Dunedin groundwater monitoring and spatial observations

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Cox SC, Ettema MHJ, Mager SM, Glassey PJ, Hornblow S, Yeo S. 2020. Dunedin groundwater monitoring and spatial observations. Lower Hutt (NZ): GNS Science. 86 p. (GNS Science report; 2020/11). doi:10.21420/AVAJ-EE81.

Dunedin City has a large number of assets and critical infrastructure sitting on a low-lying coastal plain that is underlain by a largely unseen and relatively poorly understood hazard. Shallow groundwater in this area limits the unsaturated ground available to store rain and runoff, promotes flooding and creates opportunities for infiltration into stormwater and wastewater networks. Groundwater levels are expected to rise as sea level rises, causing greater frequency of flooding and/or direct inundation once it nears the ground surface. Dunedin’s future flooding concerns can be addressed through expensive and complex hard infrastructure solutions or by adaptive solutions that take into account the natural underlying conditions of low-lying Dunedin. Adaptive solutions are no less complex but may save time and money in the city’s effort to manage flooding and groundwater inundation. This report outlines a basis for future planning and mitigation of natural hazards in Dunedin.
Monitoring network developments in 2019 have significantly improved information on Dunedin’s groundwater. Groundwater level, temperature and specific conductance observations at 15 minute intervals have been collated into a time-series database. A wide variety of statistics have been generated for each site, including median, maximum, minimum, 95th and 5th percentiles, mean, standard deviation and range of groundwater levels. Other collated site data include: tidal amplitude, efficiency and phase lag; distance from harbour or sea; groundwater sample pH, electrical conductivity; modelled seawater percentage; and a rainfall response index reflecting the local efficiency of rainfall recharge.
This report presents derivative ArcGIS data and spatial analysis of these groundwater observations, particularly factors that influence the water table position and geometry. A series of statistical surfaces have been generated to represent the present-day (2019) water table elevation and depth to groundwater, the response to rainfall recharge and tidal forcing, the available subsurface storage of rain and the position of stormwater and wastewater networks relative to the water table. The level of groundwater is influenced by subsurface flow and runoff from the hills in the west and north but will be further encroached from the south and east by sea-level rise in the harbour and ocean in the future.
Simple geometric models have been developed using the present shape and position of the water table, combined with tidal fluctuations, to depict scenarios of groundwater levels with 30, 50 and 80 cm sea-level rise. These geometric models are strongly empirical, with many implicit assumptions and caveats – particularly, that they do not account for groundwater flow and possible changes in water-budget mass balance. Although many variables and controlling processes are simplified into a single parameter, the projected groundwater levels highlight how local variations in the water table shape and slope interact locally with the ground elevation or infrastructure networks. As statistical surfaces representing a period of about one year, they may not necessarily represent short-term flow but are suited to engineering projects, such as foundation design and probabilistic assessment of liquefaction vulnerability.
Dunedin faces a particularly demanding challenge with sea-level rise due to the shape of its topography and coastline, with encroachment from both the harbour and the ocean onto its narrow coastal plain. A valuable lesson from this case study is that the subtle slope and shape of the water table, which has variability at kilometre-scales even in a seemingly flat low-lying area, interacts with land-surface topography to generate notable differences in the depth of groundwater. There are suburb-scale variations in the elevation of the water table and related available subsurface storage that are important for engineering solutions to maintain habitable land. The groundwater spatial datasets, such as water table elevation and rainfall recharge, provide tools from which inundation or flood-vulnerable areas can be identified and other hazards, such as liquefaction susceptibility, modelled. They will also enable monitoring to be targeted on key areas of groundwater-network exchange so that hazard thresholds and any critical tipping points that might lead to infrastructure system collapse can be identified. (auth)