Application of a three-dimensional eutrophication model for the Beijing Guanting Reservoir, China

生物操纵 环境科学 富营养化 营养物 浮游植物 水文学(农业) 水质 水华 水柱 生态学 海洋学 地质学 岩土工程 生物
作者
Guojian He,Hongwei Fang,Sen Bai,Xiaobo Liu,Minghong Chen,Jing Bai
出处
期刊:Ecological Modelling [Elsevier BV]
卷期号:222 (8): 1491-1501 被引量:91
标识
DOI:10.1016/j.ecolmodel.2010.12.006
摘要

The Beijing Guanting Reservoir (BGR) is located northwest of Beijing and has been an important water supply reservoir ever since the construction of a dam near the town of Guanting in 1954. As a result of excessive nutrients and organic carbon loadings from the drainage basin over the last several decades, the BGR suffers from eutrophication as well as other contamination problems and has not been used as a drinking water supply reservoir since 1997. As a management step to restore the reservoir's water quality, a numerical model was developed based on the environmental fluid dynamics code (EFDC) framework. The model simulated three phytoplankton species based on the observed cyanobacteria, green algae, and diatom concentrations in 2004 for the Yongding arm of the reservoir, which is separated from the rest of the reservoir by a sand bar. The model was calibrated with vertical temperature profiles as well as the observed chlorophyll a and nutrients concentrations in the water column. The calibrated model was further applied to investigate management scenarios, which include reduction in external loadings of nutrients with constructed wetlands, biomanipulation, and transferring water from CeTian Reservoir. All three scenarios can reduce the peak chlorophyll a levels in the reservoir. The background nutrients were high, and reducing the external nutrients was effective only after a reduction in background nutrients after phytoplankton growth. The biomanipulation and water transfer scenarios could also delay the occurrence of the peak chlorophyll a. Because the model was developed based on one year of data, the model can only reveal the short-term effects of applying the management scenarios. Future studies will consider the long-term processes, such as diagenesis, when data are available to predict the long-term effects of the scenarios.

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