Reviews geostatistical methods in ground water quality zoning Case study: the city of Kashan


university of kashan


  Rule of arid and semi arid climates in the vast of the country along with population increase and the increase in water demand for urban use industry and agriculture of one side and the growing trend of increased direct and indirect pollution of water resources of The other side Implied that the status and quality of these resources to provide water for various uses and uses of, be studied (Noshad et al, 1388).change of groundwater quality and be saltation water resources are now in great danger in the development of country agriculture , especially dry lands. Optimum management of water resources and protecting and improve of quality of those Need to Existence of information about position, amount and distribution of water chemical factors In a certain geographical area. Geostatistics as one of the branches of practical statistics Provided study Simultaneous Amounts of Variable and arrangement of variable spatial and temporal observations in the data analysis (Gvvart, 1999). Using geostatistical techniques can be created continuous surface of Statistical properties of Known points(Deutsch, 2002). there are Different methods for the study and characteristics of the groundwater that each of them depending on local conditions And existence statistics and data of sufficient have Accuracy of different. Purpose of this study studies, qualitative zoning of underground water resources In terms of water quality parameters in the city of Kashan, by using geostatistical methods. This area is geographic range of "40, ཱུ, ˚ 50 to" 37, ར, ˚ 51 east longitude, and "37, 31, ˚ 33 to" 22 and ང, ˚ 34 north latitude is In this study is used of methods of kriging, ordinary kriging, Inverse Distance Weights, Radial Basis Function, Local Polynomial Interpolation and Global Polynomial Interpolation. 2- Methodology In this study According to research goals 42 wells in the study area was selected with the appropriate distribution. and Amount elements of groundwater quality in the wells for the period 1380 to 1388 were examined and evaluated. Reasons for selection this period is completeness of statistical data of quality parameter. In the next step all data related to selected quality factors were study In terms of normality According to kolmogorov-smirnov test. After examining of data normality , finally parameters of Ca, Na, SAR, HCO3 for qualitative evaluating groundwater resources in this study were selected. To zones drawing of related to Quality parameters was used of Arc GIS9.3 software. In order to explain the continuity of spatial variables variogram data to a separately with Software GS plus was plotted and analyzed. Finally, with according to two factors RMSE (root mean square error) and R (coefficient sets) Best method for maps drawing of underground water quality were selected in the sity kashan and Aran Bidgol. Discussion After study and determine Fluorescence of Data Suitable variogram to determine the spatial structure and profile Was drawn with Using of GS + software, of variograms Analysis spherical model is the best model Fitted on Qualitative data. Spatial structure based on the standard (C/C+ C0) has been done too, According to the results obtained Measure values for C/C+C0 for every four parameters studied is more than 0/5. Results of evaluation methods showed that Between geostatistical method is most useful for study of variables HCO3, SAR, Ca and Na Methods Ordinary kriging with Higher R values and lower RMSE than the simple kriging is superior. and Between the specific methods for study qualitative variables HCO3, SAR, Ca and Na, respectively, methods, RBF, LPI, RBF and LPI are located. Conclusion In this study was to test normality of data was approved According to the results of spatial analysis of qualitative data in this study, high Influence . Range show that be effective the spherical model for best fit variogram on the data. According to principles of geostatictics, variable that have suitable spatial correlation and variance estimate is lower, fewer samples are needed to estimate(Zehtabyan, 1389), so it will also lower the cost of sampling. Thus, using Analysis variogram Ratio Nugget Effect for parameters, HCO3, SAR, CA and NA respectively 1/76, 0/58, 7/79 and 0/16 is calculated, that all the numbers obtained is small amounts that indicated high accuracy estimate with the variogram of fitted indicates a strong spatial structure for all four parameters is discussed. Also examine the spatial structure according to standard C / C + C0 shows that for the parameters, HCO3, SAR, CA and NA value for this measure, respectively is 0/98, 0/98, 0/92 and 0/99, The results indicative high spatial structure of data. The results of the geostatistical methods were used in this study showed that the method of choice for change mapping of hco3, Method Radial Basis Function to reason Higher R values and low RMSE (R= 0.44 and RMSE= 1.76) Was selected for Drawing of hco3 changes mapping. For SAR change mapping method of ordinary kriging (With values of R =0.75 , RMSE =1.96), also for drowing change mapping of hco3 method of ordinary kriging(with Values of RMSE =5.75 , R =0.41), and for drawing change mapping of na , method Local Polynomial Interpolation(with Values of R=0.55, RMSE =8.24) be selected. main cause reduction of ground waret quality in terms of quality parameters considered in study area is Unsuitable development of agricultural lands and Excessive utilization of ground water Which cause influx of brackish water to these areas.