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Random Forest Model for Agricultural and Hydrological Drought Analysis in Ethiopia (1982–2100)

Domaine:

climateagricultureenvironment and energy

Type de record:

modelsoftwaredataset
Créateur:
Abd
Éditeur:
Zenodo
Hôte:avatar

This dataset provides the Python implementation, GEE workflow, and trained Random Forest models used for agricultural and hydrological drought assessment in Ethiopia from 1982–2100. The work integrates ERA5-Land, FLDAS, CHIRPS, CHIRTS, and multi-model CMIP6 datasets (SSP245, SSP585) to analyze past and future drought dynamics.
The Random Forest model used for prediction of agricultural (SSMI/based) and hydrological (SRI-based) drought indices is openly available for reuse and adaptation.

Visit

doi.org

Languages

Ndasa

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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