A document by Jemma Stachelek. Click on the document to view its contents.

The tandem rise in satellite-based observations and computing power has changed the way we (can) see rivers across the Earth’s surface. Global datasets of river and river network characteristics at unprecedented resolutions are becoming common enough that the sheer amount of available information presents problems itself. Fully exploiting this new knowledge requires linking these geospatial datasets to each other within the context of a river network. In order to cope with this wealth of information, we are developing Veins of the Earth (VotE), a flexible system designed to synthesize knowledge about rivers and their networks into an adaptable and readily-usable form. VotE is not itself a dataset, but rather a database of relationships linking existing datasets that allows for rapid comparison and exports of river networks at arbitrary resolutions. VotE’s underlying river network (and drainage basins) is extracted from MERIT-Hydro. We link within VotE a newly-compiled dam dataset, streamflow gages from the GRDC, and published global river network datasets characterizing river widths, slopes, and intermittency. We highlight VotE’s utility with a demonstration of how vector-based river networks can be exported at any requested resolution, a global comparison of river widths from three independent datasets, and an example of computing watershed characteristics by coupling VotE to Google Earth Engine. Future efforts will focus on including real-time datasets such as SWOT river discharges and ReaLSAT reservoir areas.

Streamflow, biogeochemical cycling, and flux transport models rely on digital representations of river networks. At local to regional extents, such representations can be very detailed and account for individual hydrologic features such as dams and river diversions. However, at continental to global extents, these hydrologic features are often far less resolved. This lack of detail can lead to a mismatch between the resolution of hydrologic features relative to the resolution of the network itself. One solution to such mismatches is to impose a “global” standard hydrologic feature resolution. However, this approach may fail to provide critical information that is essential for accurate modeling because it removes hydrologic feature data (such as lakes) that could otherwise be passed to calibration and fitting routines. In this research, we test how variations in river network resolution may introduce such resolution mismatches. Using Viti Levu, Fiji as a case study, we show that even small “coarsening” of network resolution has a significant effect on lake representation and has carry-on effects on overall network transport. Because these effects were less pronounced for networks with larger lakes, this indicates that including lakes even in coarse models may be very informative given the extent to which available chemical and hydrologic data is skewed towards larger lakes.