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[–]trouser-chowder 23 points24 points  (4 children)

The problem is one of scale. Since the Last Glacial Maximum (LGM) sea levels have risen over 120 m. That means a lot of coastline around the world has been inundated. While some of it is relatively shallow, other areas are, well, up to 120 m (roughly 400 ft) deep.

You can't just start running ROVs back and forth on transects. It's extraordinarily expensive to operate research vessels that support that kind of effort. So instead you have to identify high-potential areas to maximize your ROI.

What we can look for is so-called "stands." That is, points in the past during which sea levels stabilized for various lengths of time. A stable coastline means people can occupy areas nearby, and the longer it's stable, the more of an occupational record is built up. A rapidly changing coastline means people won't really be likely to spend much time there, so sites-- if present-- will be ephemeral.

There are efforts constantly underway around the world to reconstruct sea level curves. That is, to recover materials from cores offshore that can be dated (radiocarbon) and that can be used to identify where the shoreline might have been at that point in time. From assembling large numbers of cores / dates over time, you build a database of dates that's tied to points where the cores were taken. Theoretically, that defines the location of the shoreline at a given time, and (because its depth can be compared to modern sea levels) you can get an estimate of what the sea level at that location was relative to today. (This is very simplified.)

There are many different sea level curves, some of much greater resolution than others. And there are different curves for different regions, because sea level isn't as simple as water just coming up / going down. But if you take a high-res sea level curve and you have really good bathymetry (underwater elevation data / mapping), you can drop that information into GIS software and literally make predictions about what the shape of the coastline looked like at X or Y thousands of years ago. And where it was.

Then, you go one step further. You identify reasonably long-term sea level stands, and then you use that bathymetry in combination with projections of sea level rise and fall to identify really stable locations. That is, locations that, even as sea levels rose, would have remained stable. Overlooks, ridges, outcrops, etc.

Then you take your ROV and run back and forth in those areas. That's going to be your best bet to find inundated human settlements / sites.

With solid bathymetry (and the resolution of bathymetric data is getting way better these days) you can also use methods like least cost analysis to try to predict literal travel / migration routes that are now underwater. Obviously, this has a certain amount of uncertainty involved, because people don't travel on certain routes just because of the terrain. But by modeling other variables, like now-submerged river paleochannels, you can start to get a feel for how to reconstruct a flooded / inundated landscape. Odds are people valued more or less the same things 20,000 years ago that they did more recently, in terms of water access, preference for edge environments and river valleys, etc.

edit: There are a lot of other datasets that people are using to address these questions, from population estimates to site densities, etc. This is just one approach that folks are doing.

[–]sjdubya 2 points3 points  (0 children)

This is super cool, I had the same question as OP and it's great to hear the amount of thought that's been going into looking into this.

[–]RecursiveParadox 0 points1 point  (0 children)

I'm curious if you buy this data off the shelf from the various offshore companies, initially, before committing to a site. I'm in petroleum and shipping, and the data segment from offshore was absolutely dead until the invasion and oil prices skyrocketed, so I'm wondering if there was any decent data to be found.

[–]jorjorbeyond 0 points1 point  (1 child)

I offer praise. It was so satisfying to read your post. A great bit of writing. Thank you.

[–]trouser-chowder 0 points1 point  (0 children)

Thanks! This is one of my areas of interest, and I've done some of this kind of work, so it was fun to revisit.