A Multimodel Ensemble Approach for Spatiotemporal Variability and Trend Analysis of Extreme Precipitation Indices Using CMIP6 Climate Model Projections in Mono River Basin
DOI:
https://doi.org/10.70917/jcc-2026-006Keywords:
CMIP6, extreme precipitation indices, Climate change, Spatiotemporal variability, Trend analysisAbstract
Rainfall extremes in the Mono River Basin (MRB) exhibit marked spatial and temporal heterogeneity, and their accurate characterization is essential for sustainable water governance and natural hazard mitigation. This study evaluated the capacity of a multimodel ensemble built from CMIP6 General Circulation Models (GCMs) to capture and project the spatiotemporal evolution of extreme precipitation indices across the MRB. The methodological framework integrates three successive components: a performance-based selection of GCMs using a multicriteria ranking score, a systematic bias adjustment using the Quantile Delta Mapping (QDM) technique, and the construction of a weighted multi-model ensemble (MME) using inverse RMSE weighting. The ranking procedure, applied to 10 CMIP6 GCMs against CHIRPS satellite-derived as reference data, led to the selection of five top-performing models. Trend analyses of four extreme precipitation indices (Rx1day, SDII, PRCPTOT, and R20) were subsequently conducted over the projection period of 2030-2060 under SSP2-4.5 and SSP5-8.5 scenarios, using both the Modified Mann-Kendall (MMK) test and Innovative Trend Analysis (ITA). The results indicate that the ensemble configuration systematically outperformed the individual GCMs in reproducing the observed hydroclimatic variability, as evidenced by the superior RMSE, R², NSE, and KGE scores. For the spatial aspect, the results reveal clear spatial variability in extreme precipitation over the MRB, with stronger positive trends mainly in the central and southern regions. Extreme precipitation indices indicate the intensification of extreme rainfall, particularly in downstream areas. The magnitude of these changes amplified considerably under SSP5-8.5, indicating the sensitivity of MRB hydrology to emission pathway assumptions. The obtained results enable us to provide valuable insights for improving the understanding of the extreme precipitation indices distribution for informing flood risk assessment, agricultural planning, and integrated water resource management in the basin under future climate conditions.
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Copyright (c) 2026 Joselyne Lisbeth Godonou, Jerome Enagnon Ahouandjinou, Edia Flavien Dovonou (Author)
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