GWSDAT-Based Spatiotemporal Analysis of MTBE and BTEX Plumes in Jordanian Aquifers

Abstract

This study aims to characterize the occurrence and spatial-temporal behavior of methyl tert-butyl ether (MTBE) and the gasoline-related aromatic hydrocarbons benzene, toluene, ethylbenzene, and xylenes (BTEX) in groundwater of the Amman-Zarqa Basin, Jordan. Groundwater from 66 wells representing shallow and deeper aquifer settings was sampled and analyzed for MTBE and BTEX using gas chromatography-mass spectrometry, with USEPA Method 524.2 and DIN 38407-F9 used as the principal analytical references. Major-ion chemistry and field parameters were evaluated to define the hydrochemical framework, while the Groundwater Spatiotemporal Data Analysis Tool (GWSDAT) was applied to visualize concentration patterns and assess temporal tendencies with Mann-Kendall trend statistics. Detectable MTBE/BTEX concentrations were reported in 32 wells and were generally low (approximately 1.0-1.8 µg/L). Detections were concentrated in shallow groundwater in the Seil Zarqa-Awjan/Russeifa-Zarqa corridor, where fuel stations, petroleum handling infrastructure, and a shallow permeable aquifer increase vulnerability to releases. Groundwater chemistry was dominated by Ca-Mg-Cl and Na-Cl facies, with substantial variability in salinity and redox conditions. GWSDAT outputs delineated coherent areas of elevated modeled concentration and supported comparison of temporal behavior among monitoring locations. Because the analytical reporting limit was approximately 1 µg/L, model smoothed concentrations below this limit are interpreted only as screening-level predictions and not as confirmed detections or definitive plume boundaries. The results support risk-based monitoring of shallow urban groundwater, improved integrity management of underground storage tanks, and continued long-term sampling to distinguish persistent contamination from short-term variability. Article impact statement: Low-level MTBE and BTEX detections are concentrated in vulnerable shallow groundwater; GWSDAT provides a useful screening framework when model predictions are interpreted in relation to the analytical reporting limit.