@article {DAI2016409,
	title = {Identification of optimal water transfer schemes for restoration of a eutrophic lake: An integrated simulation-optimization method},
	journal = {Ecological Engineering},
	volume = {95},
	number = {Supplement C},
	year = {2016},
	pages = {409 - 421},
	abstract = {Abstract This research developed an integrated simulation-optimization method (ISOM). This model incorporated eutrophication modeling, water resource allocation and trophic status assessment within a general modeling framework. In ISOM, the simulation effort [i.e. environmental fluid dynamics code (EFDC)] was used to forecast the concentration of water quality variables to evaluate the lake trophic status under various conditions, while the optimization studies were used to identify the optimal water transfer strategies from a number of alternatives. To solve the model, a surrogate-based genetic algorithm (GA) was proposed in which the support vector regression (SVR) was used to create a set of easy-to-use and rapid-response surrogates for identifying the functional relationships between water transfer and lake trophic status. By replacing the EFDC and the corresponding trophic state index (TSI) equations with the surrogates, the computation efficiency could be improved. The developed ISOM was applied to the inter-basin water transfer management of the Niulanjiang-Dianchi Water Transfer Project (NDWTP) to support the eutrophication restoration of Lake Dianchi. Optimal water transfer schemes for three different remediation durations were generated from the model. The results demonstrated that NDWTP could exert a positive influence on the ecology and environment of Lake Dianchi, and that the trophic level for the Lake Dianchi could be effectively mitigated through the adoption of optimal water transfer schemes.},
	keywords = {EFDC, Genetic algorithm, Simulation-optimization, Support vector regression, Trophic state index, Water transfer},
	issn = {0925-8574},
	doi = {https://doi.org/10.1016/j.ecoleng.2016.06.080},
	url = {http://www.sciencedirect.com/science/article/pii/S0925857416304050},
	author = {C. Dai and Tan, Q. and Lu, W. T. and Y. Liu and Guo, H. C.}
}
