Data used in the paper: Hydrological drought forecasts using precipitation data depend on catchment properties and human activities

doi: 10.4121/302cd0fd-59da-46e8-ac82-f98fad865751.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/302cd0fd-59da-46e8-ac82-f98fad865751
Datacite citation style:
Samuel Sutanto; Syaehuddin, Wahdan (2024): Data used in the paper: Hydrological drought forecasts using precipitation data depend on catchment properties and human activities. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/302cd0fd-59da-46e8-ac82-f98fad865751.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

Here I provide the SSI-1 derived using the LISFLOOD SFO data from 1991 to 2022. The SPI-x were derived from the ERA5 dataset from 1991-2022. The SGI-1 was derived using the LISFLOOD SFO data from 1990 to 2018. The drought forecasts derived using the Standardized Indices (SSI, SGI, SPI) for European rivers with a lead time of 7-month from 2002 to 2022 can be obtained from the author because the data exceed the limit. Scripts used in the study are provided. Please look at the script readme file.

history
  • 2024-02-23 first online, published, posted
publisher
4TU.ResearchData
format
NetCDF, Python
derived from
funding
  • ERC Starting Grant
organizations
Wageningen university and research, Department of Environmental Sciences, Earth Systems and Global Change

DATA

files (18)