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Predicting flood event classes aids in the comprehensive investigation of flood behavior dynamics and supports flood early warning and emergency plan development. Existing studies have mainly focused on historical flood event classification and the prediction of flood hydrographs or certain metrics (e.g., magnitude and timing) but have not focused on predicting flood event classes. Our study proposes a new approach for predicting flood event classes based on the class membership functions of flood regime metrics and hydrological modeling. The approach is validated using 1446 unimpacted flood events in 68 headstream catchments widely distributed across China. The new approach performs well, with class hit rates of 68.3% ± 0.4% for all events; 65.8% ± 0.6%, 56.8% ± 0.9%, and 69.5% ± 0.9% for the small, moderate and high spike flood event classes, respectively; and 82.5% ± 1.2% and 75.4% ± 1.1% for the moderate and high dumpy flood event classes, respectively. Furthermore, it performs better in the basins of northern China than in those of southern China, particularly for the small spike flood event class in the Songliao and Yellow River Basins, with hit rates of 80.0% ± 3.2% and 78.8% ± 3.2%, respectively. Our results indicate that the new approach will help improve the prediction performance of flood events and their corresponding classes, and provide deep insights into the comprehensive dynamic patterns of flood events for early warning and control management. Plain Language Summary: The prediction of flood event classes is more effective and informative than that of individual events for obtaining comprehensive dynamic characteristics of flood events for early warning and development of emergency plans. However, this is challenging owing to massive flood events with remarkable spatiotemporal heterogeneity and unclear class membership functions. We propose a class prediction approach for flood events using the class membership functions of flood behavior metrics based on frequency analysis and catchment hydrological modeling. This approach deeply mines the behavior characteristics of historical flood events with a strong mathematical basis and cooperates with hydrological models to predict flood classes. Over thousand unimpacted flood events in 68 headstream catchments across China were selected to validate the robustness of the prediction scheme. Our results show that the proposed approach well predicts the flood class with class hit rates of 68.3% ± 0.4% for all events; 65.8% ± 0.6%, 56.8% ± 0.9%, and 69.5% ± 0.9% for the small, moderate and high spike flood event classes, respectively; and 82.5% ± 1.2% and 75.4% ± 1.1% for the moderate and high dumpy flood event classes, respectively. Our study has strong implications for scientific flood warning research and flood mitigation management. Key Points: A prediction approach for flood event classes is developed using class membership functions of flood regime metrics with hydrological modelClass membership degree is estimated using the frequency distribution function, which fits well with statistical significanceAverage class hit rates are 68.3% ± 0.4% for all the events and predictions of dumpy flood class are better than those of spike flood classes [ABSTRACT FROM AUTHOR]

Purpose: Soil macropores affect the proportion of rainfall infiltration and regulate the amount of water available to the plants on a field scale. However, the distribution of soil macropores and the effect on hydrologic and ecological regimes have been underestimated at a continental scale. The aim of this study was to investigate the relationships between soil properties and climatic factors on soil macropores and assess the eco-hydrological effect of soil macropores. Materials and methods: We hypothesized that the spatial distribution of soil macropores was controlled by soil properties and climatic factors at the continental scale. Using a spatial error-egression method, the soil effective porosity (EP) and residual effective porosity (REP) across China were calculated. The effects of soil macropores on soil physicochemical properties and climate factors were analyzed by the random forest model. The effect of macropores on soil water content (SWC) and normalized difference vegetation index (NDVI) was also analyzed. Results and discussion: The EP ranged from 0.06 to 0.35 cm3 cm−3 and was significantly related with soil chemical index, particularly, negatively correlated with cation exchange capacity (CEC) and total nitrogen (TN), but positively correlated with pH. There was a negative relationship between REP and mean annual precipitation in drylands. In humid regions, there was a positive relationship between REP and mean annual precipitation. Random forest model showed in humid region mean annual precipitation was more important than the annual temperature difference in explaining REP, but the results were reversed in drylands. The SWC and NDVI had different correlations with REP in drylands and humid regions. Conclusion: Soils with better quality had lower EP at the continental scale. Soil macropores were related simultaneously to precipitation and temperature conditions. Importantly, soil macropores were not conducive to soil water conservation and vegetation development in drylands. [ABSTRACT FROM AUTHOR]

Global warming and the rapid development of urbanization increase the likelihood of the occurrence of urban inundation, causing serious economic losses and threats to people's lives. Low impact development (LID) practices have attracted increasing attention as an effective approach which can mitigate urban inundation to some extent. Investigating the impact of LID practices on urban inundation is of significant importance to the prevention and control of urban flooding. This study constructed a coupling model with the combination of Storm Water Management Model and a 2D hydrodynamic model to provide a comprehensive simulation of urban inundation. The inundation situations are simulated with various scenarios by considering the implementation of LID practices under various rainfall return periods in Wuhan, China. We found that the LID practices can be more effective for urban inundation mitigation under rainfall events with smaller magnitude, and its ability in reducing the flood risk is weakened for extreme rainfall events. The results showed that LID practices can reduce the inundation area by 22.52%–38.9%. Especially for the inundation area with water depth larger than 0.4 m, the LID practices can reduce the inundation area by 71.52%–88.73% under different scenarios. Besides, the LID practices have a certain impact on the inundation area affecting traffic with a reduced rate of 37.2%–90.06%. This study can provide scientific support and a potential guiding significance for the future implementation of LID practices in cities under similar construction conditions. [ABSTRACT FROM AUTHOR]

During the past several decades, the carbon budget in the dryland ecosystem has experienced great variation under the joint impact of climate change and anthropogenic interference. How the net ecosystem productivity (NEP) responds to climate change and human interference in the Qilian Mountains (QLM), Northwest China, remains unclear. To fill these gaps, we first estimated the NEP in the QLM and then quantified the independent and interactive influences of natural environment factors, climatic factors, and human activity intensity on the NEP change from 2000 to 2020 by linking the Geodetector and structural equation models. The NEP of the QLM showed a significant increase during the recent 20 years, and 78.93% of the QLM experienced a significant increase in NEP; while only 4.83% of the area in the QLM experienced a decreasing trend, which is dominantly located on the southeast edge, surrounding the Qinghai Lake, and the midland of the QLM. The area percentage of the carbon sink region increased from 47% in 2000 to 62% in 2020. The natural environment factors (e.g., altitude and soil type) and climate factors (e.g., temperature and precipitation) were the dominant factors that determine the spatial distribution of NEP. Compared with a single factor, the interaction of pairs of factors enhanced the influence strength on NEP. The natural environment factors indirectly affected NEP change through influencing human activities intensity and climatic factors. Human activities intensity played a medium indirectly negative effect on NEP, while climatic factors exerted strong direct and indirect positive influences on NEP. The contributions of human activity intensity, climatic factors, and natural environment on NEP change in the QLM were 33.5%, 62.3%, and 38.3%, respectively. Overall, warming and wetting shifts in meteorological conditions offset the negative impact of human activities on NEP in the QLM, and the QLM has acted as a growing carbon sink in the past 20 years. [ABSTRACT FROM AUTHOR]

