Retrieval and Evaluation of Chlorophyll-a Concentration in Reservoirs with Main Water Supply Function in Beijing, China, Based on Landsat Satellite Images

Remote sensing retrieval is an important technology for studying water eutrophication. In this study, Guanting Reservoir with the main water supply function of Beijing was selected as the research object. Based on the measured data in 2016, 2017, and 2019, and Landsat-8 remote sensing images, the concentration and distribution of chlorophyll-a in the Guanting Reservoir were inversed. We analyzed the changes in chlorophyll-a concentration of the reservoir in Beijing and the reasons and effects. Although the concentration of chlorophyll-a in the Guanting Reservoir decreased gradually, it may still increase. The amount and stability of water storage, chlorophyll-a concentration of the supply water, and nitrogen and phosphorus concentration change are important factors affecting the chlorophyll-a concentration of the reservoir. We also found a strong correlation between the pixel values of adjacent reservoirs in the same image, so the chlorophyll-a estimation model can be applied to each other

Remote sensing inversion of water quality parameters in the Yellow River Delta

In recent years, with the rapid socio-economic development of the Yellow River Delta (YRD), the pressure on the supply of water resources has continued to rise. The development of oil-based industries has also led to a series of ecological and environmental problems, such as wetland degradation and water quality deterioration. As an increasing number of rivers are getting polluted, resulting in the deterioration of their water quality, monitoring, managing, and protecting water resources in the YRD is particularly important. In this study, water quality monitoring data and simultaneous Sentinel-2 image data from April 30, 2020, to October 26, 2021, were used to construct an experimental sample in the YRD. Water quality parameters (WQPs) concentrations were correlated with Sentinel-2 image element spectral reflectance and sensitive bands were selected. An empirical method based on the characteristic bands was used to invert a total of six water quality indicators, namely dissolved oxygen (DO), permanganate index (CODMn), ammonia nitrogen (NH3-H), total phosphorus (TP), total nitrogen (TN) and turbidity. The results show: (1) A total of five water quality inversion models for DO, TN, CODMn, TP and TN were effective in the areas of the Guangli River, the Tiaohe and the Branch River. The inversion accuracies of the five inversion models (R2of 0.6099, 0.9271, 0.9581, 0.8784 and 0.7387; RMSE of 1.2723, 0.3413, 0.9923, 0.0118 and 1.8476; RPD of 1.53, 2.08, 3.56, 2.76 and 1.53) indicated the feasibility of the water quality inversion method based on Sentinel-2 data using statistical theory for monitoring water quality concentration in the YRD. (2) The spatial distribution of water quality in the YRD was generally characterized by high water quality in the upper reaches and low water quality in the middle and lower reaches (except for some seasonal variations). Among them, the water quality of the upper reaches of the Guangli River was poor, with opposite trends in DO and TN concentrations. In the Tiaohe, CODMn and TP concentrations were not strongly correlated. However, CODMn and TP concentrations were high in the middle reaches where water quality was the worst. The TN concentrations in the Branch River decreased between 2020 and 2021, but the water quality is still in Category V. Therefore, continued attention and appropriate water quality management measures in the YRD are required. Further, by measuring water quality indicators at monitoring stations, regression-fitting equations for WQPs were established to obtain complementary multi-platform observations. Thus, the water quality conditions in the YRD region can be evaluated more accurately and quickly. The research results not only provide an important reference basis for the identification and monitoring of pollution sources, prevention and treatment of water environment pollution in the YRD, but also provide water security for socio-economic and ecological environment security

Active layer thickness (2002-2020)

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