Groundwater
nasser jabraili andarian; Ata Allah Nadiri; Maryam Gharekhani
Abstract
Iran's groundwater reservoirs have faced significant and related challenges in the past three decades. The simultaneous decrease in the volume and quality of these waters, which are increasingly contaminated with pollutants, renders them largely unusable for many uses. Therefore, there is an increasing ...
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Iran's groundwater reservoirs have faced significant and related challenges in the past three decades. The simultaneous decrease in the volume and quality of these waters, which are increasingly contaminated with pollutants, renders them largely unusable for many uses. Therefore, there is an increasing emphasis on evaluating the quality of groundwater and identifying anthropogenic or geogenic factors that affect its quality more than ever before. In this study, the hydrogeochemical pollution caused by major, minor, and trace elements was identified by examining the water table against the electrical conductivity of water resources in Azarshahr plain. Long-term data on water levels and electrical conductivity were obtained from regional water resources in East Azerbaijan province. After initial examination, 33 samples were collected from wells and qanats in the area and transferred to the water laboratory of Tabriz University for analysis. The measured parameters included pH, electrical conductivity, major, minor, and trace elements.The results of chemical analysis showed that the concentrations exceeding the permissible drinking limit for nitrates and elements such as Arsenic, Lead, Nickel, and Chromium. Piper diagrams and Stiff diagrams were used to determine the water type in the area; it was found that the water type is mainly sulfate and bicarbonate-based. The origin of the available water is related to the geological formations in the area as a result of mixing and ion exchange.Furthermore, multivariate statistical analysis using factor analysis revealed four influential factor groups affecting water quality in the area; only the fourth factor was attributed to anthropogenic. In general, most of the trace elements in water sources are influenced by formations and aquifer-rock interactions.The overall trend of groundwater quantity over a 25-year period is relatively stable with a slight downward slope; however, the general trend of electrical conductivity is ascending with a much steeper slope indicating an increase in anthropogenic activities as well as the presence of saline layers, which leads to a decrease in the quality of groundwater. Most of the contaminated samples in terms of major and trace elements are located around Gowgan city at the end of the plain. The pollution at this end is related to dissolution trends along with movement paths of groundwater flow and density of pumping wells in this area.
Mehdi Teimouri; Omid Asadi Nalivan
Abstract
1- Introduction Underground water is one of the most important water resources that plays an important role in providing water for agricultural and drinking activities in arid and semi-arid regions (Usamah and Ahmad, 2018, Wu et al., 2019, Kumar et al., 2019). Awareness of the quality of water resources ...
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1- Introduction Underground water is one of the most important water resources that plays an important role in providing water for agricultural and drinking activities in arid and semi-arid regions (Usamah and Ahmad, 2018, Wu et al., 2019, Kumar et al., 2019). Awareness of the quality of water resources is one of the most important requirements in managing, planning, and developing, protecting, and controlling water resources. Using multivariate statistical techniques helps researchers identify the most important factors affecting the quality of water systems and is a valuable tool for water resources management (Pasandidehfard et al., 2019). On the other hand, geostatistical methods are also capable of zoning water quality at the watershed level and can play an important role in completing the assessment of water quality (Ahmadi et al., 2019). The aim of this study is to evaluate the quality of groundwater used for drinking and farming in Hable-Rood Basin, analyze and interpret the quality of these resources using ArcGIS, and perform statistical tests to determine the role of land use and geology formations in water quality. 2-Methodology To do this research, 132 water sources including wells, springs, and Qanats were used during the statistical period of 2008-2018. The watershed can be divided into fifteen main categories in terms of geology. Hable-Rood watershed has 11 main land uses, which has the largest area of the watershed for pasture and the smallest area of the dams. The main components were analyzed (factor analysis) to understand the most important parameters affecting the water quality. This method weighs the components and expresses a special value for each of them (Finkler et al., 2016). Factor analysis has three stages of producing a correlation matrix from all variables (Pearson correlation method), extracting the main factors, and interpreting the results. Duncan's test was also used to check the significance level of parameters among land uses and the type of formations. Geostatistical methods were used for zoning water quality for drinking and farming purposes in the GIS. The spatial relationship of a random variable in the geostatistics was determined by the semivariogram (software GS +). The root mean square error (RMSE) method was used to assess the geostatistical methods and select the best method. It should be noted that the Schoeller diagram and Wilcox diagram were used for the drinking water zoning and agricultural water quality zoning, respectively. 