURCE WEB MAPPING TECHNOLOGIES TO SUPPORT MONITORING OF GOVERNMENTAL SCHEMES

Abstract. Several schemes are undertaken by the government to uplift social and economic condition of people. The monitoring of these schemes is done through information technology where involvement of Geographic Information System (GIS) is lacking. To demonstrate the benefits of thematic mapping as a tool for assisting the officials in making decisions, a web mapping application for three government programs such as Mother and Child Tracking system (MCTS), Telangana State Housing Corporation Limited (TSHCL) and Ground Water Quality Mapping (GWQM) has been built. Indeed the three applications depicted the distribution of various parameters thematically and helped in identifying the areas with higher and weaker distributions. Based on the three applications, the study tends to find similarities of many government schemes reflecting the nature of thematic mapping and hence deduces to implement this kind of approach for other schemes as well. These applications have been developed using SharpMap Csharp library which is a free and open source mapping library for developing geospatial applications. The study highlights upon the cost benefits of SharpMap and brings out the advantage of this library over proprietary vendors and further discusses its advantages over other open source libraries as well.

An application of MC-SDSS for water supply management during a drought crisis.

Climate change influences many countries' rainfall patterns and temperatures. In Iran, population growth has increased water demands. Tabriz is the capital of East Azerbaijan province, in northwestern Iran. A large proportion of the water required for this city is supplied from dams; thus, it is important to find alternatives to supply water for this city, which is the largest industrial city in northwestern Iran. In this paper, the groundwater quality was assessed using 70 wells in Tabriz Township. This work seeks to define the spatial distribution of groundwater quality parameters such as chloride, electrical conductivity (EC), pH, hardness, and sulfate using Geographic Information Systems (GIS) and geostatistics; map groundwater quality for drinking purposes employing multiple-criteria decision-making (MCDM), such as the Analytical Hierarchy Process (AHP) and fuzzy logic, in the study area; and develop an Spatial Decision Support System (SDSS) for managing a water crisis in the region. The map produced by the AHP is more accurate than the map produced using fuzzy logic because in the AHP, priorities were assigned to each parameter based on the weights given by water quality experts. The final map indicates that the groundwater quality increases from the north to the south and from the west to the east within the study area. During critical conditions, the groundwater quality maps and the presented SDSS core can be utilized by East Azerbaijan Regional Water Company to develop an SDSS to drill new wells or to select existing wells to supply drinking water to Tabriz City.

Compilation of Groundwater Quality Map and study of hydrogeochemical characteristics of groundwater in Asia

Compilation of Groundwater Quality Map and study of hydrogeochemical characteristics of groundwater in Asia

Use of Geographic Information System and Water Quality Index to Assess Groundwater Quality in Rawalpindi and Islamabad

Water quality assessment has always been a dominant part of environmental quality management. The present study involved the suitability assessment and mapping of groundwater quality for agricultural activities and drinking purposes in Rawalpindi and Islamabad area. A total of 22 samples were collected from borewells and open wells, and these water samples were further analysed for physical and chemical characteristics on the basis of which different indices were developed. Water quality index was calculated for overall water quality quantification from the perspective of human consumption. The results showed that a greater proportion exhibited poor quality for drinking due to over-exploitation of groundwater resource, agricultural impact and direct release of contaminants. Further, evaluation of groundwater for its suitability for irrigation showed that majority of the groundwater was suitable for irrigation purposes.

Integrationof Remote Sensing and Geographic information system in Ground Water Quality Assessment and Management

Abstract. Spatial variations in ground water quality in the Khartoum state, Sudan, have been studied using geographic information system (GIS) and remote sensing technique. Gegraphical informtion system a tool which is used for storing, analyzing and displaying spatial data is also used for investigating ground water quality information. Khartoum landsat mosac image aquired in 2013was used, Arc/Gis software applied to extract the boundary of the study area, the image was classified to create land use/land cover map. The land use map,geological and soil map are used for correlation between land use , geological formations, and soil types to understand the source of natural pollution that can lower the ground water quality. For this study, the global positioning system (GPS), used in the field to identify the borehole location in a three dimentional coordinate (Latitude, longitude, and altitude), water samples were collected from 156 borehole wells, and analyzed for physico-chemical parameters like electrical conductivity, Total dissolved solid,Chloride, Nitrate, Sodium, Magnisium, Calcium,and Flouride, using standard techniques in the laboratory and compared with the standards.The ground water quality maps of the entire study area have been prepared using spatial interpolation technique for all the above parameters.then the created maps used to visualize, analyze, and understand the relationship among the measured points. Mapping was coded for potable zones, non-potable zones in the study area, in terms of water quality sutability for drinking water and sutability for irrigation. In general satellite remote sensing in conjunction with geographical information system (GIS) offers great potential for water resource development and management.