Coastal area impact and vulnerability assessment: The point of view of a morphodynamic modeller

Citation
M. Capobianco et al., Coastal area impact and vulnerability assessment: The point of view of a morphodynamic modeller, J COAST RES, 15(3), 1999, pp. 701-716
Citations number
68
Categorie Soggetti
Environment/Ecology
Journal title
JOURNAL OF COASTAL RESEARCH
ISSN journal
07490208 → ACNP
Volume
15
Issue
3
Year of publication
1999
Pages
701 - 716
Database
ISI
SICI code
0749-0208(199922)15:3<701:CAIAVA>2.0.ZU;2-K
Abstract
Long-term (>10 years) prediction of morphological behaviour in the coastal zone in response to both direct and indirect human interference and project ed climatic change is an increasingly important issue in coastal management . As our recognition of the possible impacts increases, so does the need fo r more comprehensive model-based approaches to better assess long term impa cts and plan precautionary interventions. Such models need to he integrated embracing both the morphological subsystem and the ecological subsystem, a nd their interactions in the coastal zone. By explicitly considering the "need for integration between different disci plines", this paper briefly describes possible approaches to modelling long -term dynamics of coastal morphology, particularly the modelling of coastal evolution in the typical situation: limited data and limited process knowl edge, and further complicated by the variability of the coastal space cover and coastal space use. It is argued that progress in long-term modelling o f coastal morphology will be further stimulated by adopting a conceptual fr amework which can embrace all the data, information, knowledge and experien ce concerning the coastal system of interest, whatever form they have. The objective can be accomplished by using a top-down modelling conceptual appr oach which helps to formalise knowledge and experience concerning the coast al area and integrate all the available data, information and models, inclu ding qualitative understanding. Qualitative modelling, which defines tenden cies of evolution, offers an important tool for this goal. The overall appr oach lends itself to being structured into a model-based Decision Support S ystem (DSS), coupled with Geographic Information System (GIS) technology wh ich represent the state-of-the-art of decision support tools in the environ mental field.