Huaihe River Research Articles

Health risk assessment of heavy metals and metalloid in drinking water in a region of Huaihe River Basin from 2015 to 2019

To evaluate the chronic health risk of heavy metals and metalloid in drinking water through oral ingestion in a typical area. Monitoring data of seven heavy metals and metalloid elements(Hg, As, Pb, Ni, Mn, Cr~(6+) and Cd) in drinking water in a typical area of Huaihe River Basin were collected from 2015 to 2019. The health risks of heavy metals and metalloid in drinking water in the area were assessed using the classic four-step health risk assessment model. The average concentrations of Hg, As, Pb, Ni, Mn, Cr~(6+) and Cd in drinking water in the typical area of Huaihe River Basin were(0.13±0.45), (0.49±0.49), (0.34±0.99), (1.10±2.49), (32.29±126.64), (2.13±0.50) and(0.03±0.04) μg/L, respectively. In which, Hg, Mn and Ni exceeded the limit of the Standard for Drinking Water(GB 5749-2006), the exceedance rates were 2.14%, 6.79% and 0.3%, respectively, and the maximum exceedance times were 2.61, 8.90 and 0.34, respectively. The chronic non-carcinogenic risks of Hg, As, Pb, Ni, Mn, Cr~(6+) and Cd were 1.32×10~(-2), 4.99×10~(-2), 2.97×10~(-3), 1.68×10~(-3), 7.04×10~(-3), 2.17×10~(-2) and 1.83×10~(-3), respectively. The carcinogenic risks of As, Pb, Cr~(6+) and Cd were 2.24×10~(-5), 8.82×10~(-8), 3.25×10~(-5) and 5.86×10~(-7), respectively. Hg, Mn and Ni in drinking water exceeded the standard in a typical area of Huaihe River Basin from 2015 to 2019. The chronic non-carcinogenic risks of Hg, As and other 7 heavy metals and metalloid are at an acceptable level(HQ≤1), while As and Cr~(6+) have certain carcinogenic risks(10~(-6)≤CR≤10~(-4)).

The Rise and Fall of the Imperial Capital and the Huaihe River Basin Haunted with Totalitarian Dream

The Rise and Fall of the Imperial Capital and the Huaihe River Basin Haunted with Totalitarian Dream

Utilizing Entropy-Based Method for Rainfall Network Design in Huaihe River Basin, China

The nonstationary characteristics caused by significant variation in hydrometeorological series in the context of climate change inevitably have a certain impact on the selection of an optimal gauging network. This study proposes an entropy-based, multi-objective, rain gauge network optimization method to facilitate the design of a 43 stations-based network in Huaihe River Basin (HRB), China. The first goal of this study is to improve the accuracy of gauge-related information estimation through the selection and comparison of discretization methods. The second goal of this study is to quantify the impact of trend-caused nonstationarity on optimal network design using the sliding window method. This study compares the divergence of three kinds of discretization methods, including the floor function-based approach, Scott’s equal bin width histogram (EWH-Sc) approach, and Sturges’s equal bin width histogram (EWH-St) approach. The matching degree of the variance and marginal entropy of the observed series is computed to select the most suitable of the above three discretization methods. The trend-caused nonstationarity in 75% of all stations in the HRB could definitely influence the final results of the optimal rain-gauge network design using the sliding window method. Therefore, in future studies of rain-gauge network optimization, it is necessary to carry out uncertainty research according to local conditions in view of climate change and human activities.

