Determination of groundwater level fluctuation as measure of semi-arid land resources degradation using geostatistical methods (Case Study: Kaboudrahang-Famenin plain)

In recent years, the depletion of groundwater resources has been increased by the population explosionand the development of agriculture and industry. In this study, the geo-statistical methods were used to study the spatial and temporal variations in groundwater level in Kaboudrahang-Famenin plain. For this purpose, available data of region including information about piezometers and monitoring wells were collected and then, database was composed. Next, the control of data accuracy was carried out. For comparison of geo-statistical methods, the variograms were plotted respectively and the different interpolation methods such as kriging (simple model), cokriging and Inverse Distance Weight with powers 1 to 5 (IDW) and radial basis functions (Thin Plate Radial Function, Inverse Multi Quadratic and Multi Quadratic) for groundwater zoning were used. The best interpolation method was selected by using two criteria, Root Mean Square (RMSE) and General Standard Deviation (GSD), and finally the zoning map of groundwater level was drawn in Arc-GIS software. The results of spatial statistical analysis indicated that the best variogram models for groundwater level data in the first period (1989), in the middle period (1993&1999) and the last period (2006) were spherical, circular and pentaspherical models, respectively.Evaluation of various interpolation methods with using "cross validation criteria" showed that in the investigation period, cokriging had the lowest estimation error compared with other interpolation methods. Thus, Cokriging was the most suitable interpolation method. The results of interpolated digital maps during the study period showed that the maximum fall of water table in 17 years was recorded to be 55 meters for central east region of plain. This shows the dramatic reduction in groundwater reserves of the region, which would not lead to industrial and agricultural sustainable development.