Distribution and spatial variation of volatile methylsiloxanes in surface water and wastewater from the Yangtze River Basin, China

Volatile methylsiloxanes (VMSs) earned serious concerns due to their detection and toxicities after their release to the environments. They were also detected in rivers around the globe, but their distribution remained to be explored in larger rivers with longer length, higher water volume and wider watershed. In the present study, 8 cyclic VMSs (cVMSs) and 7 linear ones (lVMSs) were investigated in 42 water samples (27 surface water (including 7 drinking source water) and 15 wastewater) from the Yangtze River Basin, China. Results showed that VMSs were detected in all sampling sites. In surface water, the concentrations of total cVMSs ranged from 17.3 to 4.57 × 103 ng/L, while those of lVMSs ranged from 1.72 to 81.6 ng/L. In wastewater, the total concentrations of cVMSs and lVMSs showed ranges of 17.6-1.66 × 103 ng/L and 2.59-252 ng/L, respectively. Apparently, cVMSs showed significantly higher concentrations than lVMSs. The concentrations of cVMSs followed an order of lower > upper > middle reaches, while those of lVMSs did not show clear distribution patterns. Among cVMSs, those with less Si numbers were dominant, while those with more Si numbers were dominant in lVMSs. Notably, the VMSs were also detected in 7 surface waters that served as drinking source waters, which earned them further concerns. In addition, the VMSs in surface water showed positive correlation with those in wastewater, which led to necessity in management on industrial emissions in the future.

Source-specific probabilistic health risk assessment of heavy metals in surface water of the Yangtze River Basin

The detrimental effects of heavy metal accumulation on both ecosystems and public health have raised widespread concern. Source-specific risk assessment is crucial for developing effective strategies to prevent and control heavy metal contamination in surface water. This study aims to investigate the contamination characteristics of heavy metals in the Yangtze River Basin, identifying the pollution sources, assessing the risk levels, and further evaluating the health risks to humans. The results indicated that the average concentrations of heavy metals were ranked as follows: zinc (Zn) > arsenic (As) > copper (Cu) > chromium (Cr) > cadmium (Cd) > nickel (Ni) > lead (Pb), with average concentrations of 38.02 μg/L, 4.34 μg/L, 2.53 μg/L, 2.10 μg/L, 1.17 μg/L, 0.84 μg/L, and 0.32 μg/L, respectively, all below the WHO 2017 standards for safe drinking water. The distribution trend indicates higher concentrations in the upper and lower reaches and lower concentrations in the mid-reaches of the river. By integrating the Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) receptor model and Positive Matrix Factorization (PMF) model, the main sources of heavy metals were identified as industrial activities (APCS-MLR: 41.3 %; PMF: 42.1 %), agricultural activities (APCS-MLR: 30.1 %; PMF: 27.4 %), and unknown mix sources (APCS-MLR: 29.1 %; PMF: 30.4 %). The calculation of the hazard index (HI) for both children and adults was <1, indicating no non-carcinogenic or carcinogenic risks. Based on the source-specific risk assessment, agricultural activities contribute the most to non-carcinogenic risks, while industrial activities pose the greatest contribution to carcinogenic risks. This study offers a reference for monitoring heavy metals and controlling health risks to residents, and provides crucial evidence for the utilization and protection of surface water in the Yangtze River Basin.

Heavy metals in centralized drinking water sources of the Yangtze River: A comprehensive study from a basin-wide perspective

Water quality in the Yangtze River Basin (YRB) has received considerable attention because it supplies water to 400 million people. However, the trends, sources, and risks associated with heavy metals (HMs) in water of centralized drinking water sources (CDWSs) in the YRB region are not well understood due to the lack of high-frequency, large-scale monitoring data. Moreover, research on the factors affecting the transportation of HMs in natural water are limited, all of which significantly reduce the effectiveness of CDWSs management. Therefore, this study utilized data on 11 HMs and water quality from 114 CDWSs, covering 71 prefecture-level cities (PLC) in 15 provinces (cities), to map unprecedented geospatial distribution of HMs in the YRB region and examine their concentrations in relation to water chemistry parameters. The findings revealed that the frequency of detection (FOD) of 11 HMs ranged from 28.59% (Hg) to 99.64% (Ba). The mean concentrations are ranked as follows: Ba (40.775 μg/L) > B (21.866 μg/L) > Zn (5.133 μg/L) > V (2.668 μg/L) > Cu (2.049 μg/L) > As (1.989 μg/L) > Mo (1.505 μg/L) > Ni (1.108 μg/L) > Sb (0.613 μg/L) > Pb (0.553 μg/L) > Hg (0.002 μg/L). Concentrations of Zn, As, Hg, Pb, Mo, Sb, Ni, and Ba exhibited decreasing trends from 2018 to 2022. Human activities, including industrial and agricultural production, have led to higher pollution levels in the midstream and downstream of the river than in its upstream. Additionally, the high concentrations of Ba and B are influenced by natural geological factors. Anion concentrations and nutrient levels, play a significant role in the transport of HMs in water. Probabilistic health risk assessment indicates that As, Ba, and Sb pose a potential carcinogenic risk. Additionally, non-carcinogenic risk to children under extreme conditions should also be considered.

A retrospective analysis of heavy metals and multi elements in the Yangtze River Basin: Distribution characteristics, migration tendencies and ecological risk assessment

The Yangtze River is the third longest river in the world with more than 6300 km, covering 0.4 billion people. However, the aquatic ecosystem of the Yangtze River has been seriously damaged in the past decades due to a rapid development of economic and industrialization along the coast. In this study, we first established a dataset of fifty elements, including nine common heavy metals (HMs) and forty-one other elements, in the Yangtze River Basin through the collection of historical data from 2000 to 2020, and then analyzed their spatiotemporal distribution characteristics. The results indicated that the Three Gorges Reservoir (TGR), a region formed by the construction of the Three Gorges Dam (TGD), may act as a sink for these elements from upstream regions. The concentrations of seven elements in surface water and 13 elements in sediment obviously increased from the upstream region of the TGR to the TGR. In addition, ten elements in the surface water and 5 elements in the sediments clearly decreased, possibly because of the interception effects of the TGD. On a timescale, Cr obviously tended to migrate from the water phase to the sediment; Pb tended to migrate from the sediment to the water phase. In the ecological risk assessment, all common HMs in surface water were supposed to have negligible risks as protecting 90 % of aquatic organisms; Cd (210.2), Hg (58.0) and As (43.1) in sediment posed high and moderate ecological risks using the methodology of the potential ecological risk index. Furthermore, Hunan Province is at considerable risk according to the sum of the potential risk index (314.8) due to Cd pollution (66.8 %). These fundamental data and results will support follow-up control strategies for elements and policies related to aquatic ecosystem protection in the Yangtze River Basin.

An innovative method based on Gaussian cloud distribution and sample information richness for eutrophication assessment of Yangtze's lakes and reservoirs under uncertainty

The precise assessment of a water body's eutrophication status is essential for making informed decisions in water environment management. However, conventional approaches frequently fail to consider the randomness, fuzziness, and inherent hidden information of water quality indicators. These would result in an unreliable assessment. An enhanced method was proposed for the eutrophication assessment under uncertainty in this study. The multi-dimension gaussian cloud distribution was introduced to capture the randomness and fuzziness. The Shannon entropy based on various sample size and trophic levels was proposed to maximize valuable information hidden in the datasets. Twenty-seven significant lakes and reservoirs located in the Yangtze River Basin were selected to demonstrate the proposed method. The sensitivity and consistency were used to evaluate the accuracy of the proposed method. Results indicate that the proposed method has the capability to effectively assess the eutrophication status of lakes and reservoirs under uncertainty and that it has a better sensitivity since it can identify more than 33-50% trophic levels compared to the traditional methods. Further scenario experiments analysis revealed that the sample information richness, i.e., sample size and the number of trophic levels is of great significance to the accuracy/robustness of the method. Moreover, a sample size of 60 can offer the most favorable balance between accuracy/robustness and the monitoring expenses. These findings are crucial to optimizing the eutrophication assessment.

[Pollution Characteristics and Ecological Risk Assessment of Microplastics in the Yangtze River Basin]

The Yangtze River, the largest river in China, has not been comprehensively studied for its basin's microplastic pollution status. Therefore, a comprehensive investigation and assessment system of microplastics was developed at the river basin scale to characterize the spatial distribution and composition of microplastics in the Yangtze River Basin in order to analyze their influencing factors and assess their ecological risks. The results showed that the microplastic abundance in the study area ranged from 21 to 44 080 n·m-3, with an average abundance of 4 483 n·m-3. The spatial distribution of microplastic abundance was higher in the tributaries than in the main streams (except the Ganjiang Basin), with the Chengdu of the Minjiang Basin being the tributary area with the highest abundance of microplastics detected. The size of microplastics in the river basin was concentrated in the 0-1 mm range; the shapes were mainly fiber and fragment; and the colors were mainly colored and transparent. Further, introducing the diversity index of microplastics, it was found that both the Simpson index and the Shannon-Wiener index could quantify the diversity of microplastic characteristic composition in the river basin, but there were certain differences in the changing trends between the two. Regression analysis showed that anthropogenic activities were significantly and positively correlated with microplastic abundance (P<0.05), and among the eight anthropogenic activity factors, civilian vehicle ownership and tourism income were the most strongly correlated with microplastic abundance, indicating that transportation and tourism were the main factors influencing microplastic distribution. From the perspective of the potential ecological risk index of microplastics, microplastics in the Yangtze River Basin posed a certain ecological risk, with 68.97% of the area falling within risk zones III and IV, with the ecological risk of microplastics in Taihu Lake warranting more widespread attention.

