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Assessment of Spatial Structure of Groundwater Quality Variables Based on the Geostatistical Simulation | ||
| Desert | ||
| مقاله 2، دوره 17، شماره 3، اسفند 2012، صفحه 215-224 اصل مقاله (246.05 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jdesert.2013.35181 | ||
| نویسندگان | ||
| Gh.R. Zehtabian1؛ H. Mohammad Asgari2؛ M. Tahmoures3 | ||
| 1Professor, Faculty of Natural Resources, University of Tehran, Karaj, Iran | ||
| 2Assistant Professor, Khoramshahr University of Marine Science and Technology, Khoramshahr, Iran | ||
| 3Ph.D. Student, Faculty of Natural Resources, University of Tehran, Karaj, Iran | ||
| چکیده | ||
| Our main objective in the present study was to assess the spatial variation of chemical and physical water properties. Prior to the design of groundwater quality monitoring networks, it is essential to investigate the spatial structure of the groundwater quality variables. A case study is presented which used ground water quality observations from groundwater domestic wells in the Dameghan, Iran. The anslyses of the spatial structure used the following variables: Electrical Conductivity (EC), PH, SAR, TDS, Sodium (Na), Calcium (Ca), Magnesium (Mg). For all these variables the spatial structure is described by means of geostatistical simulation, used to yield a series of stochastic images characterized by equally probable spatial distributions of the chemical and physical water properties across the area. The data set including 5 years of annual observations. At first normality and homogeneity of data are examined. Then variographic analysis using two techniques including kriging, Weighted Moving Average (WMA) were applied for presenting spatial variation of water properties. Finally comparison of the results using statistical techniques showed that for more groundwater quality variables (e.g. TDS, EC, Cation, Na, Ca) kriging technique performed better than WMA-2 technique in characterizing the spatial variability. WMA-2 technique only for some groundwater quality variables like SAR and Mg has better result than kriging to simulate groundwater quality variables. | ||
| کلیدواژه‌ها | ||
| Water properties؛ interpolation؛ Geostatistics؛ Spatial Variation؛ Dameghan؛ Iran | ||
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