In recent decades, there has been unprecedented development of hydropower in China, especially in the Yangtze River Basin, which has changed the hydrological and hydraulic conditions of natural rivers and has an impact on water quality. However, the spatial-–temporal extent, factors, and the reasons behind the influence of cascade hydropower development are not clear. The six hydropower stations on the main course of the middle reach of the Jinsha River in Yunnan and Sichuan Provinces have been in joint operation for seven years, and the impact of cascade hydropower development on water quality has begun to appear. In this paper, in order to accurately determine the causal relationship between cascade hydropower development and water quality changes on the middle reaches of the Jinsha River and their trends using regression discontinuity analysis, we collected monitoring data on water quality from 2004 to 2019. The results show that cascade hydropower development on the middle reach of the Jinsha River led to a decrease in TP concentration in that section of the river and an increase in the concentration of COD_Mn and NH₃-N. Furthermore, increase in sedimentation following the impoundment of cascade hydropower development is the main reason for the decrease in TP concentration, and the regional economic and social development driven by cascade hydropower development are external sources of the increase in the concentration of COD_Mn and NH₃-N. In addition, influenced by rainfall, the concentrations of COD_Mn and TP are higher in the rainy season and lower in the dry season, which is directly related to the input of non-point-source pollutants in the basin during the former. This study established a model to accurately judge the causal relationship between cascade hydropower development and water quality changes in the basin, which was then used to assess the impact of cascade hydropower development on water quality. Our results provide a basis for the formulation and implementation of a water quality protection plan for the middle reach of the Jinsha River and can also provide a basis for the development of cascade hydropower in other river basins.

Microplastics (MPs) in freshwater environments, such as lakes, have become a significant issue in recent years. However, studies on the lakes of the Yunnan Plateau have been limited. To understand the pollution status and sources of MPs in Lake Chenghai (LCH), 36 sampling sites were selected for the surface water and sediment samples. Morphological identification, compositional analysis, abundance measurement, and spatial distribution mapping of the MPs were carried out. We also performed correlation analyses with hydrological parameters and physicochemical indexes of water and sediments. We aimed to uncover the spatial distribution patterns of the MPs in LCH, along with potential sources. Our findings revealed that all samples contained MPs and all of them were fibers. The abundance of MPs ranged from 90 to 770 n/m³ (329.44 rms) in the water and from 10 to 115 n/kg (43.19 rms) in the sediments, with particle sizes of 1-3 mm and less than 1 mm, respectively. Transparent MPs were prevalent, comprising 68% of the MPs found in the water and 63% in the sediments. The primary components of the MPs were polypropylene (PP), polyethylene terephthalate (PET), and man-made fibers (rayon). The spatial distribution showed an increasing concentration of MPs from south to north in the surface water, whereas the opposite trend was found in the sediments. Human activities, prevailing winds, and the river flowing into the lake influenced the spatial distribution pattern of the MPs. The abundance and assemblage characteristics of the MPs were directly correlated with the factors of nitrogen, phosphorus, and particle size in the water and sediments, but the correlation was not significant. The main source of MPs was the production and livelihoods of the neighboring residents, especially the use of fishing gears and nets. Since LCH shows significant pollution from MPs, there is an urgent need to control and manage the watershed in order to reduce the input of MPs in the future.

The water quality of Lake Erhai has deteriorated in recent decades due to socioeconomic development in the lake basin. After the massive implementation of water environmental protection measures in Lake Erhai in 2016, the trend of water quality deterioration has been curbed and the intensity and frequency of algal blooms has decreased. However, water quality monitoring data show that pollutant concentrations in Lake Erhai still exceed acceptable values, and there is a risk of water quality standard limits being further exceeded in the future. Therefore, it is urgent to systematically study the variability characteristics of water quality in Lake Erhai to provide practical methods to predict the future evolution of water quality. Based on water quality monitoring data from 2009 to 2019, the current water quality characteristics of Lake Erhai were analyzed, and a two-dimensional hydrodynamic and water quality mathematical model was built to predict the water quality in 2025. The results showed that the total phosphorus (TP) concentration declined after 2016, mainly due to the significant reduction of TP entering the lake due to pollution interception. However, the concentrations of the potassium permanganate index (COD_Mn) and total nitrogen (TN) increased after 2016, demonstrating that the pollution control measures have had little effect on the improvement of COD_Mn and TN. The spatial and temporal distribution of pollutants showed that the water quality in winter and spring was better than in summer and autumn, and the water quality in the southern lake was better than in the northern lake. This analysis indicates that non-point source pollution remains the main source of pollution in Lake Erhai, and that rainfall is the main driving force of pollutants exceeding the water quality standard. According to the water quality predictions, without additional pollution control measures, pollutant concentrations in Lake Erhai will exceed the Class II water quality standard by 2025. This study analyzes the water quality characteristics, predicts the direction of future water quality changes, and provides a theoretical basis for the future water quality protection of Lake Erhai.

