Research on hybrid mechanism modeling of algal bloom formation in urban lakes and reservoirs

•A hybrid mechanism modeling method was proposed, which synthesized the advantages of ecological dynamic model and data-driven model.•A function model library of key impact factors in algal bloom formation was first established, and then Tabu Search and Genetic Algorithm were applied for model structure optimization and parameters calibration.•Other contrast models including data-driven model and ecological mechanism model of algal bloom formation were added.•To verify effectiveness of the modeling method, laboratory data and practical data were applied for the hybrid mechanism model.

Algal bloom in urban lakes and reservoirs breaks out more frequently in recent years, making it a serious environmental problem in the world. Ecological dynamic model and data-driven model are two most representative methods to describe algal bloom formation mechanism; however, they both have certain drawbacks. In this paper, on the basis of deep analysis on formation mechanism of algal bloom, a hybrid mechanism modeling method was proposed, which synthesized the advantages of both models mentioned above. In order to obtain an appropriate model, a function model library (FML) of key impact factors (IFs) in algal bloom formation was first established, and then Tabu Search (TS) and Genetic Algorithm (GA) were applied for model structure optimization and parameters calibration, respectively. Simulation results show that the proposed method can effectively characterize the formation mechanism of algal bloom in different urban lakes and reservoirs, and it is also with higher modeling speed and wider extendibility.