Heavy metals (HMs) in aquatic environments are characterized by high toxicity, a propensity for bioaccumulation, and non-degradability, and pose significant risks to biological communities. Previous studies of HMs in lakes have shown that the physical and chemical characteristics of the lake water may control both the migration of HMs in the sediments and the concentration of heavy metals in the lake water. In fact, the change in aquatic environments changes the heavy metal fraction in the sediment, which controls the release of HMs. In this paper, we investigated the effects of the pH, temperature, and salinity levels of overlying water on the chemical fraction of Cu and Zn in Wuliangsuhai Lake surface sediments. The results show that lower water pH and higher water salinity and temperature could increase Cu and Zn release from the sediment. An increase in pH led to changes in the speciation of solid fractions of Zn, namely increases in the residual fraction and decreases in the organic matter and sulfide, whereas acid-extractable and Fe-Mn oxide fractions remained largely the same. Increases in temperature and salinity led to opposite changes in the speciation of solid fractions, namely decreases in the residual fraction and increases in the organic matter and sulfide and Fe-Mn oxide fractions, whereas acid-extractable fractions remained largely the same. The effect of pH, temperature, and salinity on Cu fractions in the solids was much smaller. According to the ratio of the secondary phase to the primary phase (RSP), acidic, high-temperature, and high-salt conditions increase the release risks of Zn. Changes in water temperature have the greatest influence on the risk of Zn and Cu release from sediments, followed by the influence of salinity changes.

To investigate the changes in heavy metal content in the sub glacial water during the freezing and thawing process of seasonally frozen lakes, the Wuliangsuhai Lake in northern China was taken as the research object. The ice thickness, water depth, and heavy metal content at different depths of the lake were measured during the freezing and thawing periods. Based on a large amount of measured lake heavy metal data, MATLAB 2022b software is used to model data fitting and optimization identification, and wavelet analysis and 24 h sliding average method are used for verification analysis to describe the variation process of heavy metal concentration in ice water with depth and time. The results show that during the freezing and thawing periods of lakes, the water level is constantly changing, but the heavy metal content in the water below the ice follows the same distribution with water depth. During the freezing process, the heavy metal content in the water increases with the increase in ice thickness. A new numerical model describing the spatiotemporal distribution of heavy metals under the ice during the freezing period of the lake was obtained through calculation. The overall trend of the simulated contour lines is consistent with the measured values and has a small error. This study provides a reference for predicting the changes in heavy metal content under the ice cover during the freezing period in cold and arid regions. The model can be used to simulate the content values of heavy metals at different depths and times.