Combined Impacts of the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation on Summer Precipitation in Eastern China During the Medieval Climate Anomaly and Little Ice Age

AbstractWe investigate the joint effects of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) on eastern China summer precipitation (ECSP) during two typical periods in the last millennium [i.e., the Medieval Climate Anomaly (MCA) and the Little Ice Age (LIA)] using simulations from five selected climate models. The multimodel mean indicates that the ECSP anomalies under the four combined AMO and PDO phases differ between the MCA and the LIA. During the MCA, the meridional wave train induced by the PDO‐related convective heating over the northwestern Pacific is dominant and the zonal wave train related to the AMO is secondary. Independent of the AMO phase, deficient precipitation appears over South China in both PDO+ phases and vice versa. Meanwhile, most areas north of the Yangtze River valley feature positive anomalies in the PDO+/AMO+ phase but deficits in the PDO+/AMO− phase. In comparison, the Huanghe‐Huaihe River valley and southern Northeast China receive excessive and deficient precipitation in the PDO−/AMO+ and PDO−/AMO− phases, respectively. During the LIA, the zonal wave train induced by the AMO locates more southeastward than that during the MCA and has an overwhelming impact on the ECSP. Specifically, regardless of the PDO phase, excessive ECSP exists over Northeast China and South China in both AMO+ phases and vice versa. Moreover, precipitation between the two regions is excessive when the PDO is in phase with the AMO but deficient when they are out of phase.

How to Rebalance the Land-Use Structure after Large Infrastructure Construction? From the Perspective of Government Attention Evolution

Large infrastructure projects play a crucial role in regional development but can also negatively impact cultivated-land protection. This study focuses on the role of local governments in land-use conflicts and the rebalancing of land-use structures during large infrastructure construction. Using the construction of a reservoir in the Huaihe River as a case study, the research examines the evolution of government attention and the process of township local governments promoting land-use adjustment. The findings reveal that local governments go through a process of “Create–Reinforce–Adjust–Delivery” in their attention to reservoir construction to maximize their interests. Attention fluctuates in terms of reservoir construction, cultivated-land protection, and immigration-development assistance. Biased land-use decisions were made at different stages, leading to four stages of rebalancing efforts: “Generation–Challenge–Marked effect–Continuous negative impact”. This process provides insights into land-use decision-making and the rebalancing of land-use structure. The study suggests that the superior government should guide local governments to enhance attention to cultivated-land protection through laws and policies, while local governments should focus on the quality protection of cultivated land and mitigate the negative impact of rebalancing efforts.

High-Resolution National-Scale Mapping of Paddy Rice Based on Sentinel-1/2 Data

Rice has always been one of the major food sources for human beings, and the monitoring and planning of cultivation areas to maintain food security and achieve sustainable development is critical for this crop. Traditional manual ground survey methods have been recognized as being laborious, while remote-sensing technology can perform the accurate mapping of paddy rice due to its unique data acquisition capabilities. The recently emerged Google Earth Engine (GEE) cloud-computing platform was found to be capable of storing and computing the resources required for the rapid processing of massive quantities of remote-sensing data, thereby revolutionizing traditional analysis patterns and offering unique advantages for large-scale crop mapping. Since the phenology of paddy rice depends on local climatic conditions, and considering the vast expanse of China with its outstanding geospatial heterogeneity, a zoning strategy was proposed in this study to separate the monsoon climate zone of China into two regions based on the Qinling Mountain–Huaihe River Line (Q-H Line), while discrepant basic data and algorithms have been adopted to separately map mid-season rice nationwide. For the northern regions, optical indices have been calculated based on Sentinel-2 images, growth spectral profiles have been constructed to identify phenological periods, and rice was mapped using One-Class Support Vector Machine (OCSVM); for the southern regions, microwave sequences have been constructed based on Sentinel-1 images, and rice was mapped using Random Forest (RF). By applying this methodological system, mid-season rice at 10 m spatial resolution was mapped on the GEE for the entire Chinese monsoon region in 2021. According to the accuracy evaluation coefficients and publicly released local statistical yearbook data, the relative error of the mapped areas in each province was limited to 10%, and the overall accuracy exceeded 85%. The results could indicate that mid-season rice can be mapped more accurately and efficiently on a China-wide scale with relatively few samples based on the proposed zoning strategy and mapping methods. By adjusting the parameters, the time interval for mapping could also be further extended. The powerful cloud-computing competence of the GEE platform was used to map rice on a large spatial scale, and the results can help governments to ascertain the distribution of mid-season rice across the country in a short-term period, which would be well suited to meeting the increasingly efficient and fine-grained decision-making and management requirements.

