Integration of the analytic hierarchy process and Monte Carlo feature selection for a spatiotemporal weighting scheme in meteorological drought monitoring
There is a compelling need to integrate different drought indices values because these indices utilize various distributions for computation, resulting in different outcomes when the underlying distributions change. This inconsistency highlights the need for a unified approach to assessing drought conditions rather than relying on multiple indices. In response to this challenge, a new framework has been developed that combines existing drought measures into a single Comprehensive Drought Index (CDI). This innovative approach establishes a robust and inclusive method for comparing drought classifications by applying weights to the index values derived from multiple established indices. Validation results demonstrate a strong correlation with these existing measures, underscoring the effectiveness of this comprehensive method. The CDI offers a more efficient tool for improved drought management and response strategies by providing a more nuanced and cohesive understanding of drought complexities.
Authors
- Mohammed M. A. Almazah (ORCID: https://orcid.org/0000-0001-8427-8760)
- Ibrahim Nafisah (ORCID: https://orcid.org/0000-0002-1207-2197)
- Abdulkareem M. Basheer (ORCID: https://orcid.org/0000-0002-3444-6719)
- Rizwan Niaz (ORCID: https://orcid.org/0000-0001-8959-7680)
- Luca Di Persio (ORCID: https://orcid.org/0000-0002-0317-4351)
- Muhammad Hamza (ORCID: https://orcid.org/0000-0002-2893-568X)
Institutions
- University of Verona (IT)
- Quaid-i-Azam University (PK)
- King Saud University (SA)
- Albaydha University (YE)
- Al Baha University (SA)
- King Khalid University (SA)
Publication Details
- Journal
- Geocarto International
- Published
- 2025-03-28
- DOI
- https://doi.org/10.1080/10106049.2025.2474614
- Citations
- 6
- Primary Topic
- Hydrology and Drought Analysis
- Type
- article
- Field-Weighted Citation Impact
- 6.63
Funders
- King Khalid University