Impacts of the Three Gorges Dam on riparian vegetation in the Yangtze River Basin under climate change

As the largest hydroelectric project in the world, the Three Gorges Dam (TGD) is expected to have significant environmental and ecological impacts on riparian vegetation in the Yangtze River Basin (YRB). However, existing studies have mainly focused on small segments of the YRB. In addition, few studies have quantified the responses of riparian vegetation to both climatic factors and dam construction. In this study, we investigated riparian vegetation dynamics over the entire YRB before, during, and after the construction of TGD from 1982 to 2015 using the normalized difference vegetation index (NDVI). Furthermore, the effects of climatic factors and dam construction on riparian vegetation were quantitatively analyzed using path analysis. The results demonstrate that the YRB has experienced a generally greening trend after TGD construction. The impacts of climate change on riparian vegetation have exhibited notable spatial heterogeneity and temperature is the main climatic factor that affects riparian vegetation growth. Moreover, TGD becomes the major contributor to riparian vegetation dynamics in the YRB after TGD construction. TGD has not only directly enhanced riparian vegetation but also indirectly affected riparian vegetation by regulating the microclimate. This study highlights the significance of anthropogenic interference when evaluating the relationships between riparian vegetation and climatic factors, providing useful insights for the effective management and conservation of large-scale riparian ecosystems.

Spatially explicit estimation of freshwater fish stock biomass with limited data: A case study of an endangered endemic fish on the Tibetan Plateau, China

Accurate evaluation of fish stock biomass is essential for effective conservation management and targeted species enhancement efforts. However, this remains challenging owing to limited data availability. Therefore, we present an integrated modeling framework combining catch per unit effort with ensemble species distribution modeling called CPUESDM, which explicitly assesses and validates the spatial distribution of stock biomass for freshwater fish species with limited data, applied to Herzensteinia microcephalus. The core algorithm incorporates the Leslie regression model, ensemble species distribution modeling, and exploratory spatial interpolation techniques. We found that H. microcephalus biomass in the Yangtze River source area yielded an initial estimate of 113.52 tons. Our validation results demonstrate high accuracy with a Cohen's kappa coefficient of 0.78 and root mean square error of 0.05. Furthermore, our spatially-explicit, global, absolute biomass density map effectively identified areas with high and low concentrations of biomass distribution centers. Additionally, this study offers access to the source code, example raw data, and a step-by-step instruction manual for other researchers using field data to explore the application of this model. Our findings can help inform for future conservation efforts around fish stock biomass estimation, especially for endangered species.

Asymmetric response of vegetation GPP to impervious surface expansion: Case studies in the Yellow and Yangtze River Basins

Terrestrial gross primary production (GPP) changes due to impervious surfaces significantly impact ecosystem services in watersheds. Understanding the asymmetric response of vegetation GPP to impervious surface expansion is essential for regional development planning and ecosystem management. However, the asymmetric response of vegetation GPP to the impacts of impervious surface expansion is unknown in different watersheds. This paper selected the Yellow River and Yangtze River basins as case studies. We characterized the overall change in GPP based on changes in impervious surface ratio (ISR), determined impervious surface expansion's direct and indirect impacts on GPP in the two watersheds, and further analyzed the asymmetric response of the compensatory effects of indirect influences on the impervious surface expansion in different watersheds. The results showed that: (1) The vegetation GPP decreased with increasing ISR in the Yangtze River Basin, while that in the Yellow River Basin first increased and then reduced. (2) The direct impacts of increased ISR reduced vegetation GPP, while the indirect impacts both had a growth-compensating effect. Growth compensation stabilized at approximately 0.40 and 0.30 in the Yellow and Yangtze River Basins. (3) When the ISR was 0.34-0.56, the growth compensation could offset the reduction of GPP due to direct impact and ensure that the background vegetation GPP was not damaged in the Yellow River Basin. In contrast, the background vegetation GPP was inevitably impaired with increased ISR in the Yangtze River Basin. Therefore, this study suggests that the ISR should be ensured to be between 0.34 and 0.56 to maximize the impervious surface of the Yellow River Basin without compromising the background vegetation GPP. While pursuing impervious surface expansion in the Yangtze River Basin, other programs should be sought to compensate for the loss to GPP.

Extent and risks of microplastic pollution in the Yangtze River. State of the science

The Yangtze River (YR) is the longest river in Asia and the third longest in the world, and is recognized as one of the most microplastic-polluted rivers globally. However, to date, no consistent and systematic risk assessment has been conducted for the YR basin or other rivers in China. Previous assessments of microplastic occurrence, distribution, or risks in the YR basin did not take into account the sometimes-limited quality of the data or compared incomparable data, which can lead to biased assessments. The actual prospective ecological risks of microplastic pollution in the YR basin are therefore unknown. In this review, we analyze data from 21 microplastic studies to assess the occurrence and distribution of microplastics and their characteristics. We also evaluate the quality of the studies using updated quality assurance/quality control (QA/QC) criteria. Although we observe an upward trend in QA/QC scores, indicating improved data quality, no study received positive scores on all critical criteria. The microplastic exposure data from the YR basin is among the highest reported for rivers and other aquatic systems worldwide, exceeding effect thresholds in some parts of the river. We recommend generating comprehensive monitoring data of higher quality, with a greater emphasis on smaller-size microplastics, so that future risk assessments can be performed with less reliance on data alignment.

[Runoff Simulation and Its Response to Extreme Precipitation in the Yangtze River Basin]

Studies on runoff are crucial for the scientific allocation, utilization, and development of water resources and can provide an important basis for the prevention and control of flood and drought disaster, as well as water environmental pollution management. Affected by global warming, the frequency and intensity of extreme climate events, particularly extreme precipitation, have significantly changed in recent years, which can directly or indirectly impact runoff changes. In this study, we used the SWAT model to simulate the spatiotemporal variations in runoff in the Yangtze River Basin from 1965 to 2019 and analyzed the response of runoff to precipitation under extreme conditions. The results showed that the changes in total runoff in the Yangtze River Basin were not significantly different from 1965 to 2019. The total runoff and the mid-lower runoff in the basin experienced four stages of "dry-wet-dry-wet." Simulations revealed that under the 50-year extreme precipitation event, the increase in daily average runoff was 6200%, 21%, and 15% for the typical sub-basins of the upper, middle, and lower reaches of the Yangtze River, respectively. Additionally, the increase in monthly and annual average runoff was 355%, 5%, and 1.3% and 78%, 1%, and 0.24%, for upper, middle, and lower reaches of the Yangtze River, respectively. Moreover, under the 100-year extreme precipitation, the average daily runoff increasing rates were 8000%, 25%, and 17% for upper, middle, and lower reaches of the Yangtze River, respectively, compared to the monthly increase of 437%, 7%, and 1.5% and annual increase of 96%, 1.2%, and 0.28%, respectively. Our findings may improve the understanding of hydrological responses to climate change and provide valuable inferences to decision-makers and water managers for better allocation and management of water resources.

The pollution of microplastics in sediments of the Yangtze River Basin: Occurrence, distribution characteristics, and basin-scale multilevel ecological risk assessment

Microplastics (MPs) pollution in the Yangtze River Basin (YRB) of China has grown to be a serious issue, yet there is a lack of understanding of the environmental risks of MPs in the sediment of the entire basin. This work revealed the spatial distribution characteristics of MPs in YRB sediments, and it methodically assessed the ecological risks of MPs by taking into consideration their abundance, toxic effects, and polymer types. The results showed a high heterogeneity in the abundance of MPs in YRB sediments, with an average of 611 particles/kg dry weight (DW) sediment. Small-sized MPs (<1 mm), fibrous, transparent-colored and polypropylene (PP) accounted for the majority with 71.6%, 68%, 37% and 30.8%, respectively. Correlation analysis indicated significant influences of human activities such as population, industrial structure, and urban wastewater discharge on the abundance and morphological types of MPs in sediments. Based on chronic toxicity data exposed to sediments, a predicted no-effect concentration (PNEC) of 539 particles/kg DW was calculated using the species susceptibility distribution (SSD). Multiple deterministic risk assessment indices indicated that MPs in YRB sediments exhibited primarily low pollution load levels, moderate-to-low potential ecological risk levels, and high levels of polymer pollution. However, probabilistic risk assessment revealed an overall low risk of MPs in YRB sediments. Monte Carlo simulation results demonstrated that polyvinyl chloride (PVC) and polycarbonate (PC) made a great contribution to ecological risk and should be considered as priority control pollutants in MPs. In addition, various assessments showed that the ecological risk of MPs in river sediments was higher than that in lake reservoir sediments. This is the first study to comprehensively assess the ecological risk of MPs in sediments of the YRB, which improves the understanding of the basin-wide occurrence characteristics and environmental risks of MPs in freshwater systems.