Evaluation of Cloud Water Resources in the Huaihe River Basin Based on ERA5 Data

High-resolution reanalysis data are an effective way to evaluate cloud water resources (CWRs). Based on ERA5 reanalysis data and gridded observed precipitation data, combined with the diagnostic quantification method of cloud water resource (CWR-DQ), we analyze and evaluate the CWRs and their distribution characteristics in the Huaihe River Basin from 2011 to 2021. Moreover, we compare and evaluate the CWRs of two typical precipitation processes in summer and winter. The results show that the annual total amount of atmospheric hydrometeor (GMh) in the Huaihe River Basin is approximately 1537.3 mm. The precipitation (Ps) is 963.5 mm, the cloud water resource (CWR) is 573.8 mm, and the precipitation efficiency of hydrometeor (PEh) is 62.4%. The CWR in the Huaihe River Basin shows a slow increasing trend from 2011 to 2021.The monthly variations in Ps, CWR, and PEh show a single peak distribution. The spatial horizontal distributions of the gross mass of water vapor (GMv), GMh, and Ps in the Huaihe River Basin are zonal, and the values decrease with increasing latitude. In summer, the hydrometeors are mainly distributed in the middle layer (between 600 and 350 hPa). The hydrometeors in spring, autumn, and winter are mainly below 500 hPa. Two cases reveal that GMv, the condensation from water vapor to hydrometeors (Cvh), GMh, Ps, and PEh in the summer case are significantly higher compared to those in the winter case, while the CWRs are similar. The results are helpful for proposing rational suggestions for the Huaihe River Basin and to provide some beneficial reference for the development of CWRs.

Projections of flood regime changes over the upper-middle Huaihe River Basin in China based on CMIP6 models

Introduction: Climate change alters the hydrological cycle to different extents, in particular the intensification of extreme precipitation and floods, which has garnered more attention as a significant scientific issue in the last few decades. The last Coupled Model Inter-comparison Project 6 (CMIP6) was designed with new shared socioeconomic pathways (SSPs) to combine socioeconomic development with greenhouse gas emissions to project future climate.Method: In this study, we used 22 global climate models (GCMs) from CMIP6 to investigate future variations in extreme precipitation and temperature under SSP2-4.5 and SSP5-8.5 scenarios over the upper-middle Huaihe River Basin (UMHRB). Then, the modified Xinanjiang model integrating the flood control module was driven to obtain projections of the daily streamflow and to evaluate the future variations in flood regimes.Results: The results show that 1) the characteristics of future extreme precipitation, such as the average intensity and amount of annual precipitation and extreme precipitation, are projected to increase, and the average, maximum, and minimum temperature values also display substantial increasing trends in the future over the UMHRB; 2) warmer climate will lead to a more severe flood magnitude under the SSP5-8.5 scenario in the far future (2071–2100) over the UMHRB. The results of the multi-model ensemble show that the annual maximum flood peaks (15-day flood volumes) of Wangjiaba and Wujiadu stations are projected to increase by 46.4% (43.1%) and 45.4% (51.1%), respectively, in the far future (2071–2100) under the SSP5-8.5 scenario; and 3) variations in the flood frequency tend to resemble variations in flood magnitude, and the return period of the design flood will obviously decrease under future climate scenarios. For instance, in the far future, under SSP5-8.5 scenarios, the return period of the design flood with a 100-year return period will become 38 years and 31 years for Wangjiaba and Wujiadu stations, respectively.Discussion: The study enhances a more realistic understanding that the occurrence of future extreme precipitation and floods is projected to be more frequent and severe, thereby resulting in an urgent imperative to develop pertinent adaptation strategies to enhance social resilience toward the warming climate.

