Morphometry of reservoirs and lakes reveals differences in algae blooms

Algal blooms pose increasing threats to lakes and reservoirs worldwide, with harmful species such as cyanobacteria and dinoflagellates releasing toxin that endanger ecosystem and human health. However, the dominant bloom type varies across systems due to differences in climatic conditions and morphometric characteristics. This study aims to identify the key drivers influencing algal bloom types in freshwater systems. We compiled a global dataset of 160 lakes and reservoirs that have experienced either cyanobacterial or dinoflagellate blooms, incorporating climate variables, morphometric features, and physico-chemical water quality parameters. Using XGBoost and Logistic Regression models, we found that lake morphology, particularly depth and surface area, as well as wind speed are critical determinants of bloom type. Notably, a simple depth-area function (H=7.8×A^0.3)  effectively differentiate between the two bloom categories, underscoring the strong influence of lake morphology on bloom dynamics. In addition, the dimensionless morphometric index C_S=H√(π/A), combined with wind speed, further improves classification performance. Given that lake morphology reflects underlying climatic, hydrodynamic, and biogeochemical conditions, these findings offer practical guidance for assessing bloom risk and developing targeted management strategies.