Oasis degradation and terminal lake shrinkage are prevalent consequences of the disputed distribution of water resources in inland river basins, hindering regional sustainable development. The Ecological Water Diversion Project (EWDP) is regarded as an important measure to restore the desert-oasis ecosystem in inland river basins, and thus it is essential to comprehensively evaluate the response of eco-hydrological and socioeconomic systems to the EWDP. Based on multiple indicators, we used trend analysis, linear regression, partial least square regression, and structural equation model to disentangle the quantitative effects of the EWDP on the change of eco-hydrological and socioeconomic conditions in the Ejina Oasis (EO) in the lower reaches of the Heihe River in northwest China. Our results indicate that the ecological deterioration was prevalent before the execution of the EWDP, including the increase of groundwater depth, the disappearance of lakes, the decrease of NDVI. After the EWDP, runoff released to EO increased 69.15%, the mean groundwater depth decreased 0.48 m, 52.28% of the study area showed a significant increase in NDVI, areas of forest and grassland increased 20.17 and 25.65 km2, respectively. The EWDP improved the hydrological regime and prompted the recovery of the oasis. Besides, socioeconomic development was facilitated under the restoration of the eco-hydrological conditions, characterized by the expansion of farmland and the thrive of the tourism industry. The hydrological variables promoted the improvement of the ecological condition with a direct strength of 0.93 and facilitated the development of the socioeconomic conditions in EO with an indirect strength of 0.84. Runoff was the most important positive contributor both to the NDVI and GDP in EO. This comprehensive evaluation framework can offer valuable insight for water resources management and sustainable development in the inland river basin of arid areas. [ABSTRACT FROM AUTHOR]

• A catchment plastic yield and transport model of multiple sources is proposed. • Model ensemble is adopted to estimate plastic sources and its uncertainty intervals. • The proposed model performs well for both plastic yield and outflow simulations. • Primary plastic sources are solid waste, agricultural film and impermeable surfaces. • Substantial plastic loads are retained in land system due to low loss coefficients. Plastic pollution has emerged as a global environmental concern, impacting both terrestrial and marine ecosystems. However, understanding of plastic sources and transport mechanism at the catchment scale remains limited. This study introduces a multi-source plastic yield and transport model, which integrates catchment economic activities, climate data, and hydrological processes. Model parameters were calibrated using a combination of field observations, existing literature, and statistical random sampling techniques. The model demonstrated robust performance in simulating both plastic yield and transport from 2010 to 2020 in the upper and middle Mulan River Catchment, located in southeast China. The annual average yield coefficients were found to closely align with existing estimations, and the riverine outflow exhibited a high correlation coefficient of 0.97, with biases ranging from -63.0 % to -21.4 % across all monitoring stations. The analysis reveals that, on average, 12.5 ± 2.5 % of the total plastic yield is transported to rivers annually, with solid waste identified as the primary source, accounting for 37.8 ± 20.7 % of the total load to rivers, followed by agricultural film (26.4 ± 9.8 %), impermeable surfaces (21.5 ± 10.3 %), urban and rural sewage (10.4 ± 5.0 % and 3.0 ± 1.5 %, respectively), and industrial wastewater (0.9 ± 0.7 %). The annual average outflow was estimated to between 9.3 and 43.0 ton/year (median: 23.1) at a 95 % confidence level. This study not only provides insights into the primary sources and transport pathways of plastic pollution at the catchment scale, but also offers a valuable tool for informing effective plastic pollution mitigation strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

Flash floods present significant heterogeneity over both space and time due to diverse topographic, geomorphologic, and hydro-meteorological conditions of catchments. Accurate identification and simulation of typical flash flood types are of great significance for the mitigation of flash flood disasters at the national scale. Three flood peak indices and dynamic indices were adopted to characterize the behavioral variability of flash floods. The typical flash flood types and corresponding behavior indices were identified and simulated using statistical analysis (i.e., principal component analysis, dynamic K-means clustering, and analysis of similarity) and hydrological modelling (i.e., HEC and XAJ models). There were 177 flash flood events at the hourly scale being selected for case study from eight catchments with various climatic and geographic characteristics. Results showed that all the flash flood events were clustered into three types (named Types 1, 2, and 3). Type 1 was characterized by low peak flow intensity, early flood peak occurrence time, and thin flood process with short duration. Type 2 was characterized by low peak flow intensity, late flood peak occurrence time, and flat flood process with long duration. Type 3 was characterized by high peak flow intensity and late flood peak occurrence time. Flash flood types showed high consistency with their influencing factors (e.g., catchment forest ratio and drainage area, occurrence time and magnitude of maximum storm intensity, and concentration of a storm event). The simulation performances were basically the same for HEC and XAJ models. As for flash flood event simulations, the average relative error varied from 23.25% to 27.98%, from 11.95% to 18.19%, and from 8.30% to 18.25% for Types 1, 2 and 3, respectively. The average Nash-Sutcliffe efficiency coefficient varied from 0.39 to 0.54, from 0.76 to 0.85, and from 0.86 to 0.91, respectively. As for the six flash flood behavior indices simulations, the average relative root-mean-square error (RMSEr) varied from 0.37 to 0.69, from 0.37 to 0.41, and from 0.18 to 0.25 for Types 1, 2, and 3, respectively. The average correlation coefficient (r) varied from 0.52 to 0.68, from 0.78 to 0.85, and from 0.88 to 0.94, respectively. The flood peak indices were the best simulated for Types 2 and 3 with RMSEr varying from 0.18 to 0.28 and r varying from 0.86 to 0.91. The flood dynamic indices were the best simulated for Type 3 with RMSEr varying from 0.19 to 0.21 and r varying from 0.91 to 0.97. The study provided detailed flood information supports for flood management at catchment scale, and also provided new insights into flash flood simulations in small and medium-sized catchments from perspective of flood behavioral processes. [ABSTRACT FROM AUTHOR]

Flash flood disaster ranks top among all the natural hazards across the world due to its high frequency, severity and fatality. However, flash flood simulation is still challenging in small and medium-sized catchments with complex orography, flashy hydrological responses and poor observations. Three distributed hydrological models, i.e., TOPModel, HEC and CNFF, are selected to simulate flash floods in seven humid and six semi-humid catchments in China, with consideration of water balance (RER), peak flow rate (REQ) and its occurrence time (TP), hydrograph variation (SNSE) and model uncertainty. Influences of five catchment attributes are further investigated on individual model performances. All three models perform satisfactorily in humid catchments, but less satisfactorily in semi-humid catchments. Water balance is well obtained by CNFF, followed by HEC and TOPModel. Peak flow rate and its occurrence time are most accurately captured by CNFF and HEC, respectively. Hydrograph variations are well reproduced by HEC and CNFF. TOPModel performs well for picking peak flow and hydrograph variation in humid catchments. Uncertainty interval is narrowest for HEC with average relative interval length at 95% confidence level being 0.78 ~ 2.53. Most observations are bracketed by uncertainty intervals for TOPModel (64.79% ~ 91.91% of total). Three model performance indices (i.e., RER, REQ, and SNSE) are mainly affected by drainage area and forest ratio across humid and semi-humid catchments, while TP performance is mainly affected by mean slope in humid catchments. [ABSTRACT FROM AUTHOR]

Epilithic algal community structure and function are important indicators of stream ecosystem health and are sensitive to ambient environmental changes. In this study, we examined the impact of light and nutrients on epilithic algal community structure and function by an in situ nutrient addition and shaded canopy experiment in subtropical streams in China. Epilithic algae structure, dominated by diatoms, was significantly different with nutrient addition and light reduction. Nutrient addition increased the epilithic algae and diatom density, colonial life-forms, planktonic diatoms, and high-profile diatoms but decreased the low-profile diatoms. The shaded canopy increased the low-profile diatoms but decreased the adnate life-forms, planktonic diatoms, and high-profile diatoms. Epilithic metabolism, including gross primary production (GPP), net daily metabolism (NDM), and production/respiration (P/R) increased with nutrient addition, while respiration (R) only increased when the canopy was open with nutrient addition. Epilithic GPP had a significant positive correlation with diatom density (P < 0.01, R2 = 0.9425). Our results indicated that changes in epilithic algae structure due to changes in riparian canopy coverage and nutrients could affect epilithic algal community function. Quantifying the impacts of such drivers on community structure and function is vital to effective river management. [ABSTRACT FROM AUTHOR]

