G-RUN (GRUN): Global Runoff Reconstruction
type: Dataset
comment: This dataset metadata was generated with the use of AI and reviewed by an expert. If you see any mistakes please file an issue on GitHub at https://github.com/earthcube/communityCollections/issues.
description: 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.
keywords: GRUN
keywords: G-RUN
keywords: global runoff
keywords: runoff reconstruction
keywords: streamflow
keywords: hydrology
keywords: hydroclimate
keywords: machine learning
keywords: reanalysis
keywords: monthly
keywords: 0.5 degree
keywords: global gridded dataset
keywords: Figshare
creator: Gionata Ghiggi
  type: Person
  affiliation: ETH Zurich
creator: Vincent Humphrey
  type: Person
  affiliation: ETH Zurich
creator: Sonia I. Seneviratne
  type: Person
  affiliation: ETH Zurich
creator: Lukas Gudmundsson
  type: Person
  affiliation: ETH Zurich
provider: Figshare
publisher: Figshare
is accessible for free: true
variable measured: Runoff
  type: PropertyValue
  description: Monthly gridded runoff rates reconstructed using machine learning trained on in-situ streamflow observations.
  temporal coverage: 1902-01-01/2014-12-31
  spatial coverage: Global gridded land runoff reconstruction
    type: Place
    geo: GeoShape
      box: -180,-90 180,90
  temporal resolution: P1M
  spatial resolution: 0.5 degree
measurement technique: Machine learning reconstruction trained on in-situ streamflow observations
measurement technique: Prediction based on antecedent precipitation and temperature from atmospheric reanalysis inputs
encoding format: application/x-netcdf
encoding format: application/zip
encoding format: text/html
license: https://creativecommons.org/licenses/by/4.0/
distribution: Figshare dataset landing page
  type: DataDownload
  description: Dataset landing page and downloads hosted on Figshare.
  encoding format: text/html
distribution: Persistent identifier (Figshare DOI landing page)
  type: DataDownload
  description: Persistent DOI for the GRUN dataset on Figshare.
  encoding format: text/html
citation: GRUN: an observation-based global gridded runoff dataset from 1902 to 2014
  type: ScholarlyArticle
  author: Gionata Ghiggi
  author: Vincent Humphrey
  author: Sonia I. Seneviratne
  author: Lukas Gudmundsson
  is part of: Earth System Science Data
  date published: 2019
about: Hydrology
about: Runoff
about: Streamflow
about: Hydroclimate variability
about: Drought
about: Freshwater resources

PropertyValue
property ID: doi
value: 10.5194/essd-11-1655-2019