Water Quality Variation Law and Prediction Method of a Small Reservoir in China

被引:0
|
作者
Yu, Yu [1 ]
Bai, Yu [1 ]
Ni, Yingying [2 ]
Luo, Yi [2 ]
Junejo, Shafique [3 ]
机构
[1] Zhejiang Univ Water Resources & Elect Power, Sch Water Conservancy & Environm Engn, Hangzhou 310000, Peoples R China
[2] Ningbo Hydrol Stn, Ningbo 315000, Peoples R China
[3] Univ SIndh, Dept Geog, Jamshoro 76080, Pakistan
关键词
reservoir; machine learning method; phosphorus; nitrogen; hydrological data; PHOSPHORUS CONCENTRATION; PARTICULATE PHOSPHORUS; SHALLOW LAKE; SOIL LOSS; SEDIMENT; MODEL; WIND; TEMPERATURE; NITROGEN; RELEASE;
D O I
10.3390/su142113755
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Compared with the attention of large reservoirs, the water quality of small reservoirs also needs attention. In recent years, the problem of reservoir water quality has become increasingly serious. How to predict reservoir water quality may be an urgent problem to be solved. Taking the Yangmeiling reservoir as an example, this paper collects the hydrological and water quality data of the Yangmeiling reservoir in the last ten years, analyzes the relationship between hydrological and water quality data, and uses a machine learning method to simulate the relationship between water quality and hydrological data. The results show that the water quality of small reservoirs can be simply linked with hydrological data and can be predicted through hydrological data, and has high simulation accuracy. This method can be popularized in the simulation and prediction of the water quality of small reservoirs; it does not provide a theoretical basis for the water quality management of small reservoirs.
引用
收藏
页数:14
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