A Novel Precipitation-Concentration Kriging Ensemble Drought Assessment Framework ( PCK - EDAF ) for Spatially Consistent and Reliable Drought Projection Under CMIP6 Climate Scenarios

ABSTRACT Drought is a complicated and recurrent natural hazard that creates substantial challenges to sustainable water management and climate adaptation. To address these challenges, Multi‐Model Ensembles (MMEs) of GCM simulations are extensively used for assessing future drought conditions. However, to attain correct and precise characterization of drought there is a need to enhance the development of MMEs to reduce uncertainties and augment spatial consistency. Since the geospatial performance of individual GCMs varies considerably across different regions, incorporating these spatial characteristics into the ensemble formation process is essential for developing an efficient and regionally robust ensemble framework. The study proposes a new framework of drought assessment under GCMs simulations based MMEs to enhance the reliability of future drought projections called—Precipitation‐Concentration Kriging Ensemble Drought Assessment Framework (PCK‐EDAF). The construction of PCK‐EDAF comprises two sequential phases. The first phase, termed Geostatistical Homogeneity Analysis and Ensemble Weight Optimization (GHA‐EWO), derives optimal weights based on the spatial and temporal consistency of GCM outputs with observed precipitation data. The second phase, called the Kriging‐Weighted Ensemble Standardized Drought Index (KWESDI), applies these optimized weights to future ensemble simulations and standardizes the resulting drought estimates. Application of the PCK‐EDAF is based on the 103 grid points across Pakistan using simulations from 22 GCMs under multiple Shared Socioeconomic Pathways (SSP1–2.6, SSP2–4.5, and SSP5–8.5). Under PCK‐EDAF, the performance of the GHA‐EWO is evaluated as compared to conventional Equal Weighted Ensemble (EWE) and Mutual Information based ensemble in terms of Root Mean Square Error, Mean Average Error and correlation measures. Findings indicate that the GHA‐EWO is always the most effective, with lower values of RMSE and MAE and higher correlation coefficients, which prove that the model is more accurate and more consistent with the observed precipitation patterns. To determine the trend in drought under KWESDI we applied Mann‐Kendall test and the slope estimator of Sen. Results related to trend analysis show a significant increasing tendency in drought, particularly under SSP1–2.6 and SSP5–8.5 scenarios at longer time scales. SSP2–4.5 shows a weaker drought signal with statistically insignificant trends due to moderate emissions forcing. These results also suggest an amplification of drought and wetness cycles, which indicate increased climate variability in the future. Overall, the findings reveal that integrating kriging‐derived spatial weights within PCK‐EDAF significantly enhances ensemble reliability. Moreover, the developed PCK‐EDAF framework is modular and generalizable, allowing its application to other regions and datasets. This integration further enables a more realistic and spatially consistent assessment of future drought conditions under changing climate scenarios.

Rabiya Fatima, Zulfiqar Ali

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• Reviewed by heuristic-v2 on Oct 4, 2026, 07:04 UTC. Paper type: method.
• Categories: Hydrology and Drought Analysis, Precipitation Measurement and Analysis, Climate variability and models, Global and Planetary Change, Environmental Science
• BRIEF, No.8 in the Climate & Energy edition of October 4, 2026.