A new vector-based global river network dataset accounting for variable drainage density.

ABSTRACT: Spatial variability of river network drainage density (D_d) is a key feature of river systems, yet few existing global hydrography datasets have properly accounted for it. Here, we present a new vector-based global hydrography that reasonably estimates the spatial variability of D_d worldwide. It is built by delineating channels from the latest 90-m Multi-Error-Removed Improved Terrain (MERIT) digital elevation model and flow direction/accumulation. A machine learning approach is developed to estimate D_d based on the global watershed-level climatic, topographic, hydrologic, and geologic conditions, where relationships between hydroclimate factors and D_d are trained using the high-quality National Hydrography Dataset Plus (NHDPlusV2) data. By benchm

SUBMITTER: Lin P 

PROVIDER: S-EPMC7838288 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature