Abstract
The water environment of Lake Dianchi in Yunnan province is threatened by eutrophication, which leads to the decrease of dissolved oxygen in water. Meanwhile, as the index reflecting the pollution of organic and inorganic oxidizable substances in water, permanganate index is also affected. China has been developing the automatic monitoring system for a series of water quality factors, such as dissolved oxygen and permanganate index. Additionally, the monitoring and prediction of ammonia-nitrogen, one of the water eutrophication sources, are also important. This study analyzed the water quality factor data in Lake Dianchi from 2015 to 2018 and implemented the prediction based on the Long Short-Term Memory neural network algorithm. It is found that the water quality of Lake Dianchi will be in a relatively ideal state in the future, but it cannot be improved further by itself. The Kunming government should implement more targeted improvement measures according to the characteristics of water quality factors, such as the seasonality of Lake Dianchi. Those measures will improve the ecological service quality of Lake Dianchi effectively, ensure the daily water safety of people in Kunming, and bring more economic values to the city.
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More From: IOP Conference Series: Materials Science and Engineering
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