3-Results and Discussion The results showed that the Cl, EC, TDS, Na, Ca, TH, and SO4 vary significantly in different land uses. The highest average was related to industrial areas within the watershed due to the release of industrial materials and the spread and diffusion of groundwater pollution. Also, the parameters of Cl, EC, TDS, TH, and SO4 differed significantly in varied formations. The trend of water quality changes shows the water quality impact of land use, and water quality has decreased sharply in the industrial area, low-yielding land, saline lands, agriculture, and residential areas. The EC parameter showed the highest correlation with TDS at 5% significance level, which is due to a high correlation with the effect of increasing EC on TDS. The pH parameter did not correlate with the other parameters. The factor analysis on the basis of water quality characteristics showed that 88.16% of the water quality variations among land uses were controlled by a single factor (TDS with a weight of 0.99). The factor analysis on the basis of water quality characteristics showed that 91.59% of water quality changes in the formations were determined by two factors (the first and the second factors with weight loads of 0.95 and 0.95 belonged to the TDS and EC parameters, respectively), and the variance percentages of each of factors 1 and 2 were 77.29 and 14.3%, respectively. 4- Conclusion In this research, the effects of geology and land use on groundwater quality were evaluated using multivariate statistical methods and geostatistical methods in ArcGIS. It was determined that some of the groundwater quality parameters were affected by land use and some of the other parameters were under the influence of the geology in the watershed. In general, however, it can be stated that in the first priority, the land use factor and human activities, and in the second priority, the geological factor affecting groundwater quality have the most significant effects. In the formation part of the geology, the dissolution of calcareous and dolomite formations, the chemical processes of salt dissolution, and evaporative formations are the main factors controlling groundwater chemistry in the region. Based on the results, multivariate statistical techniques and geostatistical methods have the ability to recognize factors affecting groundwater quality and the zoning of water quality for different uses and are, therefore, suggested for similar research.
Kazem Nosrati; Ali Rajabi Eslami; Mojtaba Sayadi
Volume 5, Issue 15 , October 2018, , Pages 171-190
Abstract
Abstract
Introduction
Groundwater is the most important source of drinking water in most communities. Water quality assessment and hydrogeochemical agents that effect water quality due to its direct impact on consumers' health is essential. Before 1970s, the focus of most studies was on physical properties ...
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Abstract
Introduction
Groundwater is the most important source of drinking water in most communities. Water quality assessment and hydrogeochemical agents that effect water quality due to its direct impact on consumers' health is essential. Before 1970s, the focus of most studies was on physical properties of water, but in the recent century developments in sciences (i.e., chemistry and geology) researches on groundwater quality has improved. Approaches to estimate the effects of time and place on the quality and quantity of groundwater are univariate and multivariate statistical techniques. Water resource is getting more and more important in drought and interior regions such as Iran which is located in a desert belt. Therefore, the classification and analysis of groundwater quality in Mallard city in the margin of an interior basin by using multivariate statistical analysis were the aims of this study.
Methodology
The City of Mallard is located in the border of three provinces consisting of Markazi, Tehran, and Alborz. The study area has geographical coordinate with 50° 20´ to 51° eastern longitude and 35° 28´ to 35° 43´ northern latitude. The data used in this study was prepared by rural water and wastewater of Mallard. Thirteen quantitative parameters in thirty-one water wells during 2010-2015 were selected. The data was divided into three qualitative classes on the basis of a hierarchical cluster analysis. Furthermore, to identify the most important water quality parameters in each homogeneous region, a factor analysis on the basis of main component analysis method was used. In order to recognize the suitability or merit of the data, before performing factor analysis, KMO and Bartlett's spit test were done. Hence, the number of factors and main components of groundwater quality were determined. Furthermore, to a better recognition of sample's number on the basis of connection between the factors and their values a graph was depicted that breaks in the axis of the graph defined the number of the main components. In this study, to show the results of the cluster analysis, factor analysis, and one-way variance analysis, SPSS software was applied. After performing a statistical analysis on the basis of the interpolation method and by applying Arc GIS software, the study area was mapped. After registration of the location of any well by GPS, the estimation of use land and geological states was done.
Results and discussion
Based on the quality of water wells in Mallard city, all wells were divided into three qualitative clusters. Accordingly, ten wells were settled in the first cluster, twelve wells in the second cluster, and nine wells in the third cluster. The qualitative zoning showed Mallard's wells in terms of the cluster analysis. The distance between the wells is due to solidarity and self- solidarity between qualitative characteristics of the water wells. The cluster analysis on Mallard groundwater quantitative data resulted in three quantitative classes for water wells in this city. Therefore, each cluster was analyzed by the measurement of a meaningful data and accordingly quantitative status of the clusters were determined. From first toward third clusters, the concentration of all quantitative parameters except PH increased in a meaningful way.
Conclusion
The results revealed that the water quality in the third cluster was low. In each cluster, three factors, as the main parameters that effect and change the water quality, had respectively total variance of 92.85, 83.58, and 88.93. In addition, evaporate formations, using chemical fertilize, household wastewaters, and non-principle repulsed of poultry farm garbage were the effective parameters on water quality changes in the study area.
