عنوان مقاله [English]
Determination of groundwater quality is an important issue in watershed management. The aim of this study was to investigate the spatial variability of some properties of Kerman groundwater using geostatistical methods. For this, groundwater quality data including soluble calcium, magnesium, sodium, bicarbonates, sulphates, pH, EC, SAR, TDS and TH for spring season of 2009 were collected. Interpolation analysis was done using Kriging, Co-Kriging, inverse distance weight (IDW) and normal distance weight (NDW) methods. The best interpolation method was chosen through root mean square error, mean absolute error and Pearson’s coefficient parameters. Result showed that the best fitted model for magnesium and pH was linear to sill, whereas for the other groundwater properties the Gaussian’s model was the best. Spatial dependency for bicarbonates and pH was moderate, while for the other ones, strong dependencies were observed. The result also indicated that for all the groundwater properties, Kriging with the Pearson’s coefficient ranging from 0.695 to 0.851 was the best algorithm. In addition to Kriging, the NDW and IDW methods found to be appropriate for the estimation of all the parameters except for EC and TDS. For these two latter ones, additional to Krging, the Co-Kriging method led to suitable estimates. The prepared maps showed that the amounts of bicarbonates and pH were higher at the north and south sides of the study area, respectively. The amounts of the other properties were minimum at the east and north east, while increased toward the west and south west.