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G-RUN (GRUN): Global Runoff Reconstruction
GRUN (Global Runoff Reconstruction; often referred to as G-RUN) is an observation-based global gridded reconstruction of monthly runoff derived using machine learning trained on in-situ streamflow observations. The dataset provides global runoff rates on a 0.5° grid over the period 1902–2014 and is intended for analyses of freshwater dynamics, hydroclimate variability, drought propagation, and evaluation of hydrological model simulations.
Monthly gridded runoff rates reconstructed using machine learning trained on in-situ streamflow observations.
Global gridded land runoff reconstruction
Machine learning reconstruction trained on in-situ streamflow observations
Prediction based on antecedent precipitation and temperature from atmospheric reanalysis inputs
Dataset landing page and downloads hosted on Figshare.
Persistent identifier (Figshare DOI landing page)
Persistent DOI for the GRUN dataset on Figshare.
GRUN: an observation-based global gridded runoff dataset from 1902 to 2014