Spatiotemporal distribution and controlling factors on ammonium in waters in the central Yangtze River Basin, China

High levels of ammonium in water can compromise the ecological environment and be harmful to human beings. It is of great significance to understand the source and controlling factors of ammonium in waters. However, the distribution and controlling factors on ammonium in the central Yangtze River Basin have been rarely reported. The results showed that 6.58% of the surface water (SW) exceeded the China national guideline of category III for NH4+-N (i.e., 1.0 mg/L) and 30.19% of the groundwater (GW) exceeded the China national guideline of category III for NH4+-N (i.e., 0.5 mg/L). Notably, the ammonium concentrations of the plain area in the middle were much higher, which reached to the highest value at the junction of the Yangtze River and Dongting Lake. Nitrogen in SW may originate from manure but more nitrogen sources in GW. The net anthropogenic nitrogen input (NANI) can provide enough organic nitrogen for the mineralization. NH4+-N in SW was more affected by fertilizer nitrogen and feed nitrogen input but more affected by agricultural nitrogen fixation in GW. Agricultural and industrial activities controlled NH4+-N in SW and GW by increasing nitrogen input and changing hydrological conditions. In general, this research exposed the controlling of different types of factors on ammonium in waters, providing a guidance for the water pollution prevention in study area.

[Spatiotemporal Variation Characteristics of Main Pollutant Fluxes in the Yangtze River Basin from 2017 to 2020]

Based on the monitoring data of various pollutants at important water system points in the Yangtze River Basin from 2017 to 2020, research on the flux change law of the main and tributary water systems in the Yangtze River Basin was carried out at the spatiotemporal scale, and the spatial change response, interannual change trend, and flux correlation analysis were analyzed from the aspects of water quantity, quality, and flux so as to reveal the spatial-temporal contribution characteristics of pollutant flux in the upper, middle, and lower reaches of the Yangtze River Basin. The results showed that over the past four years, the concentration of major pollutants in the Yangtze River Basin showed an overall downward trend. The concentration of total phosphorus (TP) and ammonia (NH+4-N) decreased significantly. The concentration of total nitrogen (TN) and total phosphorus (TP) in the main stream gradually increased from west to east. The annual concentration of permanganate index in the upper, middle, and lower reaches decreased by 18.5%, 16.0%, and 14.0%, respectively, from 2017 to 2020, with the highest decline in the upper reaches. The four-year average value of the spatial distribution of runoff significantly increased from 466×108 m3 to 9923×108 m3. The two lake basins in the tributary river lake water system had the largest contribution to the water volume. The fluxes of permanganate index, total phosphorus (TP), and total nitrogen (TN) among the main pollutants showed an annual increase and then decrease trend. The pollutant fluxes in the Minjiang River, Tuojiang River, Jialing River, and the middle reaches of the two lakes contributed greatly to the river inflow. There were differences in fluxes in different regional water environments. The results of correlation and hierarchical cluster analysis showed that the permanganate index and TP fluxes were highly significantly correlated with water volume, and there was a significant correlation between biochemical oxygen demand (BOD5) and total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD). The main pollutants showed strong differences in the flood and non-flood periods and had a significant response in the flood season from July to September. The research results can provide scientific basis and theoretical support for the integrated management and precise prevention and control of the aquatic environment in the Yangtze River Basin.

Spatial relationship between land urbanization and ecosystem health in the Yangtze River Basin, China

Globally, land-based urbanization had far-reaching impacts on ecosystem health. Determining the spatial relationship between land urbanization and ecosystem health is important for sustainable socioeconomic development and ecological protection. However, existing studies lack research on these relationships in basin regions, which may limit the implementation of effective basin ecological management measures. Based on multi-source data, this study analyzed the spatiotemporal patterns and spatial correlations of land urbanization rate (LUR) and ecosystem health index (EHI) in the Yangtze River basin (YRB) with a series of spatial analysis methods. The results showed that EHI in the YRB decreased by 0.024 during 2000-2020, with a decreasing range of 3.133 %, while LUR increased by 0.216, with an increasing range of 54.135 %. LUR has a significant negative spatial correlation with EHI, with high EHI and high LUR (9.814% in 2020) and high EHI and low LUR (12.397% in 2020) being the main types of agglomeration. The global regression results showed that LUR significantly negatively affected EHI. At the local scale, the LUR positively affected the EHI in the mountainous region, while the opposite was confirmed in the plain region. This study can provide scientific reference for the development of sustainable urban land control measures and basin ecological management measures.

[Estimation of Cropland Nitrogen Runoff Loss Loads in the Yangtze River Basin Based on the Machine Learning Approaches]

A quantitative understanding of cropland nitrogen (N) runoff loss is critical for developing efficient N pollution control strategies. Using correlation analysis, a structural equation model, variance decomposition, and machine learning methods, this study identified the primary influencing factors of total N (TN) runoff loss from uplands (n=570) and paddy (n=434) fields in the Yangtze River Basin (YRB) and then developed a machine learning-based prediction model to quantify cropland N runoff loss load. The results indicated that runoff depth, soil N content, and fertilizer addition rate were the major influencing factors of TN runoff loss from uplands, whereas TN runoff loss rate from paddy fields was mainly regulated by runoff depth and fertilizer addition rate. Among the four used machine learning methods, the prediction models based on the random forest algorithm presented the highest accuracy (R²=0.65-0.94) for predicting upland and paddy field TN runoff loss rates. The random forest algorithm based model estimated a total cropland TN loss load in the YRB of 0.47 Tg·a^-1 (upland:0.25 Tg·a^-1; paddy field:0.22 Tg·a^-1) in 2013, with 58% of TN runoff loss load derived from the midstream and downstream regions. The models predicted that TN runoff loss loads from croplands in YRB would decrease by 2.4%-9.3% for five scenarios, with higher TN load reductions occurring from scenarios with decreased runoff amounts. To mitigate cropland N nonpoint source pollution in YRB, it is essential to integrate efficient water, fertilizer, and soil nutrient managements as well as to consider the midstream and downstream regions as the high priority area. The machine learning-based modeling method developed in this study overcame the difficulty of identifying the functional relationships between cropland TN loss rate and multiple influencing factors in developing relevant prediction models, providing a reliable method for estimating regional and watershed cropland TN loss load.

How can multiscenario flow paths of water supply services be simulated? Establishing the supply-flow-demand model of ecosystem services across a typical basin in China

Ecosystems provide many benefits to humans, and among them, water supply is crucial for human survival and development. This research focused on the Yangtze River Basin as the research area, quantitatively evaluated the temporal-spatial dynamic changes in the supply and demand of water supply services and determined the spatial relationship between the supply and demand regions of water supply services. We constructed the supply-flow-demand model of water supply service to quantify its flow. In our research, the Bayesian model was used to establish a multiscenario model of the water supply service flow path to simulate it and clarify its spatial flow path, flow direction and flow magnitude from the supply region to the demand region and determine its changing characteristics and driving factors in the basin. The results show that (1) In 2010, 2015 and 2020, the amount of water supply services showed a decreasing trend and was approximately 133.57 × 10¹² m³, 129.97 × 1012 m³ and 120.82 × 10¹² m³, respectively. (2) From 2010 to 2020, the trend of the cumulative flow of water supply service flow decreased each year and was 59.814 × 10¹² m³, 56.930 × 10¹² m³, 56.325 × 10¹² m³ respectively. (3) Under the multiscenario simulation, the flow path of the water supply service was generally the same. The proportion of the water supply region was the highest under the green environmental protection scenario, at 73.8 %, and the proportion of the water demand region was the highest under the economic development and social progress scenario, at 27.3 %. (4) The provinces and municipalities in the basin were divided into three types of regions according to the matching relationship between supply and demand: catchment region, flow pass-through region and outflow region. The number of outflow regions was lowest, accounting for 23.53 %% of the regions, while the number of flow pass-through regions was the highest, accounting for 52.94 %.

Regional differences and driving forces of ecosystem health in Yangtze River Basin, China

Ecosystem health in the Yangtze River basin (YRB) shows significant regional differences. Analysis of regional differences and drivers of ecosystem health in YRB is of practical significance for sustainable basin ecological management. However, existing studies lack research on regional differences and driving forces of ecosystem health, especially in big basin regions. Based on multi-source data, this study adopted spatial statistics and distribution dynamics models to quantitatively analyze the regional differences of ecosystem health in the YRB during 2000-2020 and employed the spatial panel model to reveal the driving forces of ecosystem health in the YRB. The ecosystem health index of the upper, middle, and lower reaches of YRB and the entire basin in 2020 was 0.753, 0.781, 0.637, and 0.742, respectively, while they all decreased during 2000-2020. Regional differences in YRB ecosystem health increased during 2000-2020. From the perspective of dynamic evolution, low-level and high-level ecosystem health units evolved to high-level, while medium-high-level ecosystem health units evolved to low-level. High-high (accounting for 30.372% in 2020) and low-low (accounting for 13.533% in 2020) were the main cluster types. Regression result showed that urbanization was the main reason for ecosystem health deterioration. The findings can provide enlightenment to further understand the regional differences of ecosystem health in YRB and provide theoretical reference for the coordinated management of ecosystem at macro-level and the differential regulation of local ecosystem at micro-level in the basin region.