High phytoplankton diversity in eutrophic states impedes lake recovery

AbstractAimThe widely observed positive response of productivity to biodiversity, known as the biodiversity‐productivity relationship (BPR), underpins nature‐based solutions for mitigating and adapting to global changes. Little is known of the role of such emergent processes in the restoration of damaged ecosystems. Here, we test for evidence of a BPR in degraded freshwater lakes, and its role in underpinning or undermining lake recovery from eutrophic states.LocationLower Yangtze and Huaihe river basins, China, East Asia.TaxaFreshwater phytoplankton; also macrophytes, fish, zooplankton and zoobenthos.MethodsA systematic review of biodiversity studies was conducted to enumerate freshwater biodiversity change during eutrophication, encompassing 572 samples from 155 lakes in East China. Empirical samples were then taken of 93 phytoplankton communities from 38 lakes in ecologically degraded states of eutrophication. Samples were analysed for niche overlap in relation to biodiversity and productivity, and metrics of network structure indicative of community stability.ResultsReviewed publications on eutrophication in East China lakes revealed losses in biodiversity of macrophytes, fishes, zooplankton and zoobenthos but not phytoplankton. Empirically sampled eutrophic lakes maintained high phytoplankton biodiversity through niche differentiation, and phytoplankton biodiversity correlated positively with biomass, in line with the expectations of BPR.ConclusionsThe positive effect of biodiversity on phytoplankton productivity in eutrophic lakes acts in opposition to the negative impacts on productivity induced by eutrophication‐management strategies of nutrient suppression. In degraded systems, the BPR contributes to sustaining productivity of lake phytoplankton communities, impeding recovery from a eutrophic state. This is a case of the BPR playing an undesirable role at the ecosystem level. Lake recovery programmes need to anticipate that the control of phytoplankton biomass will depend on reducing nutrients to a level sufficient to degrade the internal structure of the phytoplankton community.

Molecular Signatures of Dissolved Organic Matter in the Central Huaihe River and Its Tributaries

Molecular Signatures of Dissolved Organic Matter in the Central Huaihe River and Its Tributaries

Development of a Middle–Late Holocene subaqueous clinoform in the northern Jiangsu coastal zone, western South Yellow Sea

The northern Jiangsu coastal zone (NJCZ) is part of the western coast of the South Yellow Sea and is located between the mouths of the Yellow and Yangtze rivers. The two rivers and the Huaihe River have discharged into the NJCZ at various times during the Holocene. As a result, multi-stage deltas and clinoforms have developed in the NJCZ, including the old Yellow River delta (OYRD) (1128–1855 CE). An old clinoform has recently been identified just below the OYRD, but its age and origin are uncertain because of limited data. In this study, integrated analyses of a new borehole core SYS-1601 penetrating the clinoform were conducted to document the evolution of the NJCZ and to provide a study case for other coastal regions influenced by major river systems and complex hydrodynamic conditions. Analyses included accelerator mass spectrometry (AMS) 14C and optically stimulated luminescence (OSL) dating, measurements of grain size and Sr-Nd isotopes, and identification of benthic foraminifera and ostracoda. Results show that the evolution of the subaqueous clinoform prior to the development of the OYRD in the western South Yellow Sea was concurrent with and genetically linked to the formation of the Huaihe delta on the NJCZ. The clinoform started to form at the same time as the Middle Holocene maximum flooding of the NJCZ at ∼7.0 ka. Cross-shelf progradation of the clinoform was coeval with progradation of the Huaihe delta and terminated at 1128 CE, when the Yellow River changed course and started to discharge off the Jiangsu coast to form the OYRD. The clinoform exhibits an overall coarsening-upward succession, comprising clayey silt and silt in the lower part grading upwards into silt and sandy silt, and its sediment was sourced largely from the Huaihe and Yangtze rivers. During the development of the clinoform from ∼7.0 ka to 1128 CE, the Yellow River did not flow into the South Yellow Sea through the Jiangsu coast for a sufficiently long time to contribute a substantial amount of sediment to the formation of the clinoform. The initiation and evolution of the clinoform were controlled mainly by complex interactions of dynamic processes, geomorphological conditions, and sediment supply into the western South Yellow Sea during the Middle–Late Holocene.

Application of the multimedia fugacity model in predicting the environmental behaviors of PCBs: Based on field measurements and level III fugacity model simulation

The comprehensive understanding of PCBs' fate has been impeded by the lack of simultaneous monitoring of PCBs in multiple environmental media in the background areas, which were considered long-term sinks for highly chlorinated PCBs. To address this gap, this study analyzed soils, willow tree barks, water, suspended particulate matter (SPM), and sediment samples collected from the middle reach of the Huaihe River in China for 27 PCBs. The results showed that the levels of ∑27PCBs in the soils were comparable to or lower than the background values worldwide. There were no significant correlations between organic matter and ∑27PCB concentrations in the soils and sediments. Additionally, the contamination of dioxin-like PCBs in the aquatic environment of the study area deserves more attention than in the soils. Applying the level III fugacity model to PCB 52, 77, 101, and 114 revealed that the soil was the primary reservoir, and air-soil exchange was the dominant intermedia transfer process, followed by air-water exchange. Furthermore, simulated results of air-soil and air-water diffusion were compared with those calculated from the field concentrations to predict the potential environmental behaviors of PCBs. Results indicated that the studied river would be a "secondary source" for PCB 52, 77, and 101. However, PCB 52, 77, 101, and 114 would continue to transfer from the air to the soil. This study combines multimedia field measurements and the fugacity model, providing a novel approach to predicting the potential environmental behaviors of PCBs.

The Impact of Extreme Temperatures on Grain Production in the Huaihe River Basin

The Huaihe River Basin is an important major grain producing area in China, maintaining the stability of grain output is of great significance to food security. However, with global warming, the frequency of extreme temperature events has increased, and the frequent meteorological disasters have brought great challenges to the stable supply of food production. In this paper, the impact of extreme temperature on grain production in the Huaihe River Basin was analyzed by using the daily temperature and agricultural production related data of 28 prefecture-level cities in the Huaihe River Ecological Economic Belt from 2001 to 2020. The following conclusions are drawn: 1) The influence coefficient of extreme high temperature on grain production in the Huaihe River Basin is -0.021, extreme low temperature has no significant impact on food production. 2) The effects of extreme temperature on food production in different regions in the river basin were heterogeneous, but the overall impact was negative. The influence coefficients of extremely high temperature days on the eastern region and Midwest region were -0.035 and -0.052, respectively, while the influence coefficients of extremely low temperature days on the eastern region were -0.413. The results showed that the increase in the number of extremely high temperature days would reduce production in the eastern region andMidwest region of the basin, while the northern region was not significantly affected by extreme heat. The increase in the number of extremely low temperature days will reduce grain production in the eastern region, and the impact on the Midwest region and the northern region will not be significant. Based on the above conclusions, three suggestions are put forward to maintain the safety of food production in the Huaihe River Basin: 1) enhance the ability to detect climate change in the basin; 2) Protect the stability of grain cultivated land in the river basin; 3) Innovative breeding of climate-resilient food crop seeds.