[Display omitted] • Three NDVI vegetation correction schemes with CRNS were provided. • The ratio of parameter N 0 between different landscapes reached 1.42. • N 0 was negatively correlated with NDVI (y = 373.9 (x + 0.015)−0.136, R2 = 0.77) • Three methods reduced RMSE from 0.093 to 0.063, 0.054, and 0.032 g g−1, respectively. Cosmic-ray neutron sensors (CRNS) are a powerful tool for measuring soil moisture on a hectometer scale, and mobile cosmic-ray neutron technology holds significant importance for upscaling soil moisture. However, vegetation strongly affects with CRNS soil moisture measurements. Variations in vegetation over time change how the CRNS is affected, which is more challenging than a stable vegetation cover, particularly during CRNS roving, where one crosses many vegetation covers. To correct vegetation, we hypothesized that Normalized Difference Vegetation Index (NDVI) can represent vegetation hydrogen pools. From 2020 to 2023, at the 74 plots with varying vegetation cover near the Qilian Mountains, the experiments for soil moisture measurements were conducted in shrubs, forests, deserts, farmlands, and grasslands using a Cosmic-ray Neutron Rover. The measured neutron intensity clearly varied across different landscapes, and the calibrated parameter N 0 differed among 74 plots. The variations in vegetation cover resulted in low measurement accuracy for CRNS. All three NDVI vegetation correction methods (NDVI-θ NDVI method, NDVI-NDVI ave method, and NDVI-N 0 method) offered by the study could improve accuracy of soil moisture measurements. In the optimal NDVI-N 0 method, the relationship between NDVI and N 0 was established using a power function y = 373.9 (x + 0.015)−0.136 (R2 = 0.77), which had the capability to decrease the root mean square error between oven-dried and measured soil moisture from 0.093 to 0.032 g g−1 in our study area. Employing NDVI instead of biomass for CRNS vegetation correction can substantially reduce workload and effectively enhance CRNS soil moisture measurements, showing the potential for upscaling soil moisture. [ABSTRACT FROM AUTHOR]

The terrestrial water storage anomalies (TWSAs) in the Tarim River Basin (TRB) were investigated and the related factors of water variations in the mountain areas were analyzed based on Gravity Recovery and Climate Experiment (GRACE) data, in situ river discharge, and precipitation during the period of 2002–2015. The results showed that three obvious flood events in 2005, 2006, and 2010 resulted in significant water surplus, although TWSA decreased in the TRB during 2002–2015. However, while the significant water deficits in 2004, 2009, and 2011 were associated with obvious negative river discharge anomalies at the hydrological stations, the significant water deficits were not well consistent with the negative anomalies of precipitation. While the river discharge behaved with low correlations with TWSA, linear relationships between TWSA and climate indices were insignificant in the TRB from 2002 to 2015. The closest relationship was found between TWSA and Pacific Decadal Oscillation (PDO), with correlations of -0.56 and 0.58 during January 2010–December 2015 and during January 2006–December 2009, respectively. Meanwhile, the correlation coefficient between TWSA and El Niño-Southern Oscillation (ENSO) index in the period of April 2002–December 2005 was -0.25, which reached the significant level (p<0.05). [ABSTRACT FROM AUTHOR]

Waterlogging is one of the major water issues in most cities of China and directly restricts their urbanization processes. The construction of Sponge City is an effective approach to solving the urban water issues, particularly for the waterlogging. In this study, both the urban issues emerged at the stage of rapid urbanization in China and the demands as well as problems of Sponge City construction related with the water issues were investigated, and the opportunities and challenges for the Sponge City construction in the future were also proposed. It was found that the current stormwater management focused on the construction of gray infrastructures (e.g., drainage network and water tank) based on the fast discharge idea, which was costly and hard to catch up with the rapid expansion of city and its impervious surface, while green infrastructures (e.g., river, lake and wetland) were ignored. Moreover, the current construction of Sponge City was still limited to low impacted development (LID) approach which was concentrated on source control measures without consideration of the critical functions of surrounding landscapes (i.e., mountain, river, wetland, forest, farmland and lake), while application of the integrated urban water system approach and its supported technologies including municipal engineering, urban hydrology, environmental science, social science and ecoscape were relatively weak and needed to be improved. Besides, the lack of special Sponge City plan and demonstration area was also a considerable problem. In this paper, some perspectives on Good Sponge City Construction were proposed such as the point that idea of urban plan and construction should conform to the integral and systematic view of sustainable urban development. Therefore, both the basic theoretical research and the basic infrastructure construction such as monitoring system, drainage facility and demonstration area should be strengthened, meanwhile, the reformation and innovation in the urban water management system and the education system should also be urgently performed. The study was expected to provide a deeper thinking for the current Sponge City construction in China and to give some of suggestions for the future directions to urban plan and construction, as well as urban hydrology discipline. [ABSTRACT FROM AUTHOR]

Diffuse nutrient loss mechanism is complicated and shows remarkably regional differences due to spatial heterogeneities of underlying surface conditions, climate and agricultural practices. Moreover, current available observations are still hard to support the identification of impact factors due to different time or space steps. In this study, an integrated water system model (HEQM) was adopted to obtain the simulated loads of diffuse components (carriers: runoff and sediment; nutrient: total nitrogen (TN) and total phosphorous (TP)) with synchronous scales. Multivariable statistical analysis approaches (Analysis of Similarity and redundancy analysis) were used to assess the regional differences, and to identify impact factors as well as their contributions. Four catchments were selected as our study areas, i.e., Xiahui and Zhangjiafen Catchments of Miyun Basin in North China, Yuliang and Tunxi Catchments of Xin’anjiang Basin in South China. Results showed that the model performances of monthly processes were very good for runoff and good for sediment, TN and TP. The annual average coefficients of all the diffuse components in Xin’anjiang Basin were much greater than those in Miyun Basin, and showed significantly regional differences. All the selected impact factors interpreted 72.87–82.16% of the regional differences of carriers, and 62.72–71.62% of those of nutrient coefficients, respectively. For individual impact factor categories, the critical category was geography, followed by land-use/cover, carriers, climate, as well as soil and agricultural practices in Miyun Basin, or agricultural practices and soil in Xin’anjiang Basin. For individual factors, the critical factors were locations for the carrier regional differences, and carriers or chemical fertilizer for the nutrient regional differences. This study is expected to promote further applications of integrated water system model and multivariable statistical analysis in the diffuse nutrient studies, and provide a scientific support for the diffuse pollution control and management in China. [ABSTRACT FROM AUTHOR]

Summary The assessment of flow regime alterations is fundamental in understanding the potential impact of reservoirs and other water infrastructures on aquatic ecosystems and biota. Previously used methods to classify flow regimes have not captured temporal changes between unregulated and regulated flow regimes at individual stations. In this study, a combination of hierarchical classification and trend analysis was used to assess spatial and temporal flow regime alterations in the Huai River Basin, China. Two categories of flow regime indices were selected to characterize the impacts of reservoir and sluice regulation, including the basic flow indices for mean variation, and the cumulative variation indices for long-term alteration. The overall impact of reservoirs and sluices on flow regime included the decrease of high flow magnitudes but the increase of low flow magnitudes through time. Moreover, on average, the flow variability, and the high and low flow frequencies were reduced, while their durations were increased. Reservoirs had a greater impact on flow regimes than sluices. The flow regimes at 18 of 30 stations were altered significantly from a pre-regulation condition and were divided into three main types of alteration corresponding to operational rules of reservoirs and sluices. From a management perspective, water projects in China should address the environmental flow requirements of the rivers, particularly in terms of the hydrologic indices affected mostly by reservoirs and sluices. This study will promote the application of flow regime classification and river restoration in highly regulated basins in China. [ABSTRACT FROM AUTHOR]