Characterizing drought events occurred in the Yangtze River Basin from 1979 to 2017 by reconstructing water storage anomalies based on GRACE and meteorological data

The extreme change of water storage in the Yangtze River Basin (YRB) have a significant impact on identifying the characteristics of drought events in the basin. To quantify the historical hydrological drought characteristics, we put forward new framework to reconstruct the pre-2003 total water storage anomaly (TWSA) through the nonlinear autoregressive with exogenous input (NARX) model. The NARX model is developed by the Gravity Recovery and Climate Experiment (GRACE) based TWSA and the hydrometeorological data after removing the trend and seasonal signals from 2003 to 2017, then the full pre-2003 reconstructed TWSA signals were obtained by synthesizing hydrometeorological data driven NARX model results from 1979 to 2002 and GRACE-estimated seasonal cycle. We combined the reconstructed TWSA with GRACE observed TWSA to characterize the historical hydrological drought events (onset, end, duration, magnitude, intensity, and recovery) in the YRB. The results show that the drought-related extreme anomalies in total water storage can be captured successfully. From 1979 to 2017, 23 hydrological drought events were identified in the YRB with an average recovery time of 4.7 months. The longest drought lasted 28 months spanning from July 2006 to October 2008. The exceptional drought occurred in September 2011 reached to the largest deficit with a magnitude of -48.5 mm and minimum drought severity index (DSI) of -2.3. Comparing to the period of 1979-1999, the frequency, duration, and average recovery time of drought events increased significantly since 2000 in the YRB. Furthermore, we found that the duration and average recovery time of the drought events have an exponential relationship with the severity, which could help us to estimate the potential recovery time when drought events occur and predict water resources dynamic in the future.

[Environmental Driving Factors and Assessment on the Aquatic Ecosystem of Periphytic Algae of Six Inflow Rivers in Yangtze River Basin]

Phytoplankton is frequently utilized in the assessment of water ecological health, and a great number of related studies have been conducted in China; however, most of them are limited in scope. A phytoplankton survey was carried out at the basin scale in this study. A total of 139 sampling sites were set up in crucial locations of the main stream, from the Yangtze River's source region to the estuary, as well as the eight primary tributaries and the Three Gorges' tributaries. In the Yangtze River Basin, phytoplankton was found in seven phyla and 82 taxa, with Cryptophyta, Cyanophyta, and Bacillariophyta being the dominant species. To begin, the composition of phytoplankton communities in various sections of the Yangtze River Basin was studied, and LEfSe was utilized to identify highly enriched species in different regions. The association between phytoplankton communities and environmental factors in different sections of the Yangtze River Basin was then investigated using CCA. The generalized linear model demonstrated that TN and TP were strongly positively linked with phytoplankton density at the basin scale, whereas TITAN analysis identified the environmental indicator species and their corresponding optimal growth threshold range. Finally, the study assessed each Yangtze River Basin Region in terms of biotic and abiotic factors. Although the results of the two aspects were incongruent, the analysis of all indicators using the random forest method can yield comprehensive and objective ecological evaluation results for each section of the Yangtze River Basin.

Warming of surface water in the large and shallow lakes across the Yangtze River Basin, China, and its driver analysis

A variety of physical, chemical, and biological processes within the lakes relies on the surface water temperature while the spatial pattern of large lakes of different warming trends and their connections with climate change remain unclear. Using correlation analysis, regression tree analysis (RTA), and general linear models (GLMs), we have estimated the warming trends of 192 lakes since 2000 in the populated Yangtze River Basin, China, to identify dominant climate drivers and quantify their contributions. The results show that surface water temperature has increased substantially in the majority of the investigated lakes (179 from a total of 192 lakes) at a rate of 0.29 (- 0.12 to 0.62) °C/decade (median and 95% confidence interval). The shallower lakes (< 13.1 m in depth) usually have the faster median warming rates than the deeper lakes (i.e., 0.37 °C/decade versus 0.16 °C/decade). We find that in the shallow lakes, rising air temperatures and declining wind speeds can explain the majority of variation in surface water temperature (i.e., 31.4‒80.3% and 13.0‒21.0%, respectively). In contrast, in deeper lakes, change of air temperatures plays a dominant role in water warming (75.4‒91.2%). This study has emphasized the importance of declining wind speed in water warming in large and shallow lakes and illustrated a difference of dominant climatic drivers in water warming between the shallow and deep lakes.

Spatial and Temporal Changes of Sand Mining in the Yangtze River Basin since the Establishment of the Three Gorges Dam

The global demand for sand and gravel is at 50 billion tons per year, far exceeding global resource capacities. It reached 7.6 billion tons in 2021 in the Yangtze River Basin (YRB), China. However, production is severely limited in the YRB. Therefore, the incongruity between the supply and demand of river sand is prominent. Wise management of decreasing sand resources in the YRB has become critical since the Three Gorges Dam became operational in 2003. This study synthesized spatial and temporal changes in sand mining activities and quantities along the Yangtze River and its major tributaries from 2004 to 2020. Results from the study show that the mining amount during the period reached 76.2 million tons annually. At the same time, riverine suspended sediment discharge (SSD) downstream of the Three Gorges Dam decreased largely. SSD reduction leads to riverbed erosion, further limiting the riverine sand and gravel sources for mining. Thus, alternative sand and gravel resources, as well as optimizing supply/demand balance, are necessary for sustainable development. There is an urgent need to assess the relationship between river sand resources and exploitation in the YRB for creating a sand and gravel data management system in order to cope with the increasing incongruity between their supply and demand.

Afforestation of Taxodium Hybrid Zhongshanshan Influences Soil Bacterial Community Structure by Altering Soil Properties in the Yangtze River Basin, China

Taxodium hybrid Zhongshanshan has been widely planted in the Yangtze River Basin (YRB) for soil and carbon conservation, with quantities over 50 million. The objective of this study was to determine how T. hybrid Zhongshanshan plantations affected soil physicochemical properties and bacterial community structure in the YRB, and to examine the consistency of changes by afforestation. Soils under T. Zhongshanshan plantations across six sites of the YRB were compared with soils of adjacent non-forested sites. Soil physicochemical properties and bacterial community structure were determined to clarify edaphic driving factors and reveal the effects of afforestation on bacteria. The results indicated that most soil attributes manifested improvements, e.g., total nitrogen in Jiangxi and Shanghai; available phosphorus in Hubei, Chongqing and Yunnan, exhibited the potential to maintain or ameliorate soil quality. A decrease in soil bulk density caused by plantation was also observed at the expense of soil macro-aggregates augment. Afforestation of T. Zhongshanshan plantation has habitually improved Shannon diversity and Chao1 richness, of which dominant phyla were Proteobacteria, Acidobacteria, and Actinobacteria, and increased the relative abundance of the phyla Proteobacteria and Nitrospirae, and the classes Flavobacteriia, Acidobacteria_Gp5, and Bacilli. We concluded that T. Zhongshanshan plantation can be employed to facilitate soil nutrient accumulation in the YRB, but that the degree, rate and direction of changes in soil attributes are sites dependent. It is recommended that afforestation of nutrient-depleted and less productive lands in the YRB should utilize this fast-growing species in combination with proper fertilization.

Spatial and temporal distribution and affecting factors of iron and manganese in the groundwater in the middle area of the Yangtze River Basin, China

Iron (Fe) and manganese (Mn) are heavy metals ubiquitous in groundwater. High levels of Fe and Mn in groundwater can compromise water quality and pose a risk to human health if the groundwater is used for drinking or irrigation. In the middle region of the Yangtze River Basin, groundwater has been extensively used for domestic and agricultural purposes. However, little is known about the distribution of Fe and Mn in the groundwater in this area. It was found that the 74.4% and 48.9% of the groundwater exceed the China national guideline for Fe (i.e., 0.3 mg/L) and Mn (i.e., 0.1 mg/L), respectively. And 6.38% and 2.13% of the wells had Fe and Mn health risks, respectively. Spatial heterogeneity of Fe and Mn was observed. Notably, the concentrations of Fe and Mn in a plain region located between two major rivers (i.e., the Yangtze River and the Han River) were significantly higher than those in other regions. Modeling using PHREEQC revealed that the Fe-bearing minerals in the plain region were more saturated compared to those in the other regions. Besides, temporal change of Fe and Mn was observed in the plain region, significantly affected by rainfalls and groundwater levels. In addition, the distribution of Fe and Mn was significantly affected by various physicochemical factors. Particularly, Fe was more sensitive to redox potential compared to Mn. Under a reducing condition, organic matter concentration and water residence time also affect the release of Fe from Fe-bearing minerals. Overall, a comprehensive understanding of distribution characteristics of Fe and Mn and affecting factors in the middle area of the Yangtze River Basin can provide guidance for the distribution of industrial water, agricultural water, and drinking water in different regions of the study area. Especially in the plain area between the Yangtze River and the Han River, direct drinking of groundwater shall be reduced since the higher health risk value of Fe and Mn.

