Intra‐Annual Chlorophyll‐a Dynamics Under Hydroclimatic Extremes Derived From a 44‐Year Baseline: Insights From a Temperate River System (Nakdong River Basin, South Korea)

Understanding how drought affects phytoplankton dynamics is critical for developing early warning systems. Using standardized drought indices that capture both hydrometeorological extremes, we investigated how hydrological anomalies modulate intra‐annual chlorophyll‐a (Chla) concentrations, a proxy for phytoplankton biomass, in South Korea's Nakdong River Basin. We analyzed five drought indices (SPI, SPEI, SSI, EDDI, and SPEDI) from 44 years of hydrometeorological records within a hierarchical Bayesian model, incorporating streamflow, nutrient concentrations, and water temperature anomalies to examine spatiotemporal Chla variability. The resulting model demonstrated improved predictive performance ( R 2 = 0.69, RMSE = 6.94) relative to meteorological drought indices, with the hydrological drought index (SSI‐1) accounting for up to 21% of intra‐annual Chla variability. Compared to normal conditions, Chla concentrations were, on average, 12% higher during dry years and 4% lower during wet years. Tributary basins showed greater sensitivity, particularly during spring and summer cyanobacterial bloom periods; notably, severe droughts in 2017 and 2022 led to a 51% increase in summer Chla in these basins relative to normal years. Cross‐correlation analysis revealed both immediate and lagged water‐quality responses to drought, identifying nutrient accumulation and warming as key mechanisms that enhance blooms. Given these strong spring and summer drought‐bloom associations, projected drought intensification under climate scenarios is likely to exacerbate cyanobacterial bloom risks, posing significant challenges for integrated water management. This comprehensive study provides critical insights into the mechanisms driving drought‐bloom linkages and highlights the value of drought indices for early warning and adaptive management.