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A number of statistical techniques to analyze and model coastal morphological evolution over yearly and decadal (i.e., long-term) time scales based on field data are presented. After a general introduction to long-term morphological modeling, mainly linear methods are discussed, whereas nonlinear methods are treated in a companion paper (SOUTHGATE et al., 2001). The theoretical background to the methods introduced is summarized and examples of field applications are given to illustrate each method. High-quality field data sets from different sites in the world, including Germany, The Netherlands, and United States, were employed in these examples. The analysis and modeling techniques used encompassed bulk statistics (mean, standard deviation, correlation etc), random sine functions, empirical orthogonal functions, canonical correlation analysis, and principal oscillation pattern analysis. Besides an evaluation of how suitable respective technique is for analyzing and modeling long-term morphological evolution, some general observations are presented regarding scales of morphological response as derived from the field applications. Data describing the evolution of both natural and anthropogenically affected coastal systems were studied. All methods investigated proved their usefulness for extracting characteristics of long-term morphological evolution, as well as for modeling this evolution, when applied under the right circumstances. However, more sophisticated techniques rely on more data in time and space, which is typically the limiting factor in the application of statistical methods as those presented here. [ABSTRACT FROM AUTHOR]

A number of techniques for non-linear analysis of time series data have been developed in recent years and applied in many environmental sciences. In this paper, some of these techniques are reviewed and their usefulness for coastal morphological data assessed, with examples in coastal morphology and related fields where these are available. The methods reviewed are time-delay embedding techniques, singular spectrum analysis, forecasting signatures, fractal analysis and neural networks. It is expected that readers from diverse backgrounds such as statistics, environmental modeling, and data measurement would be interested in this subject. Accordingly, introductions have been provided for some concepts and background material. These include the general purposes of data analysis, the approaches traditionally used by statisticians and physical scientists, the general nature of coastal morphological data, and the distinction between linear and non-linear analysis methods. It is concluded that the information potentially provided by these techniques is essential in understanding the generic behavior of coastal morphology on yearly and decadal timescales, and hence in constructing models and making forecasts of future morphological evolution. However, for these purposes, non-linear data analysis techniques usually require longer data series, and higher spatial and temporal resolution, than is available in present coastal morphological data sets. Data from remote sensing sources have the potential to meet these requirements. [ABSTRACT FROM AUTHOR]

Technologies are considered tools to increase the number of "available options" and to "enlarge the freedom of action" of society to achieve specific objectives. One such objective is sustainable development of the coastal zones. One way to achieve this is via integrated coastal zone management (ICZM): the integration of otherwise sectoral management activities. ICZM is not yet a widespread practice. Even in situations where integrated management is attempted, the role of technologies that might be deployed on the coastal zone to satisfy other societal needs or to provide a solution to specific problem, is not always adequately considered. True integration requires an understanding of how a technology is influenced by or impacts the surrounding natural, economic, and social environment. The present article describes an analysis of the role and use of technologies in the European Union Demonstration Programme on ICZM. [ABSTRACT FROM AUTHOR]

A river basin--oriented approach was developed to support the sustainable management of human activities in a coastal area of Regione Abruzzo, Italy. Consensus and collaboration between the public, different sectoral and territorial administrations, and the economic actors was identified as a crucial prerequisite for the long-term achievement of sustainable coastal development for this region and to make existing developments sustainable. The RICAMA (Rationale for Integrated Coastal Area Management) Project was set up on a regional scale to integrate the natural and economic information in a comprehensive integrated coastal planning, management, and development framework. To achieve this objective, 19 coastal municipalities, three provinces, and one regional government, each with their sectoral services (and their sectoral management activities), needed to be "networked" to promote effective sharing of information and a coordinated approach to management. A "wide area network" was developed that includes other authorities, stakeholders, and the general public. The methodology used to support the network is based on (i) suitable and updated information about the coastal state, (ii) use of informed maintenance strategies, (iii) use of Environmental Impact Assessment and Strategic Environmental Assessment for the assessment of goodness of projects/plans, (iv) adoption of an Environmental Management System for structuring the management actions at various (administrative) levels, and (v) adoption of soft intervention technologies. [ABSTRACT FROM AUTHOR]

Discusses technologies that can help reduce the vulnerability of coastal zones to climate change. Coastal zone management; Development of information and awareness for adaptation in coastal zones; Recognition of the benefits of soft protection.

Uncertainty plays a major role in Integrated Coastal Zone Management(ICZM). A large part of this uncertainty is connected to our lack ofknowledge of the integrated functioning of the coastal system and tothe increasing need to act in a pro-active way. Increasingly, coastal managers are forced to take decisions based on information which issurrounded by uncertainties. Different types of uncertainty can be identified and the role of uncertainty in decision making, scientific uncertainty and model uncertainty in ICZM is discussed. The issue of spatial variability, which is believed to be extremely important in ICZM and represents a primary source of complexity and uncertainty, isalso briefly introduced. Some principles for complex model building are described as an approach to handle, in a balanced way, the available data, information, knowledge and experience. The practical methodof sensitivity analysis is then introduced as a method for a posterior evaluation of uncertainty in simulation models. We conclude by emphasizing the need for the definition of an analysis plan in order to handle model uncertainty in a balanced way during the decision makingprocess. [ABSTRACT FROM AUTHOR]

Long-term (>10 years) prediction of morphological behaviour in the coastal zone in response to both direct and indirect human interference and projected climatic change is an increasingly important issue incoastal management. As our recognition of the possible impacts increases, so does the need for more comprehensive model-based approaches to better assess long term impacts and plan precautionary interventions. Such models need to be integrated embracing both the morphological subsystem and the ecological subsystem, and their interactions in the coastal zone. By explicitly considering the 'need for integration between different disciplines', this paper briefly describes possibleapproaches to modelling long-term dynamics of coastal morphology, particularly the modelling of coastal evolution in the typical situation: limited data and limited process knowledge, and further complicated by the variability of the coastal space cover and coastal space use. It is argued that progress in long-term modelling of coastal morphology will be further stimulated by adopting a conceptual framework which can embrace all the data, information, knowledge and experience concerning the coastal system of interest, whatever form they have. The objective can be accomplished by using a top-down modelling conceptual approach which helps to formalise knowledge and experience concerning the coastal area and integrate all the available data, information and models, including qualitative understanding. Qualitative modelling, which defines tendencies of evolution, offers an important toolfor this goal. The overall approach lends itself to being structuredinto a model-based Decision Support System (DSS), coupled with Geographic Information System (GIS) technology which represent the state-of-the-art of decision support tools in the environmental field. [ABSTRACT FROM AUTHOR]