📖 ABSTRACT/OVERVIEW
Cyanobacterial blooms pose escalating threats to drinking water security in Nigeria's freshwater reservoirs, and the development of scientifically grounded predictive frameworks is essential for early warning systems adaptation. This research develops and validates a mechanistic bloom forecasting framework integrating physical limnological modelling, cyanobacterial ecophysiology, and climate change projections for five major Nigerian reservoirs: Kainji, Shiroro, Jebba, Tiga, and Usman Dam. The three-dimensional hydrodynamic model CE-QUAL-W2 was coupled with a species-resolved phytoplankton growth model and calibrated against a decade of monthly monitoring data. Bloom events from 2014 to 2024 were used for model calibration, and 2020 to 2024 data provided independent validation. Climate change scenarios from CMIP6 regional downscaling for Nigeria were used to force the model under SSP1-2.6 and SSP3-7.0 emissions pathways to 2070. Model performance in reproducing historical bloom events achieved a Nash-Sutcliffe efficiency of 0.74. The model successfully reproduced 8 of 11 major bloom events in the validation period with lead times of 14 to 28 days. Projections under SSP3-7.0 indicate that bloom season duration in Kainji and Tiga Reservoirs will increase by 34 to 68 days by 2060 compared to the 2010 to 2024 baseline. Bloom peak intensity is projected to increase by 1.4 to 2.6-fold under the high-emission scenario. A probabilistic risk index incorporating reservoir thermal stratification, nutrient loading, and wind mixing was validated as a simplified operational forecasting metric. The theoretical contribution of this research is the integration of climate-hydrology-phytoplankton coupling within a reservoir-specific operational forecasting architecture applicable across diverse Nigerian hydrological settings. Keywords: cyanobacterial bloom, predictive modelling, climate change, Nigerian reservoirs, CE-QUAL-W2.
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