Water and related environmental problems have become a key barrier to the sustainable development of China, where multiple uses of water and urban water management are two significant means to sustain urban development and the ecological restoration of rivers. A new assessment approach and water system model were developed to estimate eco-water or the volume of water essential for maintaining healthy and sustainable urban river ecosystems under various natural landscapes and water quality objectives. Moreover, multiple scenario analysis was adopted to explore the influences of water quality on eco-water management. The Yongding River in Beijing was selected as a case study. The results showed that the eco-water volume was 0.079, 0.073 and 0.067 billion m 3 /a under high, medium and low objectives without water quality requirements, and 0.112, 0.107 and 0.101 billion m 3 /a further considering water quality. The water residence times anticipated under each development scenario were 34.8, 37.5 and 41.5 d, which were 13.0%, 14.5% and 13.6% longer than those when water quality was considered. Better water quality could be achieved by implementing water diversions. The comprehensive implementation of water diversion projects could increase the rate of water discharge by 45.1%, decrease the permanganate concentration by 16.1%, and reduce the water residence time by 28.9% on average. This study is expected to provide scientific bases for good water governance, prepare healthy water systems for sustainable communities, and provide a reference case to achieve multiple uses of water for human uses and ecological river restoration in water short areas in developing countries. [ABSTRACT FROM AUTHOR]

The three rivers source region (TRSR) is the most sensitive region of global climate change in China. The temporal and spatial variations of main water balance components (precipitation, snowmelt, actual evaporation, runoff, etc.) during the period from 1960 to 2000 in the TRSR were analyzed by hydrologic simulation and statistical detection. The results showed that: when compared with the components in 1960s, (1) the variation of precipitation from 1970s to 1990s was not significant in the whole TRSR though it increased slightly in the Yellow River Source Region (YeSR) and Yangtze River Source Region (YaSR), but decreased slightly in the Lancang River Source Region (LcSR); (2) the snowmelt increased in most regions of TRSR except the downstream of YeSR and YaSR, but the trend was statistically significant only in the YeSR; (3) the actual evaporation increased continually in the whole TRSR, but the trends were significant in the middle stream of the YeSR and YaSR, and the YeSR was the greatest; (4) Although the runoff depth decreased gradually in the TRSR, the trends were significant only in the middle stream of the YeSR and YaSR and the YeSR was the greatest. Inevitably, the discharge decreased in the TRSR but the trend was not statistically significant. Climate change (i.e., the slightly decreasing of precipitation and the increasing of air temperature) was the most important factor to affect the variations of water balance components. The most sensitive region to climate change was YeSR, followed by YaSR, and the least one was LcSR. This study was expected to provide the foundation and a reference to analyze the water resources evolution and test the climate change impacts in TRSR as well as the whole China. [ABSTRACT FROM AUTHOR]

High regulation of dams or sluices disturbs flow regimes and pollutant transformation process significantly in most basins over the world. The water quality and quantity simulation in highly regulated river basins is always a very complicated task. The Huai River Basin is a typical area in China with the highest density of water projects and serious pollution problems simultaneously. In this paper, a procedure based on Soil and Water Assessment Tool (SWAT) was proposed to carry out the water quantity and quality simulation of Huai River Basin by incorporating the operation rules of dams or sluices into the reservoir regulation module. The water quality module in SWAT is extended to suit the actual situation of river basin in China. The results show that: for runoff simulation, 28 of all the 38 stations (73.7%) have the acceptable performance, with the average correlation coefficient and efficiency coefficient of 0.83 and 0.66, respectively in the calibration period. In the validation period, 17 of all the 34 stations (50%) have the acceptable performance, with the average correlation coefficient and efficiency coefficient of 0.77 and 0.54, respectively. The model performs the worst for reservoirs, little better for sluices and the best for unregulated stations. Comparing to the low flow and high flow simulation of original SWAT model, the low flow simulation of reservoirs and the high flow simulation of sluices are much better because of their different main purposes. For water quality simulation, the standard reaching rates of NH-N and COD are 55.9% (19/34) and 67.6% (23/34) respectively for all the stations, and the average relation coefficients are 0.46 and 0.48 respectively. Comparing with the results of original SWAT model, the improved model better reproduces the long-term water quantity and quality processes in the Huai River Basin of China. This study provides a new approach and reference to understand the variation of water quantity and quality in highly regulated river basin, and is expected as technical support for the environment restoration and integrated management in the basins, especially in China. [ABSTRACT FROM AUTHOR]

Climate change may significantly affect the hydrological cycle and water resource management, especially in arid and semi-arid regions. In this paper, output from the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model were used in conjunction with the Soil and Water Assessment Tool (SWAT) to analyse the effects of climate change on streamflow of the Xiying and Zamu rivers in the Shiyang River basin, an important arid region in northwest China. After SWAT model calibration and validation, streamflow in the Shiyang River Basin was simulated using the PRECIS climate model data for greenhouse gas emission scenarios A2 (high emission rate) and B2 (low emission rate) developed by Intergovernmental Panel on Climate Change. Monthly streamflow and hydrological extremes were compared for present-day years (1961-1990), the 2020s (2011-2040), 2050s (2041-2070) and 2080s (2071-2100). The results show that mean monthly streamflow in Shiyang River Basin generally increased in the 2020s, 2050s and 2080s between 0.7-6.1% at the Zamu gauging station and 0.1-4.8% at the Xiying gauging station. The monthly minimum streamflow increased persistently, but the maximum monthly streamflows increased in the 2020s and slightly decreased in the 2050s and 2080s. This study provides valuable information for guiding future water resource management in the Shiyang River Basin and other arid and semi-arid regions in China. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

• Budyko-based framework is improved for attribution of streamflow signature changes. • Streamflow signatures show clearly nonlinear relationships with climate variables. • Human activities play dominant roles in decreasing overall streamflow signatures. Streamflow has been complexly altered by climate change and human activities in major rivers worldwide. The traditional Darwinian approach for impact assessment of climate change and human activities mainly focuses on variations in annual streamflow, but ignores other critical streamflow characteristics (e.g., high- and low-flow signatures). In our study, seven streamflow metrics were adopted to characterize the main streamflow signatures including average, low and high flows, and the Budyko-based method was extended based on the derived differential equation of streamflow signature change to separate individual impacts of climate change and human activities. The Yellow River Basin, China was selected as the study area because of its high intensity of human activities, and daily runoff observation series from 1960 to 2015 at four stations from the source region to the downstream region were used for the assessment. The assessment results were also compared with those estimated by the hydrological modeling method for validation. The results show that all streamflow signatures at the four stations have evidently declined after the 1980s, particularly for high-flow magnitudes. Both climate change and human activities decrease most of streamflow signatures, and human activities play major roles, which are gradually enhanced from the source region to the downstream region. The contributions of human activities are from −66.85% to −56.68% in the Tangnaihai controlled catchment, from −96.93% to −54.59% in the Qingtongxia controlled catchment, from −83.61% to −57.49% in the Longmen controlled catchment, and from −91.02% to −57.29% in the Lijin controlled catchment. The most impacted signature is the average flow in the non-flood season, followed by the annual maximum flow. The estimated contributions of climate change and human activities match well with those estimated by the hydrological modeling method, particularly for the high- and average-flow signatures with contribution deviations less than 10%. However, the estimated contributions to the low-flow signatures are quite different likely due to large uncertainty of low flow estimation. This study is expected to provide insights into the streamflow variations basin wide and provide scientific foundations for ecological protection and high-quality development of the Yellow River Basin, China. [ABSTRACT FROM AUTHOR]

