A GIS approach to model sediment reduction susceptibility of mixed sand and gravel beaches.
The morphological form of mixed sand and gravel beaches is distinct, and the process/response system and complex dynamics of these beaches are not well understood. Process response models developed for pure sand or gravel beaches cannot be directly applied to these beaches. The Canterbury Bight coastline is apparently abundantly supplied with sediments from large rivers and coastal alluvial cliffs, but a large part of this coastline is experiencing long-term erosion. Sediment budget models provide little evidence to suggest sediments are stored within this system. Current sediment budget models inadequately quantify and account for the processes responsible for the patterns of erosion and accretion of this coastline. We outline a new method to extrapolate from laboratory experiments to the field using a geographical information system approach to model sediment reduction susceptibility for the Canterbury Bight. Sediment samples from ten representative sites were tumbled in a concrete mixer for an equivalent distance of 40 km. From the textural mixture and weight loss over 40 km tumbling, we applied regression techniques to generate a predictive equation for Sediment Reduction Susceptibility (SRS). We used Inverse Distance Weighting (IDW) to extrapolate the results from fifty-five sites with data on textural sediment composition to field locations with no data along the Canterbury Bight, creating a continuous sediment reductions susceptibility surface. Isolines of regular SRS intervals were then derived from the continuous surface to create a contour map of sediment reductions susceptibility for the Canterbury Bight. Results highlighted the variability in SRS along this coastline.
Eikaas
Hans S
HS
Department of Geography, Environmental Science Programme, University of Canterbury, 4800 Private Bag, Christchurch, New Zealand. h.eikass@geog.canterbury.ac.nz
Hemmingsen
Maree A
MA
D001493:Bathing Beaches; D003247:Conservation of Natural Resources; D040362:Geographic Information Systems; D019015:Geologic Sediments / Q000032:analysis*; D008962:Models, Theoretical; D009520:New Zealand; D010316:Particle Size; D012044:Regression Analysis; D012822:Silicon Dioxide; D014872:Water Movements
D012822:Silicon Dioxide