A surrogate modeling method for distributed land surface hydrological models based on deep learning

Surrogate modelling methods have been used to estimate spatially distributed parameters of land surface hydrological models due to their computational efficiency. However, traditional surrogate techniques have trouble in modelling high-dimensional input–output maps. In addition, their applications to a distributed model over large spatial and temporal domains are very unlikely to produce consistent spatial pattern and dynamic relationship of model input and output, leading to unbalanced model performance across different spatiotemporal domains. To address these issues, we employ a deep autoregressive neural network to construct an accurate and reliable surrogate system of distributed dynamic model outputs. The network uses a deep convolutional encoder-decoder architecture to take full advantage of the deep convolutional layers in high-dimensional image processing and spatial feature extraction. Moreover, the autoregressive strategy makes the network good at handling dynamic relationship between the time-varying model input and output. We apply this deep learning (DL) network to building a surrogate model of the Variable Infiltration Capacity (VIC) model simulated soil moisture over the Huaihe river basin of China. The results show that the adopted deep autoregressive neural network can provide an accurate surrogate model of the high-dimensional dynamic relationship between 15 input fields and 1 output field, each covering 408 grids, over multiple years. This surrogate model significantly outperforms the popular long short-term memory (LSTM) model, achieving an average mean squared error (MSE) of 0.26 and an average R2 of 0.76 using the test datasets. The surrogate's MSE and R2 performance represents an average improvement of 43% and 33%, respectively, compared to the LSTM model. In addition, it shows better spatial performance than the LSTM model, demonstrating its superior performance in approximating spatial patterns of VIC simulated soil moisture. The accuracy of this surrogate method and its ability to handle high-dimensional data is promising for advancing parameter uncertainty quantification of distributed land surface hydrological models, which usually have high dimensionality due to the large number of variables involved, including distributed parameters, input forcing variables, and output variables.

Evolution and driving factors of ocean carbon emission efficiency: A novel perspective on regional differences

Existing studies on carbon emission efficiency seldom discuss ocean carbon emission efficiency, and few studies on ocean carbon emission efficiency hardly discuss its regional differences. To fill this research gap, this paper innovatively measures and evaluates the ocean carbon emission efficiency of 11 Chinese coastal provinces from 2001 to 2019 using the super-efficiency SBM-GML model, and empirically analyzes the dynamic link between ocean carbon emission efficiency, trade openness and financial development by constructing a PVAR model based on an endogeneity perspective. Meanwhile, another major innovation of this study is to divide China's 11 coastal provinces into two coastal areas, north and south, with the Huaihe River as the boundary, in order to investigate the regional heterogeneity of ocean carbon emission efficiency and its influencing factors. The results show that (i) China's average ocean carbon emission efficiency has improved significantly, which is mainly due to the driving effect of technological progress. (ii) China's ocean carbon emission efficiency generally presents a spatial pattern that is higher in the south and lower in the north. Technological progress is the main source of the improvement in ocean carbon emission efficiency in the two regions. (iii) Significant regional heterogeneity exists in the impact of trade openness and financial development on ocean carbon emission efficiency, that is, trade openness and financial development both promote and hinder ocean carbon emission efficiency in the southern region than in the northern region. Finally, targeted policy recommendations are proposed.

Contamination Characteristics and Risk Assessment of Polycyclic Aromatic Compounds in Surface Dust of Suntuan Mining Area in Huaibei

The Suntuan mining area of Huaibei is a typical coal resource mining base in the Huainan-Huaibei areas in North China. Previous environmental studies related to surface dust in coal mining areas mainly focused on heavy metals and water-soluble ions, with little research on polycyclic aromatic compounds (PACs). In this study, gas chromatography-triple tandem quadrupole mass spectrometry (GC-MS/MS) was used to determine the contents of 16 parent polycyclic aromatic hydrocarbons (16PAHs), alkyl polycyclic aromatic hydrocarbons (aPAHs), and some oxygenated polycyclic aromatic hydrocarbons (OPAHs) in surface dust from the Suntuan mining area and surrounding environment. The results showed that the ΣPACs concentration range of surface dust in the Suntuan mining area was 283.8-36852.5 μg·kg-1 (mean:4114.2 μg·kg-1). ΣaPAHs (mean:2593.8 μg·kg-1) was 2.4 times higher than Σ16PAHs (mean:1074.9 μg·kg-1), which was the main contributor to PAC pollution. The composition of 16PAHs and aPAHs in surface dust was dominated by low molecular polycyclic aromatic hydrocarbons. The average OPAH content was 445.6 μg·kg-1. At the same time, PAC pollution was mainly concentrated around the mining area and near the road of a coal gangue landfill. Based on the positive matrix factor (PMF) analysis, it was inferred that the study area was mainly affected by petroleum sources, followed by coal and biomass combustion, and traffic sources and petroleum product leakage accounted for a relatively small proportion. Based on the ratio and distribution pattern of 16PAHs and aPAHs, it was inferred that when Σ16PAHs/ΣPACs<0.25, it was mainly polluted by the coal mining area. The results of PMF combined with lifetime carcinogenic risk (ILCR) showed that there were potential carcinogenic risks for children near the study area, mainly from coal and biomass burning and coal mining. There are many coal mining areas in Huaihe River Basin in China. The results of this study can provide reference for pollution prevention and control of PACs in these coal mining areas.

