Abstract
Groundwater quality is a major environmental aspect which needs to be analyzed and managed depending on its spatial distribution. Utilization of insufficient management of groundwater resources in Gaza Strip, Palestine, produces not only a reduction in quantity but also deterioration in quality of groundwater. The aim of this study is to provide an overview for evaluation of groundwater quality in the Gaza Strip area as a case study for applying spatially distributed by using Geographic Information System (GIS) and geostatistical algorithms. The groundwater quality parameters, pH, total dissolved solids, total hardness, alkalinity, chloride, nitrate, sulfate, calcium, magnesium, and fluoride, were sampled and analyzed from the existing municipal and agricultural wells in Gaza Strip; maps of each parameter were created using geostatistical (Kriging) approach. Experimental semivariogram values were tested for different ordinary Kriging models to identify the best fitted for the ten water quality parameters and the best models were selected on the basis of mean square error (MSE), root mean square error (RMSE), average standard error (ASE), and root mean square standardized error (RMSSE). Maps of 10 groundwater quality parameters were used to calculate the groundwater quality index (GWQI) map using the index method. In general, the results showed that this integrated method is a sufficient assessment tool for environmental spatially distributed parameters.
Highlights
Three billion people live without access to adequate sanitation systems necessary for reducing exposure to water-related diseases
If the root mean square error (RMSE) is smaller than the average standard error (ASE), the variability of the predictions is overestimated; if the RMSE is greater than the ASE, the variability of the predictions is underestimated
After conducting the cross validation process, maps of Kriging estimates were generated which provided a visual representation of the distribution of the groundwater quality parameters
Summary
Three billion people live without access to adequate sanitation systems necessary for reducing exposure to water-related diseases. Gaza Strip faces both groundwater quality and quantity issues as the considerable amount of water demand is fulfilled from groundwater. Many researchers applied geostatistical approach for analysis of spatial variations of groundwater characteristics [6]-[9]. Prediction of values at other locations based upon selectively measured values represents a viable alternative. In this case, to predict the concentration of pollutants at unmeasured locations, the geostatistical techniques can be used [11]. Kriging is a special case from IDW and other interpolation methods by taking into consideration the difference of estimated parameters. Geostatistical approach and Kriging methods have several advantages, such as giving fair predictions with minimum variance and taking the spatial correlation between the data listed at various places. On the other hand, Kriging gives information on interpolation errors about the reliability of estimates [13]-[15]
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