• Straw incorporation changed the N effects on soil bacterial community composition. • Straw incorporation enhanced the cellulolysis function and relevant taxa abundance. • N fertilization stimulated most of the C transformation and N cycling processes. • Reducing N fertilization will not change microbial taxa profiles and functions. • The abundance of copiotrophic taxa decreased at the mid-growing season. Integrating nitrogen (N) fertilization with crop residue amendments is usually used to enhance soil nutrient levels and promote crop growth in regions with intensive agriculture. However, the interactive effects of straw incorporation and N fertilization on the abiotic and biological properties of soil are not fully understood, especially under field conditions at different crop growth stages. In this study, we estimated the dynamic changes in the soil physicochemical properties and bacterial communities in response to N fertilization, straw incorporation, and their combinations during the maize growing season in black soil region in Harbin, China. N fertilization increased the relative abundance of the typical copiotrophic bacterial taxa, Alphaproteobacteria, but reduced that of the oligotrophic group, Acidobacteria. The straw incorporation enhanced the relative abundance of Bacteroidetes and Gammaproteobacteria, within which a variety of cellulolysis-related species phylogenetically fell. Interestingly, the straw amendments changed the effects of N fertilization on the overall soil bacterial community composition, possibly by altering the soil total carbon, C/N ratio, fixed ammonium, and moisture level. N fertilization stimulated most of the carbon (C) transformation and N cycling processes, and the straw incorporation increased the cellulolysis, N fixation, ureolysis, ammonia oxidation and denitrification functions. There were no differences in the soil chemical properties, microbial taxa profiles or predicted functions between the conventional N fertilizer usage (high N level) and the optimized N fertilization management scheme (low N level), irrespective of straw incorporation, implying that moderately reducing the usage of N fertilizer will not change the ecosystem service and function in this organic matter-rich black soil region. The relative abundance of the copiotrophic bacterial taxa decreased at the mid-growing season, which might be caused by the low soil C and N availability. In contrast, the oligotrophic bacterial groups showed predominance at the mid-growing season, which might aim to mineralize soil organic matter to meet the growth needs of both the crops and the microbes. The nitrifiers (Nitrospirae) and nitrification process were sharply activated at the mid-growing season, especially under the straw amendment condition, inferring that the combination of straw application with N fertilizer could serve as an effective measure for improving soil fertility in Northeast China. The present study enhanced our knowledge on the dynamic changes in soil biotic and abiotic parameters in response to straw incorporation and N fertilization during the maize growing season. Still, this study provides a reference for designing an environmentally friendly fertilization strategy that both alleviates environmental stress and maintains a high crop yield in Northeast China. [ABSTRACT FROM AUTHOR]

China's Sponge City initiative will involve widespread installation of new stormwater infrastructure including green roofs, permeable pavements and rain gardens in at least 30 cities. Hydrologic modelling can support the planning of Sponge Cities at the catchment scale, however, highly detailed spatial data for model input can be challenging to compile from the various authorities, or, if available, may not be sufficiently detailed or updated. Remote sensing methods show great promise for mitigating this challenge due to their ability to efficiently classify satellite images into categories relevant to a specific application. In this study Geographic Object Based Image Analysis (GEOBIA) was applied to WorldView-3 satellite imagery (2017) to create a detailed land cover map of an urban catchment area in Beijing. While land cover classification results based on a Bayesian machine learning classifier alone provided an overall land cover classification accuracy of 63%, the subsequent inclusion of a series of refining rules in combination with supplementary data (including elevation and parcel delineations), yielded the significantly improved overall accuracy of 76%. Results of the land cover classification highlight the limitations of automated classification based on satellite imagery alone and the value of supplementary data and additional rules to refine classification results. Catchment scale hydrologic modelling based on the generated land cover results indicated that 61 to 82% of rainfall volume could be captured for a range of 24 h design storms under varying degrees of Sponge City implementation. [ABSTRACT FROM AUTHOR]

Propagation from meteorological to hydrological drought events is crucial for understanding drought variation mechanisms and their consequences. Most previous studies were implemented using various standardized drought indices at month scale, which were difficult to reveal the physical processes and insufficient to characterize the comprehensive propagation characteristics (e.g., propagation time, duration, and severity) from meteorological to hydrological drought events. Furthermore, the impact mechanisms of underlying surfaces on drought propagation remained unclear. This study identified the paired relationships between meteorological and hydrological drought events and investigated their comprehensive propagation characteristics at the hydrologic response unit scale using the Soil and Water Assessment Tool (SWAT), run theory and paired analysis. The impact of underlying surfaces (e.g., land use, soil type, and slope) on drought propagation was further assessed using the Student's t -test at the 95% confident level. The upper middle Yuanjiang River Basin in China, which is prone to drought and exhibits diverse underlying surface conditions, was selected as the study area. Results indicate that the SWAT model optimally simulates the monthly streamflow with the Nash-Sutcliffe efficiency being ≥0.75 and the RMSE-observations standard deviation ratio being ≤0.50. Four main propagation types are identified, i.e., one-to-one, many-to-one, one-to-many, and many-to-many, in which the first two types are the dominant ones, accounting for 86.7% and 13.3% of total paired events, respectively. More than 85% of the study area exhibits a propagation time of ≤2 months, especially in the headwater area and the right bank of Lvzhijiang River. Drought duration and severity are amplified during the propagation process in 60.8% and 60.3% of the study area, respectively. Drought propagation time, duration, and severity are mainly controlled by soil and slope, and are slightly affected by land use type. The propagation time is quite short in areas with a high soil infiltration rate and steep slope, and the drought duration and severity are amplified in areas with a low soil infiltration rate and gentle slope. This study aims to provide deep insights on propagation from meteorological to hydrological drought considering various underlying surfaces, and further provides a scientific basis for the drought propagation mechanism and for drought disaster prevention and adaptation. • Drought propagation is analysed on time, duration, and severity by paired events. • Only 55% of meteorological drought events trigger hydrological drought events. • Areas with lower soil infiltration rates and gentler slopes show shorter duration and higher severity. • Drought propagation is impacted evidently by soil, followed by slope and land use. [ABSTRACT FROM AUTHOR]

China has begun a rapid move towards Sponge City implementation, which will include widespread installation of various Low Impact Development (LID) stormwater infrastructure. Ambitious goals have been set for all Sponge Cities, including a target capture rate of 80–85% of annual precipitation in Beijing. However, there has so far been limited investigation into whether these goals are obtainable at the catchment scale given the physical restrictions of the existing urban landscape. This paper demonstrates the use of long-term continuous hydrologic modelling to evaluate the potential of meeting rainfall capture goals over a long time period for a case study area in Beijing. Detailed land cover classification derived from satellite imagery aided in the parameterization of a SWMM (Stormwater Management Model) model representing a 133 km2 urban study area. The calibrated and validated model demonstrated satisfactory agreement between computed and observed runoff for a variety of precipitation events ranging from 10 to 207 mm. A synthetic high resolution rainfall time series was generated from historic daily observations then used as input to run the model continuously for a 35 year period. Feasible LID model scenarios based on varying degrees of implementation of rain gardens, permeable pavements and green roofs were compared in terms of their potential volume capture of annual rainfall. Modelling results demonstrated that the conversion of 30% of roof area to green roof, 10% of green areas to rain gardens and 35% of paved areas to permeable pavement could increase the baseline volume capture ratio from 59.9% to 82.2%, indicating that Sponge City goals can be met within the case study area with realistic levels of LID implementation. This study provides a decision-making basis for future planning in the study area. • Satellite imagery based hydrologic model shows good agreement with observed flows. • Continuous modelling approach suggested for evaluation of Volume Capture Ratio. • >80% of annual rainfall captured with moderate catchment wide implementation of LID. [ABSTRACT FROM AUTHOR]

