Evaluation and mapping groundwater quality us-ing geostatistics for sustainable land management in Darb El-Arbaein Area, South of western desert Egypt

Assessing the vulnerability of aquifers is the first step toward careful management of groundwater resources. The groundwater quality has to be evaluated to avoid or, at least, to minimize impacts on agriculture. The main objective of this study was to sit up a simple method to assess the groundwater quality and to map their spatial variation in terms of suitability for irrigation in Darb E1-Arbaein area and the complementary objective was to demon- itrate the GIS capabilities in exploring the full value of environmental data through spatial analysis and visual display of geographic information. Thirty six surveyed wells represented four villages with GPS data were used to assess and map the groundwater quality. For Calculating the Water Quality Index (WQI), 13 parameters (EC- pH- CI- SAR- RSC- B- Zn -Cu -Fe �Mn- Pb- Ni and Cd) hav been considered those. The results of analyses have been used to map and predict models for water quality. The data were imported into the Gtory IS software and the different water quality maps were produced. The geostatistical analysis was used for exploratory data analysis. The results showed that the groundwater in the study area has PH values of 7 to 8 and EC values ranging from 642 to 2686 � Scm. 1 The concentration of chlorides in most of the areas is high with a maximum of 570.86 ppm. The SAR values range from 1.83 to 8.47. The concentrations of heavy metals are lower than the permissible recommended limits .The high salinity was due to the high chloride concentration in the groundwater. The WQl of the studied samples ranges from 47.9 to 88.6; most of the samples ( 26 samples) fall in the Doubtful WQl category; three samples fall in the moderate WQl and seven samples fall in the high WQl category. Groundwater samples that fall in the low salinity hazard class with high WQl can be used for the irrigation for most crops and the majority of soils. The present study demonstrated a high efficiency for GIS to analyze complex spatial data and groundwater quality mapping .