High-Resolution Drought Data for India - Villages with no Irrigation

DOI

This geo-database consists of a 0.05 degree (5 x 5 km) SPEI (Standardised Precipitation-Evapotranspiration Index) that was calculated using CHIRPS precipitation data and resampled GLEAM data. We use the Priestley-Taylor equation to estimate potential evapotranspiration (PET), taking additional variables into account relevant for the Indian context.We merge the SPEI database with all Indian villages that show very little irrigation coverage over agricultural lands, and villages where we see a strong outflow out of agrarian work among males. The Indian censuses of 2001 and 2011 are used to include this information.The data is provided as a Shapefile, and can be opened with open-source geospatial software such as QGIS.The dataset also includes the original tabular data in Comma Separated Values (.csv) format.

Date Submitted: 2023-07-07

Identifier
DOI https://doi.org/10.17026/dans-zwz-mb93
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-zwz-mb93
Provenance
Creator R.J. van Duijne ORCID logo
Publisher DANS Data Station Phys-Tech Sciences
Contributor R.J. van Duijne
Publication Year 2023
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact R.J. van Duijne (University of Twente)
Representation
Resource Type Dataset
Format audio/midi; application/vnd.mif; application/zip; text/csv; text/html
Size 4005; 7673412; 18053281; 16682227; 14752; 5172181; 666
Version 2.0
Discipline Agricultural Sciences; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Earth and Environmental Science; Environmental Research; Geosciences; Life Sciences; Natural Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences