Bah et al. (2026) A new comprehensive monitoring framework for global drought assessment

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-03-29
• Authors: Alhassane Bah, Asim Biswas, Hao Feng, Qiang Yu, Q Wang, Yi Li
• DOI: 10.1016/j.jhydrol.2026.135413

Research Groups

• College of Water Resources and Architecture Engineering, Key Lab of Agricultural Water and Soil Engineering of Education Ministry, Northwest A&F University, Yangling, China
• Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining, China
• Northwest A&F University Shenzhen Research Institute, Shenzhen, China
• School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada
• College of Soil and Water Conservation Science and Engineering, Northwest A&F University, Yangling, China
• College of Environment & Safety Engineering, Fuzhou University, Fuzhou, China

Short Summary

This study introduces a novel Comprehensive Drought Index (CoDI) for global drought assessment, integrating meteorological, agricultural, and hydrological drought dimensions using Principal Component Analysis. CoDI was validated across 60 major basins and 22 historical drought events, demonstrating superior capability in capturing diverse drought conditions and identifying global drought hotspots from 1982 to 2018.

Objective

• To develop and validate a novel Comprehensive Drought Index (CoDI) for global drought assessment by integrating meteorological, agricultural, and hydrological drought dimensions, aiming to provide consistent drought characterization across diverse hydroclimatic regimes at multiple timescales.

Study Configuration

• Spatial Scale: Global, validated across sixty (60) major basins spanning multiple continents.
• Temporal Scale: Drought characterization from 1982 to 2018. Terrestrial Water Storage Anomaly (TWSa) response to CoDI exhibits lag times of 0 to 2 months. Identified drought durations ranged from 40 to 131 months.

Methodology and Data

• Models used: Comprehensive Drought Index (CoDI) developed using Principal Component Analysis (PCA). CoDI optimally combines the Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI), and Standardized Runoff Index (SRI) with continent-specific probability distributions.
• Data sources: Input indices (SPI, SSI, SRI) derived from precipitation, soil moisture, and runoff data. Validation against Terrestrial Water Storage Anomaly (TWSa) and 22 historical drought events. Comparison with scPDSI and SPEI.

Main Results

• The CoDI demonstrates substantial agreement with other indices (scPDSI, SPEI) in capturing historical and seasonal drought events.
• The Terrestrial Water Storage Anomaly (TWSa) response to CoDI exhibits short lag times (0 to 2 months) in the majority of the 60 selected basins, in contrast to the scPDSI, which displays longer lag times.
• CoDI successfully captured seasonal drought events in Australia’s southwestern region (January to March 2011), while SPEI_cru captured only the January event, highlighting CoDI's capability to capture different types of drought conditions.
• Global drought characterization from 1982 to 2018 identified key drought hotspots in the Sahel, Central Asia, and parts of South America.
• Drought durations in these identified hotspots ranged from 40 to 131 months.
• CoDI provides consistent drought characterization across diverse hydroclimatic regimes at multiple timescales.

Contributions

• Development of a novel Comprehensive Drought Index (CoDI) that integrates meteorological, agricultural, and hydrological drought dimensions using Principal Component Analysis.
• Improved capability to capture different types of drought conditions and seasonal events compared to single-variable indices.
• Provides consistent drought characterization across diverse hydroclimatic regimes and multiple timescales, enhancing drought monitoring.
• Enables improved early warning, water resource management, and climate adaptation strategies.
• Represents a significant advancement in transforming drought monitoring from single-variable approaches to integrated, multidimensional assessment.

Funding

Not specified in the provided text.

Citation

@article{Bah2026new,
  author = {Bah, Alhassane and Biswas, Asim and Feng, Hao and Yu, Qiang and Wang, Q and Li, Yi},
  title = {A new comprehensive monitoring framework for global drought assessment},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135413},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135413}
}