Assessing Groundwater Contamination Risk at Coastal Crude Retention Facility

Thesis Abstract

Groundwater quality in coastal regions is increasingly exposed to anthropogenic pressures from crude oil storage and handling facilities, raising concerns about subsurface contaminant transport, long-term aquifer vulnerability, and public health risks. This study addresses the gap between facility-scale operational practices and regional groundwater security by evaluating contamination risk at a coastal crude retention facility, with a focus on identifying pathways, drivers, and thresholds that govern contaminant migration. The aim is to quantify groundwater contamination risk and to develop a decision-support framework for proactive risk management. Specific objectives are (1) characterize hydrogeological setting and baseline groundwater quality within a 2 km radius of the facility; (2) identify and quantify potential contaminant sources and their fluxes, including hydrocarbon residuals, heavy metals, and degraded hydrocarbons; (3) evaluate the influence of hydraulic gradients, tidal cyclicity, and surface-water–groundwater interactions on plume development; (4) apply multivariate and geostatistical analyses to delineate contaminant plumes and to estimate concentration–response thresholds; (5) test the applicability of a conceptual and numerical vulnerability model to coastal aquifers under crude oil retention operations; and (6) formulate evidence-based recommendations for monitoring, mitigation, and emergency response. The methodology integrates a mixed-methods approach anchored in a quantitative hydrogeochemical framework and a qualitative risk appraisal. The study adopts a cross-sectional design across three adjacent hydrogeological units and a 24-month monitoring window to capture seasonal and tidal variability. The population comprises groundwater samples from 40 strategically distributed monitoring wells, 8 piezometers, and 6 surface water sampling points, complemented by facility operation records and spill-response logs. Data collection employs standardized sampling protocols for volatile organic compounds (VOCs), total petroleum hydrocarbons (TPH), polycyclic aromatic hydrocarbons (PAHs), major ions, and stable isotopes (?13C, ?D) to facilitate source apportionment. Instrumentation includes gas chromatography–mass spectrometry (GC-MS) for hydrocarbon suites, Fourier-transform infrared spectroscopy (FTIR) for rapid screening, ion chromatography for anions and cations, and inductively coupled plasma mass spectrometry (ICP-MS) for trace metals. Groundwater level data are collected via automated level loggers to quantify drawdown effects. Methodological rigor is ensured through quality assurance/quality control (QA/QC) protocols, including field blanks, trip blanks, duplicates, and standard reference materials. Data analysis proceeds through a sequence of statistical and geostatistical steps. Descriptive statistics summarize baseline water quality, while Mann-Whitney U and ANOVA tests examine spatial and temporal differences. Regression analyses (stepwise and penalized) quantify relationships between hydrochemical indicators and potential predictors such as distance from storage units, subsurface lithology, and tidal stage. Multivariate techniques (principal component analysis, positive matrix factorization) identify contaminant sources, and receptor models (UNMIX, PMF) support apportionment. Geostatistical interpolation (ordinary Kriging) constructs contaminant plumes, with uncertainty quantified via kriging variance. A two-layer numerical groundwater flow and transport model (MODFLOW coupled with MT3DMS) simulates plume evolution under historic operation scenarios and hypothetical spill events. The study integrates theoretical perspectives from the Theory of Planned Behavior to interpret operational deviations influencing risk, and applies the Hydrological Connectivity and Vulnerability framework to quantify aquifer susceptibility. Expected findings include (i) delineation of a shallow, tide-influenced contaminant plume with detectable hydrocarbons up to 1.5 km downgradient under peak pumping; (ii) significant correlations between hydrocarbon indicators and proximity to leakage-prone infrastructure; (iii) identifiable seasonal variation driven by groundwater table oscillations and tidal forcing; and (iv) a validated vulnerability model capable of ranking sites by contamination risk, informing targeted monitoring. Contributions to knowledge encompass (a) empirical risk assessment of groundwater contamination associated with coastal crude retention facilities in tropical/subtropical coastal aquifers, (b) an integrated hydrogeochemical–geostatistical framework for plume delineation and source apportionment in dynamic coastal settings, and (c) a transferable risk-management protocol combining monitoring optimization, threshold-based alerting, and adaptive remediation planning. The study concludes that a combination of proactive surveillance, enhanced containment measures, and timely response protocols materially reduces contamination risk, with recommendations including (i) installation of multiple downgradient monitoring networks and tidal-stage-aware sampling schedules; (ii) implementation of secondary containment and vapor control measures for storage units; (iii) deployment of a site-specific aquifer vulnerability map to guide mitigation investments; and (iv) development of an incident response plan anchored in the Hazardous Materials and Coastal Hydrology governance framework.