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  • Grid and vector (poly) datasets representing a forecast state of groundwater in Dunedin under present (SLR=000) and future conditions of sea level rise (SLR=010, 020, 030 cm etc where [OFF] represents increments of changing sea level). Layers are in NZTM (NZGD2000 EPSG: 2193) coordinates, named using a convention where: GWL= groundwater level (m, NZVD2016 EPSG:7879); DTW = depth to groundwater (m, rel to ground LiDAR 2021); MED = condition at median level; p95 = condition at a high 95th percentile level; MHWS = condition at mean high water springs; ESL = condition at storm-tide of particular extreme sea level ARI; RAINstor = maximum possible subsurface storage of rainfall (in mm); [OFF] = an amount of sea level rise in 10cm increments; [ARI] = average recurrence interval of ESL in years; [AFI] = average recurrence interval of a particular 12hr rainfall exceedance in years. Polygons define either places where groundwater is emergent (DTW≤0) under a given forecast, or places where a rainfall depth at AFI exceeds the available subsurface storage (and any infiltration to groundwater should no longer be possible).

  • Dunedin City in the South Island of New Zealand has many 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. This zipped archive contains ArcGIS 10.8 geodatabases and spatial analysis of data gathered from a shallow groundwater monitoring network between 6/3/2019 and 1/5/2023. Data are licenced under Creative Commons Attribution 4.0 (CC-BY-4.0) licence without warranty. A series of statistical surfaces represent the present-day (2023) water table elevation and depth to groundwater, the response to rainfall recharge and tidal forcing, the available subsurface storage of rain infiltration. Simple geometric models have also been developed using the present shape and position of the water table, combined with tidal fluctuations, to forecast the future state of groundwater levels at 10 cm increments of sea level rise (up to 1 m). The 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. They are best considered as a worst-case analysis of groundwater-related contribution to hazard and how this will evolve over time. Further description of these data, and implications from the analysis, can be found in Cox et al. (2023) GNS Science Report 2023/43 doi:10.21420/5799-N894.

  • A catalogue of scenarios for tsunami-generating earthquakes has been constructed. The scenarios are grouped by the regions of potential tsunami origins around the Pacific Rim as defined by MCDEM (2008). The regions are divided into subregions representing unique source areas. Within each subregion propagation models have been computed for scenarios associated with earthquakes at intervals of 0.2 in MW. Forecasts of the maximum wave-heights around the New Zealand coasts associated with each scenario are expressed in terms of the maximum water–level (m) attained within each MCDEM coastal zone for tsunami warnings. This maximum water-level information has been put into the form of a threat–level for each coastal zone. By using the maximum water-level anywhere within the coastal zone as an estimate of the threat-level a degree of conservatism is incorporated. The tsunami threat level models included here are the best forecast models that the Duty Team and GeoHazard Analysts currently has to advise MCDEM in the immediate aftermath of an earthquake. Although these models were created with best endeavours, they do have limitations. When time allows they should be subject to interpretation and revision by the TEP. Under no circumstances should these models be released outside of GNS Science. DOI: https://doi.org/10.21420/9JJV-WY50 Cite as: GNS Science. (2020). Tsunami Scenario Database [Data set]. GNS Science. https://doi.org/10.21420/9JJV-WY50