Identifying the Impacts of Climate Change and Human Activities on Vegetation Cover Changes: A Case Study of the Yangtze River Basin, China

The normalized difference vegetation index (NDVI) is a useful indicator to characterize vegetation development and land use which can effectively monitor changes in ecological environments. As an important area for ecological balance and safety in China, understanding the dynamic changes in land cover and vegetation of the Yangtze River Basin would be crucial in developing effective policies and strategies to protect its natural environment while promoting sustainable growth. Based on MODIS-NDVI data and meteorological data from 2000 to 2019, the temporal and spatial distribution of vegetation coverage in the Yangtze River Basin during the past 20 years were characterized, and the impacts of human activities and climate change were quantitatively evaluated. We drew the following research conclusions: (1) From 2000 to 2019, the vegetation cover of the Yangtze River Basin presented a fluctuating inter-annual growth trend. Except for the Taihu Lake sub-basin, the vegetation cover in other sub-basins showed an upward trend. (2) The vegetation cover exhibited a spatial distribution pattern of “high in the middle and low in the east and west”, with the multi-year average value of NDVI being 0.5153. (3) Areas with improved vegetation cover were significantly larger than the areas with degraded foliage. The central region has stronger overall trend of change than the east, and the east is stronger than the west. These vegetation cover changes are largely related to anthropogenic activities. (4) Vegetation cover changes due to precipitation and temperature exhibited significant spatial heterogeneity. While both temperature and precipitation influenced vegetation cover, the temperature was the leading climate factor in the area. (5) Anthropogenic and climate factors jointly promoted the change of vegetation cover in the Yangtze River Basin. Human activities contributed 79.29%, while climate change contributed 20.71%. This study could be used in subsequent studies analyzing the influencing factors affecting long-term vegetation cover in large-scale watersheds.

Source and formation process impact the chemodiversity of rainwater dissolved organic matter along the Yangtze River Basin in summer

Rainwater dissolved organic matter (DOM) plays an important role in the biogeochemical cycle and evolution of organic matter in the land-atmosphere interface. To better understand their sources and molecular composition in the atmosphere, rainwater samples were collected at six different locations along the Yangtze River Basin. Based on the application of a combined approach including excitation-emission matrix (EEM) fluorescence and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), various sources (terrestrial, anthropogenic, and autochthonous sources) of rainwater DOM were revealed. Results show that the derivatives of biogenic volatile organic compounds were widely distributed and contributed to rainwater DOM along the Yangtze River Basin. In the up-river city Batang, rainwater DOM was affected by the long-range atmospheric transport due to the Indian summer monsoon. Lijiang, a city on the southeastern edge of Tibetan plateau, was related to strong local biomass burning. The industrial cities of Panzhihua and Luzhou showed large differences in organic composition due to distinct industrial types. Fuling, a district in Chongqing Municipality, was significantly contributed by aged organics from biomass burning. While rainwater DOM in Shanghai, a coastal megacity, contained a high fraction of sea spray organics. Further, more than 70% of rainwater DOM molecules are associated with 36 typical transformation mechanisms during rainwater-scavenging processes, e.g., oxidation reactions, dealkylation and decarboxylation. Our study demonstrates that local natural and anthropogenic emissions and climatic conditions strongly shaped the chemodiversity and possible precursor-product pairs of rainwater DOM along the Yangtze River Basin, which helps to better understand the biogeochemical cycles of organic matter in a large-scale watershed under the influence of human activities.

Environmental fate of microplastics in the world's third-largest river: Basin-wide investigation and microplastic community analysis

Rivers have been recognized as major transport pathways for microplastics into the sea but large-scale quantitative data on the environmental fate of riverine microplastics remains limited, hindering proper risk assessment and development of regulatory measures. Microplastics in the whole Yangtze River Basin of China were systematically investigated by sampling the water, sediment, and soil. Microplastics were detected in all samples, with an average abundance of 1.27 items/L, 286.20 items/kg, and 338.09 items/kg for water, sediments, and soils, respectively, with polypropylene and polyethylene being the most abundant polymers. A generally increasing trend of microplastic abundance from upstream to downstream was identified, which were co-attributed by geographical and anthropogenic factors including elevation, longitude, distance from the nearest city, population density, urbanization rate, and land use. Microplastics in the sediments showed more prominent vertical migration than those in the soils, and the density and size of microplastics may be the key factors governing the migration of microplastics across different compartments. Community analysis showed that microplastics in different compartments were significantly different and highly correlated with geographical distance. Major cities at the middle and lower reaches were considered pivotal nodes of microplastic pollution in the Yangtze River Basin. Policy recommendations were also proposed towards better remediation of microplastic pollution involving riverine systems.

Measurement and driving factors of grey water footprint efficiency in Yangtze River Basin

Water shortages and poor water quality have become an urgent problem that is constraining the sustainable development of China. Grey water has been found to bring greater stress on the water supply than freshwater consumption, and the grey water footprint (GWF) has received significant attention as a comprehensive indicator to assess wastewater pollution. In this study, we analysed the grey water footprint in the Yangtze River Basin from 2003 to 2017 and established a Logarithmic mean divisia index (LMDI) model to decompose the grey water footprint efficiency into six key factors. Our findings are as follows: (1) The average grey water footprint (AGWF) in the central regions was 40% higher than eastern region and 172% higher than western region; (2) Economic effects and capital deepening effects are the main factors affecting positive changes in grey water footprint efficiency; (3) Based on an analysis of the driving factors of greywater footprint efficiency in each province, we conducted a territorial classification according to the primary driving factors in each province. Our results reflect the spatial distribution characteristics of the influencing factors on the grey water footprint effect in the Yangtze River Basin and will enable the government to formulate relevant policies for each subregion.

Assessment on Temporal and Spatial Variation Analysis of Extreme Temperature Indices: A Case Study of the Yangtze River Basin

Extreme temperature change is one of the most urgent challenges facing our society. In recent years, extreme temperature has exerted a considerable influence on society and the global ecosystem. The Yangtze River Basin is not only an important growth belt of China’s social and economic development, but also the main commodity grain base in China. The purpose of this study is to study the extreme temperature indices in the Yangtze River Basin. In this study, the Mann–Kendall nonparametric test and R/S analysis method are used to analyze the spatial and temporal variation characteristics of major extreme temperature indices in the Yangtze River Basin from 1970 to 2014. The main conclusions are drawn as follows: (1) The occurrence of cold days (TX10), cold nights (TN10), ice days (ID), and frost days (FD) decrease at a rate of −0.66–−2.5 d/10a, respectively, while the occurrence of warm days (TX90), warm nights (TN90), summer days (SU), and tropical nights (TR) show statistically significant increasing trends at a rate of 2.2–4.73 d/10a. (2) The trends of the coldest day (TXn), coldest night (TNn), warmest day (TXx), warmest night (TNx), and diurnal temperature range (DTR), range from −0.003 to 0.5 °C/10a. (3) Spatially, the main cold indices and warm indices increase and decrease the most in the upper and lower reaches of the Yangtze River Basin. (4) DTR and TN90 show no abrupt changes; the main cold indices changed abruptly in the 1980s and the main warm indices changed abruptly in the late 1990s and early 2000s. (5) The extreme temperature indices are affected by the atmospheric circulation and urban heat island effect in the Yangtze River Basin. Relative indices and absolute indices will continue to maintain the present trend in the future. In short, the main cold indices of extreme temperature indices show a decreasing trend, the main warm indices of extreme temperature indices show an increasing trend, and cold indices and warm indices will continue to maintain the present trend in the future in the Yangtze River Basin. Extreme temperature has an important impact on agriculture, social, and economic development. Therefore, extreme temperature prediction and monitoring must be strengthened to reduce losses caused by extreme temperature disasters and to promote the sustainable development in Yangtze River Basin.

Influence of socioeconomic development on river water quality: a case study of two river basins in China

Social and economic development processes require large amounts of natural resources and in some cases seriously deteriorate river water quality. Since the reform and expansion era began, China has vigorously pursued socioeconomic development but neglected environmental protection. However, in recent years, improvements in environmental awareness and the implementation of environmental protection measures have led to a balanced relationship between economic development and the environment. In this study, the Yangtze River Basin and the Yellow River Basin were selected as research areas. We used a combination of canonical correlation analysis (CCA) and a distance-based influence assessment method to quantitatively assess the influence of socioeconomic development on river water quality. The results revealed a strong correlation between socioeconomic development and river water quality. The degree of influence of socioeconomic development on water quality varied not only temporally but also spatially due to differences in socioeconomic development and hydrometeorology in the two basins in North and South China. The average degree of influence in the Yangtze River Basin was between 0.22 and 0.27, and that in the Yellow River Basin was between 0.2 and 0.36. Moreover, the degree of influence in the Yangtze River Basin in the wet season was greater than that in the dry season, whereas the opposite pattern was observed in the Yellow River Basin. The degree of influence in both basins gradually declined after 2011, indicating that the coupling and coordination between socioeconomic development and environmental protection have continuously improved and that the water quality has gradually improved. By analysing the influences of various socioeconomic indicators on water quality, we found that the main factors that influence water quality are per capita GDP and urbanization rate in the Yangtze River Basin and urbanization rate in the Yellow River Basin. The results provide a basis for future sustainable development in the Yangtze River Basin and the Yellow River Basin.

