Shorelines are constantly responding to forcing conditions associated with waves, tides, precipitation, wetting/drying, wind, sediment supply, large wood...the list goes on and on. The video above was shot at Kalaloch, Washington during a winter storm event, and provides a visual sense of the forces that beaches and shorelines are frequently exposed to.
So this is all fine and good - we would expect shorelines to change in response to these forces, and it is of interest from a scientific perspective to understand the processes that drive shoreline change and recovery. However, there is also a distinct, and hopefully obvious, societal interest in understanding patterns of change, and in particular erosion trends in shorelines. That interest is, of course, because we have put a lot of things that we value in the way of eroding shorelines.
Measuring long-term trends in shorelines, though, is surprisingly difficult. I employ my own approaches based on surveying methods, but they are field-based and time-consuming and therefore limited in the geographic scope that they can be applied to. In general, prior to survey based methodologies shoreline change analyses made use of aerial photography...which is very useful because of the time-frame over which trends can be inferred, but generally limited by the limited temporal frequency and the varying quality of aerial photographs.
So this problem associated with developing long-term trends in shorelines over large spatial scales remains an on-going challenge. A few years ago, as part of an AGU annual meeting workshop, I was invited to spend a day at the Google office that handles Google Earth and Google Earth Engine, and learned about Google's efforts to hoover up the full record of LandSat imagery dating back to the 1980's and build them into a cohesive global dataset with applications to a variety of problems and questions.
As a consequence of that workshop I started to use the Google Earth Engine timelapse tool (embedded above) to understand local shoreline dynamics, and also played around with (taking advantage primarily of the skills and efforts of my fiend Matt Lucas) using Google Earth Engine specifically to assess multi-decadal shoreline change. Here, for example, is an NVDI (which attempts to use pixel characteristics to identify water and land) applied to the Elwha River delta in 1984:
and another view from 2015:
in which you can see the pattern of change associated with the Elwha dam removal near the river mouth. So clearly this tool can pick up, at least in some way, these large changes in shoreline position.
When Matt showed me these results I thought to myself, "there is some power here to do some large-scale shoreline change analyses". Well, sure enough, a group of researchers from Holland has done the work, and developed a fascinating web based data visualization tool to go with it.
Its not perfect. If you look closely at some portions of our local shoreline, for example (like this screen grab showing Cape Flattery near Neah Bay below), you see a bunch of red bars, suggesting long-term erosion. But this is a bedrock shoreline, and is unlikely to have eroded at relatively high rates over this time frame.
But it does pick up some of the known patterns of change on the sandy shorelines of SW Washington. Here, for example, is a screen grab showing Grays Harbor and parts of Willapa Bay:
here we can see the rapid erosion rates plaguing areas around the mouth of Willapa Bay, as well as the area around Westport, Washington. So that is encouraging. And of course there is nothing else out there that provides a global perspective like this tool does. This represents a big advance in terms of understanding patterns of shoreline change on a global scale.
No comments:
Post a Comment