Occurrence time distribution fitting and encounter probability analysis of extreme precipitation in the Huaihe River Basin

Occurrence time distribution fitting and encounter probability analysis of extreme precipitation in the Huaihe River Basin

Research on watershed water ecological management and compensation based on evolutionary game

Abstract Ecological compensation is an effective way to alleviate watershed water ecological management. Considering the behavior of public participation, this paper constructs a tripartite evolutionary game model of the public, enterprises, and local governments, analyzes the evolutionary stability of the strategic choice of each participant, and discusses the influence of various factors on the strategic choice of the three parties. Combined with regional data, Matlab R2018b is used to simulate and analyze the evolution trend of each subject strategy in the Huaihe River Basin under different situations. The study found that: (1) The government's increase in rewards and punishments has significantly promoted public participation and enterprises' active governance of pollution, but increasing rewards and punishments are not conducive to local governments' own performance of regulatory responsibilities. (2) Increasing the amount of compensation and incentives is an effective way to promote public participation. (3) The sum of reputation gains, reputation losses, and rewards and punishments is greater than the difference between the additional benefits of negative governance and the cost of corporate governance, so as to ensure that enterprises actively control pollution.

A Method for Identifying the Dominant Meteorological Factors of Atmospheric Evaporative Demand in Mid‐Long Term

AbstractTo better understand the changes in the atmospheric evaporative demand (AED) in the context of global warming, the anomaly contribution analysis is presented to estimate mid‐long term contributions of meteorological factors to the AED. The Pearson correlation coefficient (RP) between the total contribution (ψ) of meteorological factors and the relative variation (ϕ) of the AED, and the Sen's trend slope (βS) of (ϕ, ψ) scatters are used to evaluate the applicability of the method. The smaller the values of |1 − RP| and |1 − βS|, the more applicable the method is. To validate the method, the reference crop evapotranspiration is employed as a proxy for the AED. The multi‐year contribution analysis is used as a comparison approach, which can only investigate the dominant meteorological factors of the AED in long term. Moreover, the Huaihe River basin of China is taken as a case study. Results show that (a) the values of |1 − RP| and |1 − βS| in mid‐long term are less than 0.1 in most cases when applying the anomaly contribution analysis, and the mid‐long term contribution processes of meteorological factors to the AED are clearly demonstrated; and (b) the wind speed and sunshine hours are the two most dominant factors (the total absolute contribution exceeds 60%) in long term, but they are not always the dominant factors in mid‐long term (e.g., wind speed in summer, and sunshine hours in winter). Therefore, the anomaly contribution analysis is a reasonable and effective method, which can help to gain insights into the changes in the AED.

Increasing riverine export of dissolved organic carbon from China.

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC ) and DOC concentrations (CDOC ) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC , as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001-2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2 , p = .01), but little change in CDOC (-0.001 mg/L/year, p > .10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p < .05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (-0.043 and -0.014 mg/L/year, p = .01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC , the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.