Available acid consumption capacity of sediments in six water bodies in the Yangtze River Basin in China

Acid-base reactivity is a fundamental property of sediments and is responsible for sediments' multiple roles in aquatic ecosystems. However, little information currently exists about the composition, magnitude, and change of the available acid consumption capacity (AACC) of sediments. To optimize reaction conditions, we developed operational procedures to determine AACC using base titration to recover surplus acid in suspensions. We characterized the sediment AACC of Dianchi Lake (DL), Daduhe River (DR), Tuojiang River (TR), Honghu Lake (HL), Wuhan Donghu Lake (DhL), and Taihu Lake (TL) in the Yangtze River Basin, China. The procedure demonstrated that reacting 40 mL 0.1 M HCl with fresh sediments equivalent to 1.0 g dry weight for 4 h and recovering surplus acid in the suspension by NaOH titration to an endpoint pH of 3.0 could determine sediment AACC. Sediment AACC in the Yangtze River Basin had high regional variability. The mean magnitude of AACC among sites was ranked DL > DR > DhL > TR > HL > TL, which is extremely similar to their geographical location from the upper to lower reaches of the Yangtze River Basin. Qualitative results from acid titration curves showed that more components contributed to AACC in DL, DR, TR, and DhL sediments than to those in HL and TL sediments. The correlation between AACC and the total amount of multivalent cations released indicated that AACC depended significantly on labile acid-soluble minerals that contain multivalent cations (Fe³⁺, Fe²⁺, Ca²⁺, Al³⁺, Mg²⁺, and Mn²⁺) (p < 0.01). Based on the contribution percentages of multivalent cations to AACC, sediment AACC of six water bodies were divided into two types: Ca-Mg dominated (DL, DR, and TR) and Fe-Al dominated (HL, DhL, and TL). We suggest that sediment AACC complexing with pH can contribute to a better description of the acid-base characteristics of sediments.

Impact of Urbanization on the Environmental Regulation Efficiency in the Yangtze River Basin Based on the Empirical Analysis of Spatial Econometrics

Urbanization has been positioned as an important driving force for economic development. This article examines the impact of urbanization on environmental regulation efficiency (ERE) in the Yangtze River Basin (YRB). Based on a panel dataset of 97 cities in the YRB from 2005 to 2016, a spatial econometric model was used for analysis. Results show that the average ERE in the YRB is relatively low and manifests in the shape of a curved smile. The urbanization level of the permanent population is far lower than the average level of developed countries. However, the urbanization level is showing a steady growth trend. During this period, ERE in the Yangtze River middle, upper, and lower reaches was measured at 0.77, 0.58, and 0.52, respectively. The urbanization rate was measured at 0.59, 0.45, and 0.39, in the lower, middle, and upper reaches, respectively. When only considering population urbanization, the previously observed negative correlation between ERE and the Kuznets curve disappears. However, if the carrying capacity of economic activities is considered, the U-shaped relationship between urbanization rate and ERE returns. The environmental Kuznets curve is consequently verified. In addition, there is an inverted U-shaped nonlinear relationship between economic development and ERE. The results of this article show that there are unsustainable risks in the rapid pursuit of population urbanization. Only by improving the quality of urbanization and adapting the level of urbanization to the carrying capacity of resources and environment can we truly promote high-quality economic development. The article puts forward some suggestions to promote the green development of the economy.

Two-Step Measurement of Water-Energy-Food Symbiotic Coordination and Identification of Key Influencing Factors in the Yangtze River Basin

With the intensification of people's production and life behaviors, the systemic risks of water, energy and food in the Yangtze River Basin have become increasingly prominent, which has become a bottleneck for sustainable development of social, economic and ecological in the basin. Therefore, studying the symbiotic coordination between water, energy and food is of great significance to promoting regional sustainable development. First, from the perspective of water-energy-food symbiosis, with the water-energy-food ecosystem conceptual model as the nexus, the two-step measurement model of the symbiotic index and the symbiotic level index is used to study the water-energy-food symbiosis of the Yangtze River. Then, we use the BP-DEMATEL-GTCW model to identify the key influencing factors that affect the symbiotic security of the water-energy-food ecosystem. In this research, it is found that the average value of the symbiotic degree of the water-energy-food ecosystem of the 11 provinces or municipalities in the Yangtze River Basin only reached the risk grade. It can also be seen from the identification results of key influencing factors that energy microsystem-related indicators have a greater impact on the symbiotic development of the entire WEF ecosystem. Therefore, special attention needs to be paid to increasing energy sources and reducing expenditure. Relevant departments need to effectively develop primary energy production and expand energy-saving investment through multiple channels to expand energy self-sufficiency and ultimately promote the coordinated and effective development of water, energy and food in the Yangtze River Basin.

Eco-environmental impacts of dams in the Yangtze River Basin, China

Nearly half large dams of China have been built in the Yangtze River Basin (YRB) and the eco-environmental impacts of existing dams remain elusive. Here we present a spatio-temporal approach to measuring the eco-environmental impacts of dams and its long-term changes. We also develop a new metric, the dam eco-environmental effect index (DEEI), that quickly identifies the eco-environmental impacts on dams over 36 years. Underlying the analysis are the revised universal soil loss equation (RUSLE), the generalized boosted regression modeling (GBM), the generalized linear model (GLM), stepwise multiple regression, trend analysis, soil erosion and sediment yield balance equation, and sample entropy used to identify the eco-environmental impacts of dams on yearly timescales. We find that the accumulated negative environmental effects of constructed dams have increased significantly and has led to large-scale hydrophysical and human health risk affecting the Yangtze River Basins downstream (i.e. Jianghan-Lushui-Northeastern Hubei, Dongting Lake District, Yichang-Jianli, and Qingjiang) and reservoir areas (i.e. Wanxian-Miaohe, Miaohe-Huanglingmiao, and Huanglingmiao-Yichang). We also provide observational evidence that dam construction has reduced the complexity of short-term (1-12 months) in runoff and sediment loads. This spatial pattern seems to reflect a filtering effect of the dams on the temporal and spatial patterns of runoff and sediment. Three Gorges Dam (TGD) has a significant impact on the complexity of the runoff and sediment loads in the mainstream of the Yangtze River. This enhanced impact is attributed to the high trapping efficiency of the dam and its associated large reservoir. This assessment may underestimate the cumulative effect of the dam because it does not consider the future effects of the planned dam. Our study provides a quantitative methodology for finding the relative change rate of eco-environmental impact on dams, which is the first step towards addressing the extent, process, and magnitude of the dam-induced effects.

Evaluation and Future Projection of Extreme Climate Events in the Yellow River Basin and Yangtze River Basin in China Using Ensembled CMIP5 Models Data

The Yellow River Basin (YLRB) and Yangtze River Basin (YZRB) are heavily populated, important grain-producing areas in China, and they are sensitive to climate change. In order to study the temporal and spatial distribution of extreme climate events in the two river basins, seven extreme temperature indices and seven extreme precipitation indices were projected for the periods of 2010-2039, 2040-2069, and 2070-2099 using data from 16 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, and the delta change and reliability ensemble averaging (REA) methods were applied to obtain more robust ensemble values. First, the present evaluation indicated that the simulations satisfactorily reproduced the spatial distribution of temperature extremes, and the spatial distribution of precipitation extremes was generally suitably captured. Next, the REA values were adopted to conduct projections under different representative concentration pathway (RCP) scenarios (i.e., RCP4.5, and RCP8.5) in the 21st century. Warming extremes were projected to increase while cold events were projected to decrease, particularly on the eastern Tibetan Plateau, the Loess Plateau, and the lower reaches of the YZRB. In addition, the number of wet days (CWD) was projected to decrease in most regions of the two basins, but the highest five-day precipitation (Rx5day) and precipitation intensity (SDII) index values were projected to increase in the YZRB. The number of consecutive dry days (CDD) was projected to decrease in the northern and western regions of the two basins. Specifically, the warming trends in the two basins were correlated with altitude and atmospheric circulation patterns, and the wetting trends were related to the atmospheric water vapor content increases in summer and the strength of external radiative forcing. Notably, the magnitude of the changes in the extreme climate events was projected to increase with increasing warming targets, especially under the RCP8.5 scenario.

Influence of the Three Gorges Reservoir on climate drought in the Yangtze River Basin

Although El Niño-Southern Oscillation (ENSO) has been widely confirmed to have significant impacts on climate change in Asia, it is unknown whether the climate change in the Yangtze River Basin (YTR basin) is related to the operation of the Three Gorges Reservoir, which is the world's largest hydropower station. In this study, we used the Standardized Precipitation Evapotranspiration Index (SPEI) as an indicator of climate change and found that the mutation period of the YTR basin was 2003-2006 based on three mutation tests. By analyzing the trends of the SPEI and five related meteorological factors before and after 2003, it was found that the construction of the Three Gorges Reservoir increased the relative humidity and provided a more humid climate for the downstream basin. The relationships between drought events and ENSO and the water level of the reservoir indicated that the basin was more prone to drought in El Niño years and the Three Gorges Reservoir could alleviate agricultural drought in the downstream basin. The spatial impacts of the Three Gorges Reservoir on regional climate change were more pronounced, while the impact of ENSO could not be reflected at the station scale.

Yangtze River Basin Environmental Regulation Efficiency Based on the Empirical Analysis of 97 Cities from 2005 to 2016

The Yangtze River Basin (YRB) is an important area for China's economic development and environmental governance. The aim of this paper is to analyze the total factor productivity across 97 cities in the YRB from 2005 to 2016. Based on the input and output indicators from 2005 to 2016, this paper selects the SE-SBM model to measure the environmental regulation efficiency (ERE) of 97 cities in the YRB and then uses the DEA-Malmquist index to measure the total factor productivity of the region. Results suggest that the overall ERE in the YRB is weakly ineffective, while ERE in the central and eastern coastal areas is relatively high. ERE matches the economic foundation and development of the city. YRB environmental regulation efficiency was in descending order in the middle stream, upstream, and downstream. The efficiency of regional environmental regulation shows an N-type development trend, with obvious characteristics of phased development. Moreover, the total factor productivity of the YRB has shown a downward trend. The scale efficiency index and the technical efficiency index have positively boosted the total factor productivity, while the technological progress index has dragged down the total factor productivity of the area. The contribution to the total factor productivity index is in order of scale efficiency, technological progress index, and technological efficiency index in the downstream. The overall inputs and outputs of the YRB have great development potential. The inputs have not been fully utilized, the outputs have not been maximized, and the regional differentiation is significantly observable.