• A BPROME method to quantify the impact of number of events on model performance and uncertainty is constructed. • A regular influence of the model uncertainty decreases and the model performance increases with the number of events increases. • At an appropriate range of numbers of events can achieve better parameter calibration effect of the model in data-scare areas. Rainfall-runoff data in drainage systems in urban areas is the essential input variable for urban hydrological modeling. Obtaining high quality and sufficient size of urban flood events is always difficult due to the inconvenient underground observation and the untimely capture of the rapid rising and recession stages of urban runoff. It largely constrains the efficiency of model calibration and brings large uncertainty in urban rainfall-runoff simulation. Therefore, the evaluation of the number of events' influence on model performance and uncertainty is of great significance, which can provide useful information to help the decision makers select sufficient useful observation data for model calibration with relatively fewer events. In this study, we constructed a comprehensive method of behavioral parameter ranking of multi-events (BPROME) based on coupling the Generalized Likelihood Uncertainty Estimation (GLUE) algorithm and the Storm Water Management Model (SWMM). The results in the two small demonstration areas (named Case #A and Case #B) in Shenzhen city of China proved the good performance of the BPROME in uncertainty assessment in urban areas. We found the model uncertainty (average bandwidth (B) and average deviation amplitude (D)) and model performance (containing Ratio (CR) and the maximum value of behavioral samples' NSE (NSEmax)) became stable at a certain number of events in both two case areas. The B and D decrease and the CR and NSEmax increase as the number of event increases. In particular, the model performance and uncertainty reach their appropriate state concerning the limited observations at a certain range of numbers of events (both three to five in our two case areas). Our results demonstrate the potential influence of the numbers of events for the urban rainfall-runoff modeling calibration which can balance the model efficiency and data collection cost (the number of input rainfall-runoff data). The findings could help decision-makers seek a trade-off between data investment and acceptable model performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • A modified quantitative method was constructed to separate flood events. • Ten flood behavior metrics was used to fully describe flood events and identify flood event classes. • Flood events in the Yangtze River basin were clustered into six distinct classes. • Flood event classes showed varying spatial pattern, indication a hindrance to unified flood management. • Meteorological, geographical, and human activities factors were dominant impact factors. Flood is one of the most devastating natural hazards and is responsible for sizeable social-economic losses and substantial fatalities. Flood events with diverse behavior characteristics vary greatly in spatial patterns and bring great challenges for flood management. In this study, the Peak Over Threshold (POT) approach coupled with an event-start-and-end detecting approach was proposed to separate flood events during 2008 ∼ 2018 across the Yangtze River Basin. Ten flood behavior metrics, comprehensively characterizing magnitude, duration, timing, rate of change, and flood forms of flood events, were used to fully describe flood events and then to identify flood event classes. Subsequently, the spatial heterogeneity of flood events was revealed based on behavior similarity classification of numerous events. Furthermore, a Contribution-Based Impact Factor Analysis (CBIFA) method was constructed to investigate the contributions of natural and anthropogenic factors to flood event variations. Results show that: (1) six flood event classes were identified including long-duration and small-rate-of-change flood events (Class 1, 31.00%), sharp-thin and short-tail flood events (Class 2, 20.58%), sharp-thin and early-peak flood events (Class 3, 5.12%), dwarf-fat flood events (Class 4, 18.37%), small and sharp-thin flood events (Class 5, 4.24%), and conventional events (Class 6, 20.67%). (2) Class 1 and Class 4, characterized by small rate of change, long duration and large magnitude, occurred across the whole Yangtze River Basin and mainly in the Middle-Lower Yangtze plains. Class 2 with small magnitude and short duration was mainly distributed in the Qinghai Tibet Plateau. Class 3, Class 5, and Class 6 mainly occurred in mountainous areas and hills in the middle and upper reaches, wherein Class 3 and Class 5 were characterized by large rate of change and short duration. (3) The meteorological factors were the most important impact factors and explained 30.23%∼68.10% of the total flood event variations, followed by geographical (9.19%∼32.10%), human activities (6.56%∼23.17%), soil (9.19%∼19.34%) and vegetation (2.56%∼5.31%) factors. Identifying the spatial pattern of flood events and their driver factors is a crucial step toward accurate flood prediction and will finally provide essential information for reliable flood management. [ABSTRACT FROM AUTHOR]

• The relative contributions of meteorological variables to the dryness changes have been quantified in Northwest China. • Warmer temperature and drier air have resulted in significant increase of dryness in recent decades. • Dryness may further increase along with higher temperature, drier air, and higher wind speed. Northwest China has experienced a warming-wetting climate featured by increasing temperature and precipitation during the past six decades. Recent studies suggested that the climate may have shifted from wetting to drying after the 1990s if changes in energy supply were considered. However, how the change in energy supply affects the dryness remains unclear. In this study, we quantified the dryness in Northwest China based on the Standardized Precipitation Evapotranspiration Index (SPEI) which considers the impact of potential evapotranspiration estimated by the Penman-Monteith equation on dryness during 1961–2018. Then, the contributions of changes in meteorological variables (precipitation, temperature, relative humidity, wind speed, and net radiation) to the dryness changes were estimated using a detrending technique. The results indicated that Northwest China experienced a wetting period (1961–1989) and then a drying period (1989–2018). During 1961–1989, increased precipitation and slowed wind were the main drivers of the wetting trend. During 1989–2018, although the increased precipitation and decline in solar radiation favored a wetting condition, warmer temperature, drier air (decrease in relative humidity), together with rebounded wind speed offset the wetting trend and resulted in significantly increasing dryness in Northwest China. The dryness would further increase if current climate trends continue in the future, which may have important implications for water management in Northwest China. [ABSTRACT FROM AUTHOR]

Afforestation is a key technique for the control of desertification and environmental deterioration in arid and semiarid regions. Therefore, it is important to quantify the influence of the succession that results from afforestation on biodiversity conservation and ecological environment. Here, we describe a case study in the sand-binding vegetation communities in China’s semiarid desert steppe in which we evaluated the effects of afforestation and key ecological processes on the community characteristics, and explored the ecological mechanism of the succession paradigm of afforestation in arid and semiarid regions. 42 species from 20 families and 40 genera along the afforestation successional gradient were collected during a comprehensive vegetation survey in 2013. The community was dominated by species in the Leguminosae, followed by the Poaceae, Compositae, and Zygophyllaceae. Our results show that the succession significantly affected community and habitat characteristics. The numbers of families, genera, and species decreased primarily during succession and then increased sharply to a maximum. Species diversity appeared to reach its maximum towards the middle of the succession, and shrubs had a greater contribution and accounted for 80.6% of the community biomass, whereas herbaceous plants contributed 64.8% of the total vegetation cover. Soil crusts significantly altered the rainfall infiltration and redistributed soil water balance, and water in the 40- to 100-cm soil layer played a decisive role in vegetation productivity and cover. Therefore, the interactional feedback between vegetation development, soil crusts and soil water was the main driver responsible for the feedback mechanism of the succession paradigm for the sand-binding vegetation communities in the semiarid desert steppe of China. [ABSTRACT FROM AUTHOR]

