Abstract

Groundwater is present at shallow depth under many coastal low-lying cities. Despite the importance of protecting coastal urbanised areas from flooding and climate-change-induced sea-level rise, the effects of shallow groundwater fluctuations are rarely investigated. The aim of this study was to determine characteristics of shallow groundwater, including spatial and temporal trends in depths to groundwater and their relationship to natural and anthropogenic stressors. The study uses depth to groundwater measurements from a uniquely extensive and densely spaced monitoring network in Ōtautahi/Christchurch, New Zealand. Data-driven analysis approaches were applied, including spatial interpolation, autocorrelation, clustering, cross-correlation and trend analysis. These approaches are not commonly applied for groundwater assessments despite the potential for them to provide insights and information for city-wide systems. The comprehensive approach revealed discernible clusters and trends within the dataset. Responses to stresses such as rainfall events and stream flow were successfully classified using clustering analysis. The time series analysis indicated that in areas of shallow groundwater, low variation in levels occurred and this was also found using clustering. However, attributing some clusters to specific hydrogeological attributes or stressors posed challenges. The primary feature in hydrograph classification proved to be the proximity to tidal rivers and their correlation with tidal signals. These results highlight the value of using large datasets to characterise spatial and temporal variability of shallow groundwater in urban coastal settings and to assist with monitoring infrastructure planning in the face of future climate-change hazards.

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