Temporal-spatial dynamics of anthropogenic nitrogen inputs and hotspots in a large river basin

Environmental pollution caused by human activities in the Yangtze River Basin (YRB), especially nitrogen pollution, has always been a hot topic. High-intensity anthropogenic nitrogen (AN) inputs have undergone some changes on account of environmental management practices in the YRB. We used the latest statistical data (2000-2017) to estimate spatiotemporal heterogeneity of AN inputs across the YRB, characterize hotspots of AN inputs, and predict the future trend, which is critical to meet nitrogen management challenges. We found agricultural sources were major contributors to nitrogen inputs (more than 70%) in the YRB. Due to the reduction in agricultural fertilizers use in China, AN inputs had gradually decreased from a peak of 19.0 Tg/yr in 2014 after a rapid growth period. Additionally, the nitrogen flux in sub-catchments and from various sources indicated an increasing distribution characteristic from the upper reaches to the lower reaches. Hotspots of AN inputs were mainly concentrated in the Sichuan Basin and the Middle-Lower Yangtze Plain (more than 50 tons/km²), however, growth rates were relatively low or even negative. STIRPAT model showed population size was the most important factor affecting AN loads. Although the growth rate would slow down in the future, AN loads would be maintained at a high level. Besides, aquaculture had become an important source of potential nitrogen growth in the whole basin, although the contribution was relatively small at present. Controlling nitrogen loads in hotspots and avoiding high inputs of new nitrogen sources should be the focus of future nitrogen environmental management.

Changes in precipitation extremes in the Yangtze River Basin during 1960-2019 and the association with global warming, ENSO, and local effects

Extreme precipitation events can pose great risks to natural ecosystems and human society. Investigating past changes in the frequency, intensity, and duration of such events and understanding the possible driving factors are critical for reliable projections of future changes and for informing adaptation strategies planning. Here we analyze trends in a complete list of extreme precipitation indices (EPIs) over the Yangtze River Basin (YRB) during the period of 1960-2019. Also, we examine the possible influences of global warming, ENSO, and local effects on the spatiotemporal variability of the EPIs. Our results show that average and extreme precipitation intensities, and the frequency of extreme heavy precipitation in the YRB have significantly increased, while precipitation frequency and maximum duration of wet spells have significantly decreased. A regional difference in trend occurrence and magnitude is also observed, showing the intensity and frequency of precipitation extremes over the Middle and Lower reaches are more likely to increase and increase faster, compared with those of the Upper reach of the YRB. Furthermore, our correlation analysis shows global warming, ENSO, and local effects all are significant driving factors that control the spatiotemporal variability of precipitation extremes over the YRB. Global warming tends to enhance the frequency and intensity of precipitation extremes. The La Niña phase of ENSO often corresponds to an increase of frequency and intensity of precipitation extremes in the current year, but a decrease of frequency and intensity in the coming year. Local warming mainly exerts a reducing effect on precipitation extremes, which is likely a response to the significant decrease of relative humidity in the YRB. Our findings highlight the need for a systematic approach to examine global, regional, and local drivers of trends in precipitation extremes in the YRB, and contribute to the understanding of precipitation changes in this region.

Human-driven spatiotemporal distribution of phosphorus flux in the environment of a mega river basin

Large river basins transport considerable nutrients to the ocean every year. However, phosphorus (P) generated by human activities not only threatens aquatic ecosystem health in the river basin, but also has a negative effect on the estuary water environment. To better understand the environmental effects of anthropogenic P in a mega basin, we examined its inputs and distribution characteristics, and analyzed the factors driving it in the Yangtze River Basin (YRB) and sub-catchments. Anthropogenic P flux in the sub-catchments gradually increased from upper to lower reaches, and hotspots were primarily concentrated in traditional agricultural areas such as the Sichuan Basin and the Middle-Lower Yangtze plains. Agricultural sources were the main anthropogenic P inputs, of which fertilizer P was the leading contributor and driver of P changes, but livestock manure also accounted for a high proportion. Presently, anthropogenic P inputs in the YRB are considerably higher than in other parts of the world. Although long-distance transportation allows some P from the entire basin to be deposited in freshwater, a large amount of P still reaches the estuary and has a negative effect on water quality, outweighing the influence of local coastal inputs. To maintain the ecological health of the river basin and estuary, it will be necessary to further improve P utilization efficiency and encourage greater cooperation between different regions in the river basin.

Eutrophication assessment of seasonal urban lakes in China Yangtze River Basin using Landsat 8-derived Forel-Ule index: A six-year (2013-2018) observation

Lakes eutrophication have been a complex and serious problem for China's Yangtze River Basin. A series of algorithms based on different remote sensing dataset have been proposed to simulate the lakes trophic state. However, these algorithms are often targeted at a particular lake and cannot be applied to a watershed management. In this study, a Forel-Ule index (FUI) method based on Landsat 8 OLI image is proposed to simulate trophic state index (TSI) in three typical urban lakes (Dianchi, Donghu, and Chaohu) from 2013 to 2018. The results show that the Landsat 8 derived FUI can well represent the lake TSI with an accuracy of R² = 0.6464 for the in situ experimental TSI dataset (N = 115) and R² = 0.8065 for the lake average TSI dataset (N = 315). In the study period 2013-2018, the order of the simulated TSI is Dianchi > Chaohu > Donghu. Seasonal dynamics show differences where the percentage of eutrophic area in summer is significantly lower than the other seasons for Lake Dianchi and Chaohu. However, the percentage of eutrophic area for Lake Donghu is highest in summer and lowest in winter. To further detect the driving factors of eutrophication in study lakes, the Pearson correlation and multiple linear regression analyses were conducted. The results show that sunshine and temperature are, respectively, the most and the second most significant factors for Lake Dianchi with explanations of 14.8% and 22.0%; temperature and pollution are the main influencing factors for Lake Donghu (39.2% and 10.9% explanation, respectively) and Chaohu (57.2% and 60.7% explanations, respectively). In addition, the wind is another negatively significant factor for Lake Chaohu with an explanation of 31.3%. Our results serve as an example for other lakes in the Yangtze River Basin and support the formulation of effective strategies to reduce seasonal eutrophication.

[Risk Ranking of Endocrine Disrupting Compounds, Pharmaceuticals, and Personal Care Products in the Aquatic Environment of the Yangtze River Basin]

Endocrine disrupting compounds (EDCs), pharmaceuticals, and personal care products (PPCPs) have been of great concern as emerging contaminants of aquatic environments. In this study, the risks of EDCs and PPCPs in the Yangtze River Basin were ranked, based on their environmental exposure datasets and ecotoxicity datasets. The prioritized chemicals were then identified. The results found that EDCs and personal care products were deemed to represent higher risks to aquatic organisms, for example, estrone, estriol, 17β-estradiol, bisphenol S, atrazine, triclocarban, and triclosan, while the risks of pharmaceuticals were 500-fold lower. Among the pharmaceuticals, antibiotics posed relatively higher risks. The Xiangjiang River and Honghu Lake with its surrounding rivers were hotspots where more chemicals were found with the highest concentrations, followed by Taihu Lake, Dongting Lake and the Yangtze River Delta. When comparing with algae and worms, fish were the most sensitive taxa to 17β-estradiol and 17α-ethynylestradiol. The results of this work provide sound guidance for the future monitoring and management of chemicals in China.

Evaluation of GRACE mascon solutions using in-situ geodetic data: The case of hydrologic-induced crust displacement in the Yangtze River Basin

Since the Gravity Recovery and Climate Experiment (GRACE) satellite mission was started in 2002, a variety of spatial products have been made available to further understanding of mass redistribution in the Earth system. Two such mascon (mass concentration) solutions were developed by the Center for Space Research (CSR-M) and the NASA Jet Propulsion Laboratory (JPL-M), which offers significantly improved spatial localization and more accurate amplitude measurements of changes in recovered terrestrial Total Water Storage (TWS). However, it is difficult to validate GRACE-derived TWS mascons due to the lack of independent measurements of water storage in various forms at larger scales.In this study, we present a simple framework to evaluate GRACE mascon products based on in-situ GPS measurements from the Yangtze River Basin (YRB) in China. We found that the mascons show a more pronounced spatial difference in TWS distribution and highlight more details as compared to smoother results from empirical post-processing filtering applied to spherical harmonics (SH) data. The prediction of vertical displacements from CSR-M and JLP-M is closer to GPS than that from SH. The residual analysis showed the reductions in WRMS (weighted root-mean-squares) from the GPS minus the CSR-M average were greater than those for JPL-M in 41 GPS stations, and the scaling factors from CLM4.0 used in JPL-M-sf had few improvements with respect to agreement with GPS measurements. Our findings indicated CSR-M solutions were more consistent with in-situ observations and more in line with actual surface mass transport in the YRB. These findings also suggested that when using GRACE mascons to detect local TWS changes or when combining GRACE-derived data with GPS-observed displacement to estimate crustal response to loadings, users should note the contributions from effects of load signal sources from atmospheric, non-tidal ocean, and difference sensitivity kernels on differences between TWS from satellite-based and in-situ observations.

