Random Forest Model for Agricultural and Hydrological Drought Analysis in Ethiopia (1982–2100)
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| Formato: | Recurso digital |
| Publicado: |
Zenodo
2025
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| _version_ | 1866902276980867072 |
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| author | Abdullahi, Mohammed |
| author_facet | Abdullahi, Mohammed |
| contents | <p>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.<br>The Random Forest model used for prediction of agricultural (SSMI/based) and hydrological (SRI-based) drought indices is openly available for reuse and adaptation.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17410178 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Random Forest Model for Agricultural and Hydrological Drought Analysis in Ethiopia (1982–2100) Abdullahi, Mohammed <p>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.<br>The Random Forest model used for prediction of agricultural (SSMI/based) and hydrological (SRI-based) drought indices is openly available for reuse and adaptation.</p> |
| title | Random Forest Model for Agricultural and Hydrological Drought Analysis in Ethiopia (1982–2100) |
| url | https://doi.org/10.5281/zenodo.17410178 |