Intensive agricultural activities in the Hetao irrigation district have severely degraded local aquatic ecosystems and water quality, and Ulansuhai Lake is now the most rapidly degrading eutrophic lake in China. A better understanding of the hydro-agronomic and pollutant transport processes in the area is thus urgently needed. This study simulated monthly streamflow, total nitrogen (TN) and total phosphorus (TP) for the Hetao irrigation district using the Soil and Water Assessment Tool (SWAT) to evaluate the nutrient load, source areas, and hydrological pathways. The Nash-Sutcliffe efficiency (NSE) values obtained for the streamflow simulations were 0.75 and 0.78 for the calibration and evaluation periods, respectively. The SWAT model captured the temporal variation in streamflow (R² > 0.8) for two periods; the NSE values for the TN and TP loads were 0.63 and 0.64 for the calibration period and 0.48 and 0.42 for the evaluation period, respectively. The predicted monthly TN load was correlated with irrigation (r = 0.61) and the monthly TP load with precipitation (r = 0.89), indicating that nitrogen transport is primarily associated with soil leaching and groundwater flow, and phosphorus is primarily transported by sediments caused by rainfall erosion. A case study of split nitrogen fertilizer applications demonstrated reduced annual TN load by as much as 13% in one year. Fertilization timing also affects the load in different pathways especially in lateral subsurface flow and shallow groundwater. Better agricultural management could thus reduce nitrogen losses, and buffer strips could minimize phosphorus transport.

This study examined the discharge and recharge relationships between lake and groundwater in Lake Hulun using a novel tracer method that tracks hydrogen and oxygen isotopes and chloride ions. The hydrogen and oxygen isotopes in precipitation falling in the Lake Hulun Basin were compared with those in water samples from the lake and from the local river, well and spring water during both freezing and non-freezing periods in 2017. The results showed that the local meteoric water line equation in the Lake Hulun area is δD = 6.68 δ¹⁸O − 5.89‰ (R² = 0.96) and the main source of water supply in the study area is precipitation. Long-term groundwater monitoring data revealed that the groundwater is effectively recharged by precipitation through the aeration zone. Exchanges between the various compounds during the strong evaporative fractionation process in groundwater are responsible for the gradual depletion of δ¹⁸O. The lake is recharged by groundwater during the non-freezing period, as shown in the map constructed to show the recharge and discharge relationships between the lake and groundwater. The steadily rising lake water levels in the summer mean that the water level before the freeze is high and consequently the water in the lake drains into the surrounding groundwater via faults along both sides of the lake during the frozen period. The groundwater is discharged into the lake in the west and into the Urson River in the east due to the Cuogang uplift.

Algal blooms pose serious threats to water environments and the balance of aquatic ecosystems. Moreover, environmental factors may be the primary driver of bloom outbreaks. Studying the characteristics and driving factors of the evolution of cyanobacterial blooms can provide a scientific basis for the restoration of lake water environments and aquatic ecosystems. Based on the Landsat extended time series and practical ecological investigation, this study determined the bloom area and dominant species of cyanobacterial blooms in Hulun Lake, and analyzed their evolution characteristics and primary influencing factors. The results show that the area of bloom outbreak tended to decrease from 2018 to 2020, with the peak area remaining below 150 km²; in contrast, the bloom area showed an increasing trend in 2021–2022, with a maximum of 1970.55 km² in June 2022. Pearson correlation analysis of bloom area and driving factors showed that the wind speed was the main influencing factor of bloom outbreaks. In 2022, there were five dominant species of cyanobacteria in summer and three in autumn. Redundancy analysis of the dominant species of cyanobacteria and water quality indicators showed that COD, DO, TP, WT, pH, and TN were the main influencing factors of the dominant species of cyanobacteria in summer, and COD, DO, TP, and WT were the main influencing factors in autumn. In general, cyanobacteria in Hulun Lake are sensitive to changes in wind speed and nutrient concentration. An important approach towards effectively reducing the intensity of cyanobacterial blooms in Hulun Lake and coping with the ecological risks associated with the changing environment would be to reduce external loads and regulate the ecosystem structure of the lake. In the future, while studying the law of cyanobacterial bloom outbreaks, attention should be paid to the impact of the cyanobacterial physiological status on bloom outbreaks.

Overlying water and sediment samples were collected from 11 locations in Ulansuhai Lake in June of 2012 to determine the concentration of dissolved inorganic phosphorus (DIP) in the interstitial water, overlying water and sediment and to estimate the diffusion flux of DIP at the sediment–water interface. The DIP levels in overlying water were 0.004–0.185 mg/L (average = 0.062 mg/L), while they were 0.05–0.25 mg/L (average = 0.124 mg/L) in the interstitial water in the 0–2 cm surface sediment. Moreover, the annual mean exchange flux of DIP in the sediment was between −0.092 mg/m2·d and 0.053 mg/m2·d, and this occurred via internal source action in most areas. After area weighting, it is estimated that the exchange capacity of DIP at the sediment–water interface of the Ulansuhai Lake is 1.30 t/a. These findings indicate internal loading of phosphorus in sediment of the Ulansuhai Lake; thus, the diffusion of DIP in the interstitial water has effects on the lake, with a degree of influence of 2.7% to 81.5%.

Energy is a fundamental driver that causes material movement. It is important to discover changes in energy by studying the internal mechanism of pollutant migration between system components during the freezing process. To explore the migration mechanism of heavy metal ions (HMIs) from ice to water in a lake, we carried out a laboratory freezing experiment and simulated the distribution and migration of HMIs (Fe, Cu, Mn, Zn, Pb, Cd, and Hg) under different conditions. Then, we analyzed the use of energy by first-principle calculations. The results showed that HMIs are more stable in an aqueous environment than in an ice environment. For the same HMI, the binding energy in water is smaller than that in ice. Hence, the HMIs migrated from ice to water as the lake was freezing. The ability of different kinds of heavy metals to migrate from ice to water is related to their binding energy in ice. The concentrations of HMIs in ice are positively correlated with their binding energies. This study investigated the migration characteristics and mechanisms of HMIs in the process of lake freezing.

Climate change and eutrophication have significant impacts on aquatic ecosystems, with phytoplankton playing a critical role as primary producers. This study investigates the relationships between phytoplankton communities and environmental and meteorological factors in Wuliangsuhai Lake, a representative ecosystem in an arid and cold region of China. Using data from 25 sampling sites (April–September 2023), a generalized additive model (GAM) was employed to analyze water quality and laboratory measurements. The results showed a bimodal distribution of phytoplankton density, with peaks in July (5.33 × 10⁶ cells/L) and August (14.90 × 10⁶ cells/L). Green algae dominated in spring, while cyanobacteria became dominant in summer. GAM analysis revealed that temperature (TEMP) was the primary driver, explaining 20.7% of the deviance. When TEMP was examined together with other factors, the explanatory ability of the model was significantly enhanced, and finally, the model explained 57.10% of the deviance. GAM analysis also revealed that different algae species responded differently to environmental factors, with the cyanophyta-dominant species Pseudoalgae being more sensitive to TEMP and pH, whereas the chlorophyta-dominant species Chlorella was more affected by wind speed and salinity. Cyanobacteria dominance, exacerbated by warming, increases the risks of harmful algae blooms and ecosystem instability, highlighting the need for mitigation strategies in vulnerable freshwater ecosystems.