Quantifying uncertainty in the temporal disposition of groundwater inundation under sea level rise projections - Chambers, Lee A.; Hemmings, Brioch; Cox, Simon C.; Moore, Catherine; Knowling, Matthew J.; Hayley, Kevin; Rekker, Jens; Mourot, Frédérique M.; Glassey, Phil; Levy, Richard (Frontiers in Earth Science, 2023)
Over the next century, coastal regions are under threat from projected rising sea levels and the potential emergence of groundwater at the land surface (groundwater inundation). The potential economic and social damages of this largely unseen, and often poorly characterised natural hazard, are substantial. To support risk-based decision making in response to this emerging hazard, here we present Bayesian modelling framework to map the spatial distribution and temporal variability in the uncertainty of groundwater level rises and inundation, under Intergovernmental Panel on Climate Change (IPCC) projections of Sea Level Rise (SLR). Such probabilistic mapping assessments, which acknowledge the spatial uncertainty of groundwater flow model predictions, in addition to the inherent deep uncertainty of the IPCC-SLR projections themselves, are still almost always lacking. The results presented herein demonstrate the value of history matching for increasing the spatial confidence of posterior groundwater level rise and inundation projections, whilst exploring a model’s capacity to predict changes (rather than absolute values) in relation to a decision threshold. The latter may have profound (decision-making) implications for the extremely large number of at-risk, coastal communities and ecosystems, which are typically data poor.