Supplementary file 1_Projected precipitation patterns in the White Volta Basin under shared socioeconomic pathways: a bias corrected approach with statistical validation of anthropogenic climate influence.docx

Introduction

The White Volta Basin faces escalating climate change risks, including threats to water security and agricultural productivity driven by rainfall variability. This study projects precipitation variability under Shared Socioeconomic Pathways (SSPs) and evaluates the anthropogenic contribution to projected precipitation outcomes in the basin.

Methods

Bias correction and statistical hypothesis testing were used to assess projected precipitation. The CMhyd distribution mapping method corrected bias in sixteen Global Climate Models (GCMs) from the CMIP6 dataset against CHIRPS precipitation observations for the baseline period 1981–2014. Ensemble projections were generated for four scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The corrected framework covered 18 stations (15 virtual and 3 in-situ: Tamale, Zuarungu, and Garu). One-way Analysis of Variance (ANOVA) was applied to assess scenario influence across near-term (2020–2039), mid-term (2050–2069), and long-term (2080–2100) windows, and paired t-tests (216 comparisons) tested model-consensus departure from baseline. A Rainfall Anomaly Index (RAI) was also computed to characterize anomaly frequency.

Results

Bias correction validation showed strong performance: Pearson Correlation Coefficient = 0.90, Coefficient of Determination = 0.82, Nash-Sutcliffe Efficiency = 0.82, Root Mean Square Error = 35.16 mm, and Percent Bias = 0.1%. Basin-mean F-statistics from ANOVA increased from 4.1 (near-term) to 11.0 (mid-term) and 26.4 (long-term), indicating strengthening pathway separation over time. Station-level long-term separation was strongest at in-situ stations (Tamale: F = 48.399; Garu: F = 48.451; Zuarungu: F = 36.113). Paired t-tests confirmed highly significant departures from baseline in 87.5%, 76.4%, and 56.9% of comparisons for the near-term, mid-term, and long-term periods, respectively. RAI results indicated increasing dry-anomaly frequency in future periods (detailed figures in the Supplementary Appendix).

Discussion

The temporal strengthening of pathway separation (rising F-statistics) indicates that anthropogenic forcing becomes increasingly dominant in shaping precipitation outcomes toward the end of the century, with the clearest signal at in-situ stations. Spatiotemporal patterns point to a drying tendency that intensifies toward late-century horizons, with stronger deficits under the higher-emission SSP3-7.0 and SSP5-8.5 scenarios. Together, these station-resolved, updated projections provide critical evidence to inform climate adaptation planning in the White Volta Basin.