The North American Great Lakes, one of the largest freshwater reservoirs in the world, experience frequent water level fluctuations due to climate change and human activities, posing significant challenges to ecology, navigation, agriculture, and residential life. In this study, based on meteorological and hydrological data of the Great Lakes basin, dynamic differential equations are developed to describe the dynamic changes of water levels over time. The optimal water levels of the Great Lakes are obtained as 183.34, 176.51, 169.27, 174.44, and 75.12 with the objective of benefit maximization. The ARIMA model was used to predict the precipitation and evaporation of the basin based on historical data, and the dynamic network flow regulation mechanism was studied, in order to control the lake water level at the optimal water level of each stakeholder through parameter optimization.

Wenjuan Qi, Zirui Tang. Dynamic Regulation of Great Lakes Water Levels Using Multiple Model Algorithms. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 10: 140-146. https://doi.org/10.25236/AJCIS.2024.071019.

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