Antibiotics in the aquatic environment are of great concern as novel contaminants. In this study, we investigated the occurrence, distribution, potential sources, and risk assessment of antibiotics in an interconnected river–wetland–lake system. Thirty-three target antibiotics, including sulfonamides (SAs), macrolides (MLs), fluoroquinolones (FQs), tetracyclines (TCs), and chloramphenicol (CLs) belong to five common groups of antibiotics, were tested from water samples collected in the Panlong River, Xinghai Wetland, and Lake Dian (or Dianchi). Mass spectrophotometry was used to detect the target antibiotics, and the water quality parameters were measured in situ. We found four antibiotics, lincomycin (LIN), trimethoprim (TMP), sulfamethoxazole (SMX), and ofloxacin (OFL), with relatively low concentrations at the ng/L level, and detection rates among sample sites ranged from 42.3% to 76.9%, with maximum concentrations of 0.71 ng/L~5.53 ng/L. TMP was not detected in the Panlong River but appeared in the wetlands and Lake Dian. Midstream urban areas of the Panlong River showed the highest pollution among sites. Antibiotic concentrations were positively correlated with total nitrogen (TN) (p < 0.05) and showed some negative correlation with pH, salinity, and DO. According to the risk assessment, antibiotics in water do not pose a threat to human health and aquatic ecosystems, but a potentially harmful combined effect cannot be excluded. Our research offers a geographical summary of the distribution of antibiotics in urban river, wetland, and lake ecosystems in the plateau (PWL), which is important for predicting the distribution characteristics of antibiotics in the plateau water environment and establishing a standardized antibiotic monitoring and management system for the government.

The Three Gorges Reservoir on the Yangtze River is the largest water control project in the world. While exerting great benefits (i.e., flood control, hydropower generation, inland river navigation and scenic tourism), the eutrophication of the tributary bay of the Three Gorges Reservoir has become one of the main environmental problems. This paper is to study the causes of water environment evolution in the tributary bay and investigate the driving force of eutrophication succession after the Three Gorges Reservoir enters the regular operation. By considering the Meixi River on the left bank of the mainstream of the Three Gorges Reservoir area (a typical tributary), this paper developed a three-dimensional hydrodynamic, water quality and water eutrophication mathematical model for the Meixi tributary bay, calibrated with measured data about hydrological regime (water level, flow), hydrodynamic factors (velocity) and water quality (water temperature, Chl-a, TP, TN, etc.). The annual variation of Chl-a concentration in the tributary bay was simulated, and the response relationship between the variation of Chl-a concentration and water conditions of the mainstream and tributary bay (e.g., reservoir water level, reservoir bay velocity, exogenous nutrient input, water temperature stratification and other factors) was analyzed. Results show that the water storage operation of the Three Gorges Reservoir contributes to the low flow velocity maintenance (≤0.05 m/s) in the tributary bay, the backward flow of the mainstream and the sufficient nutrients carried by the tributary water; the water temperature stratification is more likely to occur in the slow detention area in the middle-upper part of the bay in spring and summer, which provides a potential driving force for algae blooms. With the continuous decline of pollution load input in the reservoir basin, the algae blooms in tributary bay was the result of the combined action of low water level operation, low flow velocity (≤0.02 m/s), a large number of non-point source loads input with rainfall and runoff (the proportion of wet year is >70%), and obvious water temperature stratification in shallow water area, and the suitable meteorological conditions are the main inducing factors. Therefore, since the ecological regulation cannot be applied to the multitudinous tributary bays, the non-point source pollution control in the tributary bay is the key to controlling factor.

Cascade hydropower alters river hydrological regimes and threatens aquatic ecosystems, calling for robust ecological risk assessment (ERA). Conventional assessments often rigidly apply the full five-layer Driving Force–Pressure–State–Impact–Response framework, leading to indicator redundancy and unbalanced weighting. Single weighting methods also fail to reconcile expert judgment with data variability. To address these issues, we developed a three-layer (target–element–indicator) evaluation system embedding DPSIR logic without its full structure, focusing on hydrological regime, water environmental quality, and aquatic ecology with ten indicators. We used an improved group AHP-CRITIC coupling method for weighting: AHP aggregates expert judgments via geometric mean, and CRITIC integrates data variability and inter-indicator conflict. Multi-attribute utility theory normalized indicators into a unified security index, applied to four cascade stations in the middle Jinsha River using 66-year (1953–2018) hydrological and seven-year (2013–2019) in situ monitoring data. The evaluation obtained a comprehensive index of 0.71 to 0.74, which is generally safe. River connectivity loss was the primary limiting factor. Hydrological alteration was mild overall with a value of 0.139, while extreme flow decline rate variation reached a high level of 0.83. Weekly regulated stations achieved over 97% ecological flow guarantee, which is much higher than daily regulated stations. This streamlined framework improves interpretability for cascade basins and supports sustainable watershed management.