Atmospheric Pollution Mapping of the Yangtze River Basin: An AQI-based Weighted Co-word Analysis

The purpose of this paper is to analyze the characteristics and human effects of atmospheric pollution in the Yangtze River Basin (YRB). An AQI(Air Quality Index)-based weighted co-word method is applied to explore the characteristics of keywords taken from the data, using authoritative media sources and government reports. Hierarchical clustering techniques are utilized to classify and visualize the keywords and display the different types of incidents. The results reveal the following four main clusters: enterprise pollution, coal-burning pollution, traffic pollution, and air pollutants. Cluster 1 is divided into 7 sub-clusters to offer powerful insight into the structural characteristics of industrial activities. This study is one of the first attempts to use a bibliometric approach to visualize the underlying and interconnected sub-clusters from grey data. It also provides an atmospheric pollution mapping for formulating government policies by understanding the human effects of air pollution incidents.

Study on the Livelihood Vulnerability and Compensation Standard of Employees in Relocation Enterprises: A Case of Chemical Enterprises in the Yangtze River Basin

The relocation of chemical enterprises along the Yangtze River a necessary means of ecological protection in the Yangtze River Basin. Vulnerability assessment provides a new idea for the study of livelihood ability and compensation standard of employees after relocation. Based on the framework of "Exposure-Sensitivity-Adaptability" proposed by the Intergovernmental Panel on Climate Change (IPCC) and the survey data of 410 employees of relocation enterprises in the Hubei Province of the Yangtze River Basin, this study firstly constructs a livelihood vulnerability evaluation index system and evaluation model, and analyzes whether the employees of relocation enterprises have the ability to cope with the risk impact brought by the Yangtze River Ecological Restoration policy. Then, we use multiple linear regression model to explore the relationship between the group's exposure, sensitivity, adaptability and livelihood vulnerability. Finally, we design a new compensation standard calculation method for special groups from the perspective of social cost, to alleviate their livelihood vulnerability and provide a theoretical basis and decision support for the government and enterprises to formulate and implement relevant resettlement standards. The results show that: (1) employees of all ages show a certain degree of vulnerability in their livelihood; (2) there are differences in livelihood vulnerability between male and female employees; (3) compared with other positions, the livelihood vulnerability of producers is relatively high, and the vulnerability index is unevenly distributed and internally differentiated; (4) a low family burden ratio, high education, convenient living conditions and complex social network can effectively reduce the vulnerability of employees' livelihood; (5) the key obstacle factors affecting the sustainable livelihood of families are living convenience, adaptability to relocation, policy understanding, children's burden ratio, education, and annual income per capita; (6) the alternative opportunity cost method can be used as the basis to determine the compensation standard of the relocated employees, which can better reflect the compensation effect of the opportunity cost in the existing definition of international compensation mechanisms and realize the leap from concept to action.

Relationship between Air Pollution and Urban Forms: Evidence from Prefecture-Level Cities of the Yangtze River Basin

Urban forms, such as size, shape, density, compactness, and fragmentation, are associated with local air pollution concentrations. However, empirical analyses on how urban form improves or degrades urban air quality are still limited and inconclusive, especially for those rapidly expanding cities in developing countries. In this study, by using the improved STIRPAT (stochastic impacts by regression on population, affluence, and technology) model, the quantitative impact of urban form on near-surface PM_2.5 and NO₂ concentrations was identified in the 10 prefecture-level cities of the Yangtze River Basin (YRB) from 2000 to 2013. Trend analyses showed a significant increasing trend in both PM_2.5 (9.69 × 10⁻⁴ µg·m⁻³·year⁻¹) and NO₂ (1.73 × 10⁻⁴ ppb·year⁻¹) for the whole study period. Notably, a turning point of PM_2.5 from increasing to decreasing trends occurred around 2007. In addition, both pollutants showed a spatial agglomeration. The STIRPAT model demonstrated that socioeconomic, transportation and urban form factors played an important role in alleviating the increase of PM_2.5 and NO₂. In particular, a 1% decrease in urban extent density (UED) significantly increased NO₂ by 0.203%, but reduced PM_2.5 by 0.033%. The proximity index (PI) measured as a city’s compactness was significantly negatively correlated with PM_2.5 and NO₂. Conversely, a significant positive relationship of PM_2.5 and NO₂ concentrations against the openness index (OI) was observed, an important variable for measuring a city’s fragmentation. In addition, the environmental Kuznets curve (EKC) hypothesis between per capita GDP and PM_2.5 concentration was confirmed but failed in NO₂. Overall, this study encouraged a less fragmented and more compact urban form, which helped alleviate local air pollution concentrations by enhancing urban connectivity, reducing vehicle dependence, and facilitating the use of bicycles and walking.

Improved Remotely Sensed Total Basin Discharge and Its Seasonal Error Characterization in the Yangtze River Basin

Total basin discharge is a critical component for the understanding of surface water exchange at the land-ocean interface. A continuous decline in the number of global hydrological stations over the past fifteen years has promoted the estimation of total basin discharge using remote sensing. Previous remotely sensed total basin discharge of the Yangtze River basin, expressed in terms of runoff, was estimated via the water balance equation, using a combination of remote sensing and modeled data products of various qualities. Nevertheless, the modeled data products are presented with large uncertainties and the seasonal error characteristics of the remotely sensed total basin discharge have rarely been investigated. In this study, we conducted total basin discharge estimation of the Yangtze River Basin, based purely on remotely sensed data. This estimation considered the period between January 2003 and December 2012 at a monthly temporal scale and was based on precipitation data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite, evapotranspiration data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, and terrestrial water storage data collected from the Gravity Recovery and Climate Experiment (GRACE) satellite. A seasonal accuracy assessment was performed to detect poor performances and highlight any deficiencies in the modeled data products derived from the discharge estimation. Comparison of our estimated runoff results based purely on remotely sensed data, and the most accurate results of a previous study against the observed runoff revealed a Pearson correlation coefficient (PCC) of 0.89 and 0.74, and a root-mean-square error (RMSE) of 11.69 mm/month and 14.30 mm/month, respectively. We identified some deficiencies in capturing the maximum and the minimum of runoff rates during both summer and winter, due to an underestimation and overestimation of evapotranspiration, respectively.

[Measures and achievements of schistosomiasis control in the Yangtze River Basin]

This paper reviewed the prevention and control of schistosomiasis in the Yangtze River Basin in three stages, centered on the measures and achievements. It pointed out the key work of prevention and control which are infectious source control and effective surveillance at present stage. It will be beneficial to schistosomiasis control in China.

Seasonal microbial variation accounts for arsenic dynamics in shallow alluvial aquifer systems

Determining the temporal variation of microbial communities in groundwater systems is essential to improve our understanding of hydrochemical dynamics in aquifers, particularly as it relates to the fate of redox-sensitive contaminants like arsenic (As). Therefore, a high-resolution hydrobiogeochemical investigation was conducted in the As-affected alluvial aquifer systems of the Jianghan Plain. In two 25 m-deep monitoring wells, the seasonal variation in the composition of groundwater microbial communities was positively correlated with the change in groundwater level (R = 0.47 and 0.39 in NH03B and NH05B, respectively, P <  0.01), implying that the latter could be a primary driver of the seasonal microbial dynamics. In response to the fluctuating groundwater level, iron (Fe) reducers within the Desulfuromonadales were dominant (9.9 ± 4.7% among different sampling sites) in groundwater microbial communities during the monsoon season and associated with high concentrations of Fe(II) and As, while the predominance (16.7 ± 15.2% among different sampling sites) of iron-oxidizers the Gallionellaceae was accompanied by low Fe(II) and As in the non-monsoon season. These results suggest that microbially-mediated iron reduction/oxidation may have governed the seasonal mobilization/scavenging of As in groundwater. Our results provide new insights into mechanisms responsible for seasonal variations in groundwater As concentrations in similar aquifer systems.

Comparison of drought indices in the analysis of spatial and temporal changes of climatic drought events in a basin

The standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI) based on two different methods were calculated using monthly meteorological data from the Yangtze River Basin. According to the completeness and length of dataset, the monthly data of 35 meteorological stations from 1959 to 2017 were applied in this study. The results revealed that the SPEI calculated by the Penman-Monteith (PM) method performed better than the SPI and the SPEI based on the Thornthwaite (TH) method. Since SPEI_PM considered more meteorological factors and detailed physical processes, it obtained the most reasonable and accurate results of drought trends. Using the variations of SPEI_PM to analyze the decadal changes of drought characteristics in the basin, it could be found that 1980-1989 and 1990-1999 were the most humid periods in the basin, while the drought events became more frequent and severe in the recent decade. The spatial distributions of drought trend, duration and frequency indicated that the stations located in the midstream of the river were most prone to drought events, followed by the upper reaches. Our results provided more information for the regions where severe droughts occurred frequently and last longer, and more attention should be paid to these regions in future catchment management.