Comparison GIS-Based interpolation methods for mapping groundwater quality in the state of Qatar

Abstract

Groundwater (GW) quality deterioration is one of the main water security issues in Qatar. GW in Qatar is over-exploited for agriculture activities that caused saltwater intrusion in the coastal areas and some inland GW. The selection of an appropriate interpolation method is crucial for producing a reliable map of spatial variability in environmental research and the decision-making process. In this study, 41 GW samples were used to produce interpolated maps and reveal the spatial variability of GW parameters namely: pH, electrical conductivity (EC), total dissolved solids (TDS), sodium adsorption ratio (SAR), major cations, and anions, and some trace elements, using spatial interpolated methods in geostatistical tool (ArcGIS Software). Multiple mapping methods were used to compare the current results with the national and international guidelines to give a relevant decision. Three different interpolated methods, namely inverse distance weighted interpolation (IDW), radial basis functions (RBFs), and simple Kriging (SK) were used to produce interpolated maps. Cross-validation was applied to assess the best-fit interpolation method. The result shows that the SK model was the optimum interpolated method for the most of the variable data. While the RBFs model was the best interpolation method for selenium and boron data. The IDW model was the best-interpolated method for sodium, TDS, SAR, and potassium data. The IDW and RBFs methods produced interpolation maps that help visualizing the location of GW within and above the guidelines. The analysis of spatial variability in the study area revealed high levels of TDS, EC, SAR, and some cations and anions in the coastal and south Qatar. While the spatial variability for nitrate and boron suggested the influence of human activities. A thorough understanding of the status of GW quality in Qatar is a significant tool for the GW management and decision-makers.