• A Bernoulli-Gamma-Gaussian model is built to calibrate S2S precipitation forecasts. • The model is effective in correcting bias and improving forecast reliability and skill. • A 15-day sliding window is suitable for pooling samples for S2S forecast calibration. Subseasonal to seasonal (S2S) precipitation forecasts can fill the gap between weather and seasonal forecasts. While raw forecasts from S2S models are informative, calibration is necessary to correct systematic biases and quantify forecast uncertainty to facilitate applications of S2S forecasts. This paper develops a seven-parameter Bernoulli-Gamma-Gaussian model to calibrate S2S precipitation forecasts. The Bernoulli distribution characterizes the occurrence of zero versus non-zero values of precipitation, the Gamma distribution accounts for the distribution of non-zero precipitation amounts and the bivariate Gaussian distribution formulates the relationship between raw forecasts and observations. A case study of the East River catchment in South China is devised for the S2S forecasts provided by the European Centre for Medium-Range Weather Forecasts (ECWMF). The Bernoulli-Gamma-Gaussian model is used to calibrate raw forecasts at the daily time step and the Schaake Shuffle is used to instill the temporal patterns to form ensemble time series forecasts. The results show that raw S2S forecasts generally suffer from considerable forecast bias and unreliable ensemble spread and can exhibit negative forecast skill. Compared to the quantile mapping, the Bernoulli-Gamma-Gaussian model with the Schaake Shuffle is effective in correcting biases, improving reliability and yielding forecast skill for daily and accumulated precipitation. Furthermore, a sliding window of 15 days tends to be suitable to pool samples to deal with sampling variability and precipitation seasonality for the purpose of calibration of S2S forecasts. Overall, the Bernoulli-Gamma-Gaussian model can serve as an effective tool to calibrate S2S precipitation forecasts for hydrological modeling and water resources management. [ABSTRACT FROM AUTHOR]

As most of the runoff resulting from snow-ice melt is related to climate change factors in the arid region of northwest China, the risk to water resource systems threatens the socio-economic and ecological environment and is becoming increasingly prevalent. Therefore, we explored the risks of water resource shortages for different periods (2010, 2020, and 2030) in the Aksu River basin (ARB) in the northwest arid region of China by reconstructing a risk model based on the framework proposed by the Intergovernmental Panel on Climate Change (IPCC) with an improved vulnerability (V) module and a more suitable hazard probability in the cost module. The major conclusions are as follows: (1) the simulation of the Community Land Model-Distributed Time Variant Gain Model (CLM-DTVGM) and the Vegetation Interface Processes model (VIP) was suitable for the eco-hydrological processes in the ARB under climate change (i.e., R2 ≥ 0.583; Nash coefficient ≥0.371; and relative mean standard ≤155.727 for CLM-DTVGM; R2 = 0.798 for VIP); (2) the vulnerability of the water resource system in the ARB was medium in 2010, and dropped to a medium-low to non-vulnerable level in 2020 before increasing in 2030 under different Representative Concentration Pathways (RCP) (RCP2.6, RCP4.5, and RCP8.5); and (3) there was a medium-low risk of water resource shortages in the ARB in 2010 (i.e., 0.246), and although the risk of water resource shortages decreased in 2020 due to the increasing water supply from mountainous areas, the risk predicted to increase significantly in 2030, to a medium-high risk level. This study is critical for accurately predicting and understanding the impact of climate change on water resource systems as well as on the drought risk in arid regions. [Display omitted] • Climate change and human activities have a significant impact on the risk of water shortage in the Aksu River Basin. • VIP and CLM-DTVGM can simulate the hydrological process in the Aksu River Basin well. • The cost of drought disaster was well integrated into the risk assessment model of water resource system. • The resilience of the water resource system in the ARB weakened, but the cost and exposure, and vulnerability increased. • The water resource system of Aksu River Basin will also suffer from great risks in the future. [ABSTRACT FROM AUTHOR]

Summary: Healthy phytoplankton communities are the basis of healthy water ecosystems, and form the foundation of many freshwater food webs. Globally many freshwater ecosystems are degraded because of intensive human activities, so water ecosystem restoration is a burning issue worldwide. Selection of key regions for phytoplankton-related restoration is crucial for an effective aquatic eco-restoration. This paper presents a practical method for identification of key regions for phytoplankton-related restoration, using random forests (RFs) method to cluster sites based on dominance, biodiversity, water chemistry and ecological niche. We sampled phytoplankton for species richness and relative abundance and water quality in the Huai River basin (HRB), China to determine the phytoplankton communities’ composition and structure and characterize of their ecological niches. A wider mean niche breadth of a species usually leads to a greater overlap with the niche of other species. Using these data and water quality indices, we identified the key regions for phytoplankton-related river restoration activities. Results indicate that our method for recognition of key regions is effective and practical and its application to the HRB identified the Northern Plain area as the key region for restoration. This area is severely polluted and contributes significantly to the HRB phytoplankton communities. Phytoplankton in this region is highly adaptable to environmental change and therefore will be relatively unharmed by environmental instability induced by restoration measures. During restoration, indices of water temperature, total phosphorus and chemical oxygen demand can be altered with little negative influence on phytoplankton communities, but measures that increase ammonia–nitrogen concentration would be highly detrimental. These results will provide valuable information for policy makers and stakeholders in water ecosystem restoration and sustainable basin management in the HRB. [ABSTRACT FROM AUTHOR]

Abstract: The chemistry of major ions (Ca, Mg, Na, K, HCO3, SO4, Cl and Si) in the water of the Huai River basin was studied, based on samples from 52 sites from nine different water bodies in July 2008. Ions and total dissolved solids (TDS) displayed clear spatial patterns with lower concentrations in the south and higher in the north of the basin; the same conditions were also found in the East Line of South–North Water Transfer Project (SNWTP) in this region. The Huai River main channel and Hongze Lake have moderate ion concentrations relative to the whole basin. TDS concentrations versus the weight ratios of Na/(Na+Ca) and ternary ions demonstrate that the southern rivers (Shi R. and Pi R.) are mainly controlled by the weathering of carbonates, whereas the northern water systems (Guo R., Shaying R., Nansi Lake and its tributaries) are dominated by the weathering of evaporites. The Huai River main channel, Hongze Lake and the East Line of SNWTP are synergistically influenced by weathering of evaporites and carbonates, yet Hongze Lake and the East Line of SNWTP are mainly controlled by evaporation and crystallization processes. This study also confirmed that the Huai River is the geographic division between southern and northern China. Most rivers of this basin have very high ionic composition relative to the global median and other world rivers. The spatial patterns and ionic composition also suggest that intensive anthropogenic activities in northern areas of this basin are well characterized. A comparison with WHO and Chinese standards for drinking water indicates that the northern water systems of this basin are not suitable for use as drinking water sources, and pollution control should be improved and enhanced in northern areas of the basin. [Copyright &y& Elsevier]

