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The AAPG/Datapages Combined Publications Database

Environmental Geosciences (DEG)

Abstract


AAPG Division of Environmental Geosciences Journal
Vol. 7 (2000), No. 3., Pages 137-148

GIS Previous HitModelingNext Hit of Impacts of an Accelerated Rate of Sea-Level Rise on Coastal Inlets and Deeply Embayed Shorelines

Werner G. Hennecke, Peter J. Cowell

Abstract

Scientific evidence suggests that an accelerated sea level rise will have a significant impact on shorelines over the next 50–100 years. Hence, coastal management and planning in the near future needs to evaluate the physical impacts on vulnerable coastlines. In Australia, the need to estimate potential coastal erosion and potential coastal property damage is acute, because >80% of the Australian population live in coastal areas. However, a limitation that has to be considered in Australia and in many other parts of the world is the lack of data for the coastal zone. Principles drawn from presently available coastal process models are used in this study to identify the potential physical impacts of sea level rise on barrier inlets and deeply embayed shorelines, including estuaries.

The models (Hybrid-Bruun, Aggradation, and Translation Models) are implemented into a geographic information system (GIS) environment as a set of equations, which are then applied to the terrain data. In principle, these are data that exist in the public domain, such as the 1:25,000 topographic map series and bathymetric maps at various scales. Changing parameter values in the models (such as the rate of sea level rise, Previous HitdepthNext Hit of closure, dune height, the size of the flood-tide delta, sediment input from outside the embayment, or the rate of flood-tide delta translation) allows the user to run a number of impact scenarios for each model and locality. Output maps of these scenarios typically present the spatial distribution of hazards caused by rising sea level in a grading triage of risk classes: a definite risk, an uncertain risk, and a negligible risk according to each model. These Previous HitmodelingTop results can then be used by local government authorities for further detailed studies of individual sites potentially at risk.


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