[Spatial-temporal Distribution of Suspended Solids and Its Sedimentation Flux and Nutrients Effects in Xin'anjiang Reservoir, China]

To analyze the spatial-temporal distribution and sedimentation characteristics of suspended solids in reservoirs, high-frequency monitoring of a sediment trap and buoy, combined with three-dimensional water sampling, was conducted and analyzed in Xin'anjiang Reservoir for a year. The results showed that the turbidity data of the buoy has significant correlation with rainfall, inflow, and suspended solids (SS), particularly for SS (P<0.01, R²=0.86). There is an obvious spatial difference in SS between spring and summer, when the rainfall season occurs (river area > transition area > lake area). However, there is little difference in SS concentration between autumn and winter. There is a spatial trend of river area > transition area > lake area (with rates of 27.82, 4.34, and 0.26 g·(m²·d)^-1, respectively), and a temporal trend of spring and summer > autumn and winter. The sedimentation flux of the whole lake is 2.57×10⁶ t·a^-1 combined with the investigation of the four-season SS at 60 points across the whole lake, and the settlement flux in spring and summer is higher than that in autumn and winter. The contents of particulate nitrogen (PN) in JK, XJS, and DB were 6812, 15886, and 21986 mg·kg^-1, and the particulate phosphorus (PP) contents were 2545, 3269, and 3077 mg·kg^-1, respectively. Statistical analysis shows that there is a good exponential relationship between moderate rainfall and turbidity growth rate in the river area of the reservoir (R²=0.81). Moreover, the continuous heavy rainfall affects turbidity in river area, but has little effect on the transition area. The concentration of SS has a good exponential decay with distance from the river to the dam (R²=0.84), especially in spring and summer. Research shows that the average annual deposition rate in Xin'anjiang Reservoir is 0.07%, lower than other large reservoirs in the country; however, there are certain risks in front of the dam because the nutrient sediments are high. The results suggest that reservoir managers should pay attention to water and soil conservation in the watershed to reduce the impact of rainfall on reservoir water quality. Meanwhile, the potential nutrient internal release risk in the downstream area before the dam should be considered.

[Spatial and Temporal Variability of CO2 Emissions from the Xin'anjiang Reservoir]

Xin'anjiang Reservoir is the largest reservoir in eastern China, with a surface area of 580 km² and a mean depth of 30 m. It is in an oligotrophic or mesotrophic state at present. This study measured carbon dioxide (CO₂) emissions from the upstream river, the reservoir's main body, and the river downstream of the Xin'anjiang Reservoir to investigate the spatial and seasonal variability of CO₂ emissions from the water surface using static floating chambers and gas chromatography. Results showed that the downstream river had, significantly, the highest CO₂ emission flux[(1535.00±1447.46) mg·(m²·h)^-1], followed by the upstream river[(120.39±135.41) mg·(m²·h)^-1]. The reservoir's main body had the lowest flux[(36.65-61.94) mg·(m²·h)^-1]. The high CO₂ emission flux in the downstream river was probably influenced by turbulence during the discharge periods, which would allow the dissolved CO₂ in the hypolimnion before the dam to be released to the atmosphere in the watercourse of the downstream river. However, the CO₂ emission flux decreased with distance to the dam, likely because of the drop in strength of the turbulence. Moreover, there was an obvious alternation between CO₂ source and CO₂ sink in the main body of the reservoir, with CO₂ sources in autumn and winter and CO₂ sinks in spring and summer. The maximum and minimum CO₂ emission values occurred in winter and spring, respectively. Such variability in the CO₂ emissions was probably influenced by the bloom of alga in spring and summer, because dissolved CO₂ in the water was absorbed by the respiration of alga. However, hydrologic conditions were unstable in the upstream river due to a fast water flow, so alga was difficult to bloom there, and a CO₂ source was observed throughout the year, except during April and August. The measurement of the flux from the upstream river, main body, and downstream river required a long period for the investigation of greenhouse gas emissions to avoid underestimating the total CO₂ emission from a hydroelectric reservoir system.

Monitoring spatiotemporal variations in nutrients in a large drinking water reservoir and their relationships with hydrological and meteorological conditions based on Landsat 8 imagery

Nutrient enrichment is a major cause of water eutrophication, and variations in nutrient enrichment are influenced by environmental changes and anthropogenic activities. Accurately estimating nutrient concentrations and understanding their relationships with environmental factors are vital to develop nutrient management strategies to mitigate eutrophication. Landsat 8 Operational Land Imager (OLI) data is used to estimate nutrient concentrations and analyze their responses to hydrological and meteorological conditions. Two well-accepted empirical models are developed and validated to estimate the total nitrogen (TN) and total phosphorus (TP) concentrations (C_TN and C_TP) in the Xin'anjiang Reservoir using Landsat 8 OLI data from 2013 to 2016. Spatially, C_TN decreased from the transition zone to the riverine zone and the lacustrine zone. On the other hand, C_TP decreased from the riverine zone to the transition zone and the lacustrine zone. Temporally, C_TN displayed elevated values during the late fall and winter and had lower values during the summer and early fall, whereas C_TP was higher during the spring and lower during the winter. Among the environmental factors, the rainfall and the inflow rate have strong positive correlations with the nutrient concentrations. TN is more sensitive to meteorological factors (wind speed, temperature, sunshine duration), and the spatial driving forces vary among the different sections of the reservoir. However, TP is more easily influenced by human activities, such as fishery and agricultural activities. Current results would improve our understanding of the drivers of nutrients spatiotemporal variability and the approach in this study can be applicable to other similar reservoir to develop related strategies to mitigate eutrophication.