System-scale detection of erosion and deposition is crucial in order to
assess the transferability of findings from scaled laboratory and small
field studies to larger spatial scales. Increasingly, synoptic remote
sensing has the potential to provide the necessary data. In this paper,
we develop a methodology for channel change detection, coupled to the
use of synoptic remote sensing, for erosion and deposition estimation,
and apply it to a wide, braided, gravel-bed river. This is based upon
construction of digital elevation models (DEMs) using digital
photogrammetry, laser altimetry and image processing. DEMs of
difference were constructed by subtracting DEM pairs, and a method for
propagating error into the DEMs of difference was used under the
assumption that each elevation in each surface contains error that is
random, independent and Gaussian. Data were acquired for the braided
Waimakariri River, South Island, New Zealand. The DEMs had a 1.0 m
pixel resolution and covered an area of riverbed that is more than 1 km
wide and 3.3 km long. Application of the method showed the need to use
survey-specific estimates of point precision, as project design and
manufacturer estimates of precision overestimate a priori point
quality. This finding aside, the analysis showed that even after
propagation of error it was possible to obtain high quality DEMs of
difference for process estimation, over a spatial scale that has not
previously been achieved. In particular, there was no difference in the
ability to detect erosion and deposition. The estimates of volumes of
change, despite being downgraded as compared with traditional
cross-section survey in terms of point precision, produced more
reliable erosion and deposition estimates as a result of the large
improvement in spatial density that synoptic methods provide.