Research On Optimisation and Regulation of Water Level in The Great Lakes Based on Simulated Annealing-Dynamic Programming Algorithm

Fuzhi Zhan

doi:10.54097/yb36w462

Authors

Fuzhi Zhan

DOI:

https://doi.org/10.54097/yb36w462

Keywords:

Dynamic Water Level Regulation Model, Simulated Annealing Algorithm, Dynamic Programming Model, Water Level Control.

Abstract

Shipping, fishing, power generation... Lakes are crucial to ecosystems and increasingly impact human life. Rising conflicts over lake resource use highlight water management issues. This paper simulates Great Lakes water level changes to maximize benefits for all stakeholders. Two models are established: Model I: Optimal Water Level Estimation Model; Model II: Water Level Dynamic Regulation Model. This paper implemented a simulated annealing strategy to develop an optimal water level estimation model; by incorporating the historical water levels of the Great Lakes basin and the needs of various stakeholders, closely approximated and determined the optimal monthly water levels for each lake; the model's validity was confirmed with a Pearson correlation coefficient of 0.828. Based on the optimal water level estimation model, This paper utilized the concept of dynamic programming to analyze data on precipitation, evaporation, river flow, and total water usage. By incorporating theories of regulatory time delay and supply water volume lag factors, we established a dynamic water level regulation model, thus ensuring that the water levels of the Great Lakes remain within optimal limits.

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