Water level fluctuation (WLF) in shallow lakes in the middle and lower reaches of the Yangtze River has been a concern of many researchers. This work aims to investigate the effects of climate change and regulation of floodgates and the Three Gorges Dam (TGD) on WLF and lake volume in Huayang Lakes during the past 52 years. The results revealed that precipitation is the dominant factor that leads to seasonal variation of lake levels, whereas regulation of floodgates and TGD are the key drivers of hydrology regime change in the past 20 years. Natural lake regime has higher water level when there is more precipitation and less lake volume. Floodgates and TGD regulations have changed this pattern since 2003, causing less difference in water level in spite of more precipitation and lake recession. Under the combined impacts of floodgates and TGD regulations, Huayang Lakes have experienced a prolonged outflow time since 2003 and the contribution rate caused by the floodgates and TGD regulations has increased by 19.90%. Additionally, the water level of Huayang Lakes decreased by approximately 0.3~0.5 m from September to November, but it showed no alteration from January to March in the past two decades. This indicated that floodgate regulations used for agricultural irrigation and fishery culture dominate the hydrology regime in winter and early spring. This study is beneficial for aquatic ecosystem protection in floodgate-controlled lakes under the circumstance of climate change and vigorous anthropology activities.

Understanding the spatial distribution and pollution characteristics of heavy metals in lake sediment is crucial for studying deposition and migration processes, assessing lake conditions, and determining the extent of remediation dredging. The present work is a case study of heavy metal pollution in Shitang Lake in Anhui province, China. Heavy metal concentrations were determined in sediment at locations across the lake to a depth of 100 cm, and pollution levels were assessed on the basis of the Geoaccumulation Index (Igeo) and Potential Ecological Risk Index (RI). Hg and Cd were the predominant heavy metals in the sediment, and the Igeo and RI indicated high pollution levels in the northern and southern zones of the lake. These findings can be used to guide the prioritization of dredging operations.

Outliers are often present in large datasets of water quality monitoring time series data. A method of combining the sliding window technique with Dixon detection criterion for the automatic detection of outliers in time series data is limited by the empirical determination of sliding window sizes. The scientific determination of the optimal sliding window size is very meaningful research work. This paper presents a new Monte Carlo Search Method (MCSM) based on random sampling to optimize the size of the sliding window, which fully takes advantage of computers and statistics. The MCSM was applied in a case study to automatic monitoring data of water quality factors in order to test its validity and usefulness. The results of comparing the accuracy and efficiency of the MCSM show that the new method in this paper is scientific and effective. The experimental results show that, at different sample sizes, the average accuracy is between 58.70% and 75.75%, and the average computation time increase is between 17.09% and 45.53%. In the era of big data in environmental monitoring, the proposed new methods can meet the required accuracy of outlier detection and improve the efficiency of calculation.