Abstract
Long-term (>10 years) prediction of morphological behaviour in the coastal zone in response to both direct human interference and projected climatic change is an increasingly important issue in coastal management. recognition of the possible impacts increases, so does the need for more comprehensive model-based better assess long term impacts and plan precautionary interventions. Such models need to be integrated both the morphological subsystem and the ecological subsystem, and their interactions in the coastal By explicitly considering the "need for integration between different disciplines", this paper briefly describes approaches to modelling long-term dynamics of coastal morphology, particularly the modelling of coastal the typical situation: limited data and limited process knowledge, and further complicated by the variability coastal space cover and coastal space use. It is argued that progress in long-term modelling of coastal will be further stimulated by adopting a conceptual framework which can embrace all the data, information, and experience concerning the coastal system of interest, whatever form they have. The objective can by using a top-down modelling conceptual approach which helps to formalise knowledge and experience the coastal area and integrate all the available data, information and models, including qualitative Qualitative modelling, which defines tendencies of evolution, offers an important tool for this goal. proach lends itself to being structured into a model-based Decision Support System (DSS), coupled with Information System (GIS) technology which represent the state-of-the-art of decision support tools mental field.
| Original language | English |
|---|---|
| Pages (from-to) | 701-716 |
| Number of pages | 16 |
| Journal | Journal of coastal research |
| Volume | 15 |
| Issue number | 3 |
| Publication status | Published - 1999 |
Keywords
- Sea-level rise
- Climate change
- Coastal management
- Qualitative modelling
- Integrated modelling
- Long-term morphodynamics
- Vulnerability