|تعداد مشاهده مقاله||111,757,157|
|تعداد دریافت فایل اصل مقاله||86,348,454|
Investigation of Spatial Structure of Groundwater Quality Using Geostatistical Approach in Mehran Plain, Iran
|مقاله 5، دوره 2، شماره 1، فروردین 2016، صفحه 57-65 اصل مقاله (803.45 K)|
|نوع مقاله: Original Research Paper|
|شناسه دیجیتال (DOI): 10.7508/pj.2016.01.006|
|Hassan Khosravi* 1؛ Kamran Karimi2؛ Sara Nakhaee nejadfard3؛ Tayebeh Mesbahzadeh1|
|1Assistant Professor, Faculty of Natural Resources, University of Tehran, Karaj, Iran|
|2PhD Student of Combating Desertification, Gorgan Agriculture and Natural Resources University, Iran|
|3PhD Student of Combating Desertification, Hormozgan University, Iran|
|Groundwater is a major source of water for domestic, industrial, and agricultural sectors in many countries. The main objective of this research was to provide an overview of present groundwater quality using parameters such as calcium, magnesium, sodium, chloride, sulfate, pH, and electrical conductivity (EC) in the Mehran plain, Ilam province using GIS and geostatistical techniques. A total of 23 deep and semi-profound wells were selected based on the classified randomized sampling method. The sampling locations were obtained by GPS. Plastic containers were used for the collection of water samples. These samples were transferred to the laboratory for analyzing water quality parameters. Statistical characteristics, qualitative data interpolation, and zoning were investigated using SPSS 20 ،GS+5.3 and ArcGIS10.1. Kolmogorov–Smirnov test were used to test data normality. In order to normalize parameters, logarithm, and 1/x were used for sulfate, EC, cation, and anion. Then the variogram analysis was performed to select the appropriate model. Results showed that co-kriging is the best method for cation and anion, whereas local polynomial interpolation is suitable for sulfate. The results of the interpolation of groundwater quality factors showed that there is approximately good adaption among groundwater factors and geomorphology and topology of the region. Because of inappropriate irrigation system, the highest concentration is in the northwest and western parts of the region, where there is the minimum height and maximum agricultural land. Growth of arable land and agricultural activities has caused increasing concentrations of studied elements, especially EC.|
|Geostatistical؛ Groundwater؛ Mehran plain؛ spatial variations modeling|
Baalousha, H. (2010). Assessment of a groundwater quality monitoring network using vulnerability mapping and geostatistics: A case study from Heretaunga Plains, New Zealan. Agr Water Manage, 97, 240–246.
Cameron,K., and Hunter, P. (2002). Using spatial models and Kriging techniques to optimize long-term ground-water monitoring networks. Environmetrics, 13, 629-656.
Costa, A., and Soares, A. (2008). Homogenization of Climate Data: Review and New Perspectives Using Geostatistics. Math Geosci, 41, 291–305.
David, M. (1977). Geostatistical Ore Reserve Estimation. Environ Monit Assess, 82, 311–320.
Feng-guang, Y., Shu-you, C., Xing-nian, L. and Ke-jun, Y. (2008). Design of groundwater level monitoring network with ordinary kriging. J. Hydrodyn, 20, 339–346.
Hoseini, Y. (2013). Use of geostatistical analysis to optimize estimation of hydraulic conductivity for drainage projects. Intl. J. Agron Plant Prod, 4, 236-241.
Hudak, P. F., and Sanmanee, S. (2003). Spatial patterns of nitrate, chloride, sulfate, and fluoride concentrations in the woodbine aquifer of North-Central Texas.
Ishaku, J. M. (2011). Assessment of groundwater quality index for Jimeta-Yolaarea, Northeastern Nigeria. J. Geol Min Res, 3, 219-231.
Jalali, M. (2007). Hydrochemical identification of groundwater resources and their changes under the impacts of human activity in Chah basin in Western Iran. Environ Monit Assess, 130, 347–364
Karimi, H., Naderi, F. A. and Mehdizadeh. Z. (2011). Capability of Mehran plain's groundwater for irrigation of agriculture lands in GIS environment. J. Irrig Wat Eng, 2, 1 - 8.
Lee, J., Jang, S., Wang, J., and Chen-Wuing, L. (2007). Evaluation of potential health risk of arsenic-affected groundwater using indicator Kriging and dose response model. Sci Total Environ, 1, 151–162.
Maghami, Y. Ghezavati, R,.Vali, A,. and Sharfi, S. (2011). Evaluation of interpolation methods for mapping water quality using GIS (Case study: Abadeh- Iran). J. Geogr. Reg. Plann, 22, 182-171.
Nas, B., and Berktay. A. (2010). Groundwater quality mapping in urban groundwater using GIS. Environ Monit Assess, 160, 215-227.
Nunes, L. M., E. Paralta, M.C. Cunha., and L. Ribeiro. 2007. Comparison of variance-reduction and space filling approaches for the design of environmental monitoring networks. Comput Aided Civ Infrastruct Eng, 22, 489–498.
Pin Lin. Y., Kuo Chang, T. and Po Teng. T. (2001). Characterization of soil lead by comparing sequential Gaussian simulation simulated annealing simulation and Kriging methods. Environ geol, 41, 189-199.
Reed, P., Minsker, B. and Valocchi. A. J. (2010). Cost-effective long-term groundwater monitoring design using a genetic algorithm and global mass interpolation. Water Resour Res, 36, 3731-3741.
Stites, W, and Kraft, G. J. (2001). Nitrate and chloride loading to groundwater from an irrigated North-Central U.S. Sand- Plain vegetable field. J. Environ Qual, 30, 1176–1184.
UNDP, UNEP, and World Bank. (2000). World Resources 2000-2001. Washington DC, World Resources Institute.
Yan. Z., ZH. Yong-zhang, W., Lin-feng, W., Zheng-hai, A., Yan-fei, L., Hong-zhong, Z., Chang-yu, A., Jin, A., Wen-chao, L. and Le. G. (2013). Mineralization-related geochemical anomalies derived from stream sediment geochemical data using multiracial analysis in Pangxidong area of Qinzhou-Hangzhou tectonic joint belt, Guangdong Province, China. J. Cent. South Univ. 20, 184−192.
Zehtabian, Gh., Jaanfaza, A. Mohammad H., Asgari, M. and Nematollahi, C. (2010). Modeling of spatial variations of some groundwater chemical properties (case study: Garmsar watershed). Journal of Range and Desert Research of Iran, 17, 61-73.
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