Abstract
Shoreline change analysis is a well defined and widely adopted approach for the examination of trends in coastal position over different timescales. Conventional shoreline change metrics are best suited to resolving progressive quasi-linear trends. However, coastal change is often highly non-linear and may exhibit complex behaviour including trend-reversals. This paper advocates a secondary level of investigation based on a cluster analysis to resolve a more complete range of coastal behaviours. Cluster-based segmentation of shoreline behaviour is demonstrated with reference to a regional-scale case study of the Suffolk coast, eastern UK. An exceptionally comprehensive suite of shoreline datasets covering the period 1881 to 2015 is used to examine both centennial- and intra-decadal scale change in shoreline position. Analysis of shoreline position changes at a 100m alongshore interval along 74km of coastline reveals a number of distinct behaviours. The suite of behaviours varies with the timescale of analysis. There is little evidence of regionally coherent shoreline change. Rather, the analyses reveal a complex interaction between met-ocean forcing, inherited geological and geomorphological controls, and evolving anthropogenic intervention that drives changing foci of erosion and deposition.
Highlights
Understanding the primary controls on coastal behaviour over timescales relevant to management remains extremely challenging despite the continuing extension of multi-year monitoring programmes and datasets
This paper presents a new approach to mesoscale shoreline behaviour analysis that combines conventional shoreline change metrics with alongshore segmentation using cluster analysis (Hennig et al, 2015)
Trends and magnitudes calculated from the analysis of relative shoreline positions over different periods in time provide the basis for management decisions and understanding of coastal behaviour worldwide
Summary
Understanding the primary controls on coastal behaviour over timescales relevant to management remains extremely challenging despite the continuing extension of multi-year monitoring programmes and datasets. Shoreline management is increasingly concerned with adaptive responses to coastal change at decadal to centennial scales (Nicholls et al, 2012, 2013), invariably framed by projections of climate change and their consequences at the coast (Zhang et al, 2004; Dickson et al, 2007; Nicholls and Cazenave, 2010). The complex interplay of natural and anthropogenic processes and influences at this mesoscale (see for example Del Río et al, 2013) makes it difficult to attribute causes to observed changes. Sea-level rise, elevated storm-surge water levels, high energy storm waves, depletion of sediment budgets and the construction of sea walls are all capable of promoting beach erosion. The time-scales over which such effects are manifest and the persistence of the associated morphological changes can be very different
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