Decision-support modelling for an uncertain future: developing forecasts of sea level rise impacts on groundwater

<p>The low-lying coastal urban area of South Dunedin, New Zealand, is particularly susceptible to the impacts of sea-level rise, which is projected to rise by as much as 1.2 m by 2100 under high emissions scenarios.&#160; Currently, more than 2,500 homes are < 50 cm above mean sea level and groundwater levels are typically < 1 m below the surface.&#160; As sea levels rise, groundwater levels are also predicted to rise, increasing the probability of inland groundwater inundation (groundwater flooding) throughout South Dunedin.&#160; It is therefore imperative to develop an improved understanding of the physical controls, and the uncertainty associated with these controls, on the occurrence and severity of the groundwater inundation hazard caused by rising sea levels.&#160; We deploy a simple and fast-running model within a highly-parametrised Uncertainty Quantification (UQ) workflow to investigate the adequacy of steady-state-only versus transient calibration when assessing the risks of groundwater inundation.&#160; The decision to proceed beyond a steady-state-only calibration is time-consuming and costly (often vastly so) and requires careful attention and further research in practical application.&#160; The reduction in uncertainty of decision-relevant forecasts accrued through implementing a transient calibration procedure (or lack thereof), given existing and yet to be acquired data, is the metric by which the modelling is judged.&#160; Firstly, the workflow involves history matching and uncertainty analysis implemented through PESTPP-IES to explore and reduce the uncertainty of decision-relevant forecasts (spatial groundwater elevation and drain fluxes).&#160; Secondly, a paired complex-simple model analysis is used to: explore 1) the potential uncertainty reductions in decision-relevant forecasts achieved through transient calibration and 2) the potential introduction of unquantifiable bias of decision-relevant forecasts introduced by the competing calibration procedures.</p>