Alexandru T. Codilean, Henry Munack and their colleagues have just released their Open and Global Database of Cosmogenic Radionuclide and Luminescence measurements in fluvial sediment (OCTOPUS). This is a great open and accessible resource of data!
The cosmogenic radionuclide (CRN) part of the database consists of Be-10 and Al-26 measurements in fluvial sediment samples along with ancillary geospatial vector and raster layers, including sample site, basin outline, digital elevation model, gradient raster, flow direction and flow accumulation rasters, atmospheric pressure raster, and CRN production scaling and topographic shielding factor rasters. The database also includes a comprehensive metadata and all necessary information and input files for the recalculation of denudation rates using CAIRN, an open source program for calculating basin-wide denudation rates from Be-10 and Al-26 data.
The luminescence part of the database consists of thermoluminescence (TL) and optically stimulated luminescence (OSL) measurements in fluvial sediment samples from stratigraphic sections and sediment cores from across the Australian continent and includes ancillary vector and raster geospatial data.
OCTOPUS can be accessed at: https://earth.uow.edu.au
The developers of OCTOPUS also submitted a manuscript describing the database in detail to the open access journal Earth System Science Data (Discussions). The paper is now accessible and open for interactive public discussion until 01 May 2018 at:
You are invited to download the data and take part in the discussion.
In our 2010 paper on TopoToolbox published in Environmental Modelling and Software, we have introduced a matrix algebraic approach to calculate flow accumulation. In a recent paper in Water Resources Research, Alan Richardson and colleagues take this approach a step further by presenting a method that enables implicit, parallizable solving of the flow accumulation equation by a preconditioned iterative solver. Their approach leads to significant speed-ups particularly for processing large datasets on many-core computational systems such as large GPU clusters. In addition, this method is particularly suited in situations when drainage areas need to be calculated very frequently such as in landscape evolution models (LEMs) since upslope areas calculated in a previous time step can be used as initial guess for the next iteration. When drainage patterns stabilize during a simulation, this may speed up such calculations tremendously.