The use of biodegradable plastic film mulching as a replacement for polyethylene plastic film has gained recognition due to its reduced environmental pollution. However, its impact on soil environment is not yet fully understood. Here, we compared the effects of different plastic film mulching on the accumulation of microbial necromass carbon (C) and its contribution to soil total C in 2020 and 2021. Results showed that biodegradable plastic film mulching decreased the accumulation of fungal necromass C compared to no plastic film mulching and polyethylene film mulching. However, the bacterial necromass C and soil total C were not affected by the plastic film mulching. Biodegradable plastic film mulching decreased the soil dissolved organic carbon content after maize harvest. Random forest models suggested that soil dissolved organic C, soil pH and the ratio of soil dissolved organic C to microbial biomass C were important factors in regulating the accumulation of fungal necromass C. The abundance of the fungal genus Mortierella was also found to have a significant positive contribution to the accumulation of fungal necromass C. These findings suggest that biodegradable plastic film mulching may decrease the accumulation of fungal necromass C by changing substrate availability, soil pH, and fungal community composition, with potential implications for soil C storage., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Land use impacts from agriculture, industrialization, and human population should be considered in surface water quality management. In this study, we utilized an integrated statistical analysis approach mainly including a seasonal Mann-Kendall test, clustering analysis, self-organizing map, Boruta algorithm, and positive matrix factorization to the assessment of the interactions between land use types and water quality in a typical catchment in the Huai River Basin, China, over seven years (2012-2019). Spatially, water quality was clustered into three groups: upstream, midstream, and downstream/mainstream areas. The water quality of upstream sites was better than of mid-, down-, and mainstream. Temporally, water quality did not change significantly during the study period. However, the temporal variation in water quality of up-, down-, and mainstream areas was more stable than in the midstream. The interactions between land use types and water quality parameters at the sub-basin scale varied with seasons. Increasing forest/grassland areas could substantially improve the water quality during the wet season, while nutrients such as phosphorus from cropland and developed land was a driver for water quality deterioration in the dry season. Water area was not a significant factor influencing the variations of ammonia nitrogen (NH 3 -N) and total phosphorus (TP) in the wet or dry season, due to the intensive dams and sluices in study area. The parameters TP, and total nitrogen (TN) were principally linked with agricultural sources in the wet and dry seasons. The parameters NH 3 -N in the dry season, and chemical oxygen demand (COD Cr ) in the wet season were mainly associated with point source discharges. Agricultural source, and urban point source discharges were the main causes of water quality deterioration in the study area. Collectively, these results highlighted the impacts of land use types on variations of water quality parameters in the regulated basin., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The aquatic ecological health status was focused on the Huai River Basin (HRB) from the aspects of water quantity, water quality, water ecology, river connectivity, and riparian habitat environment. Ten monitoring sections were set up in the middle and upper reaches of HRB, and 5 experiments of each section were conducted in July and December from 2012 to 2014. Thus, relevant data on the species, the density of phytoplankton, zooplankton and benthic animals, the concentration of water physicochemical variables, and riparian habitat quality were obtained. Eleven key impact factors were chosen using frequency statistics, theoretical analysis, and correlation analysis methods, forming the evaluation index system of aquatic ecological health. Then, the indicator weight value was determined by the combined weight method, and the health degree was evaluated by the comprehensive index method. On the whole, the aquatic ecological health degree of the upper sections (D1 ~ D3) of the Shaying River ranges from 0.334 to 0.927, which is generally in a "sub-healthy" state. The aquatic ecological health degree of the main section of the Huai River (D8 ~ D10) ranges from 0.362 to 0.777, which is in the "critical" or "sub-healthy" state. The Huaidian Sluice (D5) and Fuyang Sluice (D6) in the middle and lower reaches of the Shaying River had the worst aquatic ecological health. Its water ecological health range is 0.283-0.523, and most of them are under "sub-pathologic." The research results have important theoretical and practical significance. They can enrich the evaluation theories and methods of river aquatic ecological health, help to grasp the aquatic ecological health status in HRB, and provide basic support for aquatic ecological protection and water pollution control in sluice-controlled rivers., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Snow cover is an important indicator of climate change. Variations of snow integrate the competing effect of increasing temperature and precipitation. In this study, based on Theil-Sen Median (TSM) and Mann-Kendall (M-K) methods, observational evidence from space was used to investigate the variation of snow parameters in China from 1979 to 2018, and some meaningful conclusions were found. (1) The downward trend of snow depth (SD) with a median of -0.02 cm/year was generally found in the high altitude mountains, and the upward trend of SD with a median of 0.01 cm/year occurs in the plains. A widespread and accelerated decrease of SD was observed in the latest period (2009-2018) in NC and NX. (2) The mean annual areas with snow cover days (SCDs) greater than 150 days (d) accounted for 17.8%, 24.73% and 38.14% in NC, NX and QTP. SCDs in NC and Northern QTP were widely reduced, but the longest snow season with more than eight months is still maintained on QTP. (3) The downward trend of snow storage (SS) was found in all three snow areas. The difference of snow phenology is reflected in the slowest accumulation and melting rate of SS on QTP; the largest peak value of SS and the shortest snow season in NC; the slow accumulation and rapid melting of snow in the NX, and the peak value is achieved at the latest. The trend of maximum temperature was judged as the most important factor affecting the change of SD, while longitude and latitude are closely related to the change of SCD., Competing Interests: Declaration of competing interest The authors declare that there are no conflicts of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Phytoplankton is critical to river ecosystems. These organisms are sensitive to streamflow and water quality changes and, therefore, used to determine stability of river ecosystems, especially in regulated rivers. However, exactly how such disturbances alter spatial distribution of phytoplankton remains unclear, particularly during different seasons. A thorough understanding of these mechanisms is required to better analyze impact of environmental factors on regulated rivers. Given this, phytoplankton communities, streamflow, and water quality factors were assessed in areas sampled four times from 2015 to 2016 in upper and middle Huai River Basin. Biodiversity indices, as well as cluster and rank analyses, were used to (1) determine phytoplankton composition and distribution and (2) clarify impacts of key streamflow and water quality factors on such communities. It was found phytoplankton composition deteriorated over time, with phyla number decreasing from six to three. Moreover, proportion of Bacillariophyta increased from 51.83% to 68.13%. Phytoplankton in three regions, upstream region (Shannon-Wiener index 1.39-2.95), midstream region (0.70-4.55), and downstream region (0.22 to 2.97), were spatially clustered. The most impact factors impacting variation in composition and distribution were water quality factors and then hydrological factors. Of these, the most important factors in wet seasons were total nitrogen and maximum runoff, while ammonia nitrogen and low flow discharge were the most important factors during dry seasons. Streamflow and water quality contributed the most in midstream region, which was significantly affected by numbers of high and low flow. Contributions of these factors to downstream region were the strongest during dry seasons, which were significantly affected by numbers of low flow. Collectively, these results reveal significant impact of streamflow and water quality factors on phytoplankton deterioration in upper and middle Huai River Basin. Critically, this study provides scientific and technological support for increased biomonitoring and ecohydrological studies in regulated river basins., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The environmental risk presented by "down-the-drain" chemicals to receiving rivers in large urban areas has received increasing attention in recent years. Geo-referenced Regional Environmental Assessment Tool for European Rivers (GREAT-ER) is a typical river catchment model that has been specifically developed for the risk assessment of these chemicals and applied in many European rivers. By utilizing the new version of the model, GREAT-ER 3.0, which is the first completely open source software for worldwide application, this study represents the first attempt to conduct an application of GREAT-ER in the Wenyu River of China. Aquatic exposure simulation and an environmental risk assessment of nonylphenol (NP) and its environmental precursor nonylphenol ethoxylates (NPEOs) were conducted effectively by GREAT-ER model, since NP is one of typical endocrine disrupting chemicals (EDCs) and its environmental precursor NPEOs as a "down-the-drain" chemical are extensively used in China. In the result, the predicted environmental concentrations (PECs) of NP and NPEOs in the water of Wenyu River were 538 and 4320 ng/L, respectively, at the regional scale, and 1210 and 8990 ng/L, respectively, at the local scale. From the results profile of the RCR, the combination of high emissions from large STPs with insufficient dilution of the river caused the high RCR. The PECs of NP in the sediment were in the range of 216.8-8218.3 ng/g (dry weight), which was consistent with the available monitoring data. The study showed the worldwide applicability and reliability of GREAT-ER as a river catchment model for the risk assessment of these chemicals and also revealed the general environmental risks presented by NP and NPEOs in the Wenyu River catchment in Beijing due to the extensive use of these chemicals. The results suggest that specific control or treatment measures are probably warranted for these chemicals to reduce their discharge in major cities.

Water quality deterioration is a prominent issue threatening water security throughout the world. Huai River Basin, as the sixth largest basin in China, is facing the most severe water pollution and high disturbance. Statistical detection of water quality trends and identification of human interferences are significant for sustainable water quality management. Three key water quality elements (ammonium nitrogen: NH3-N, permanganate index: CODMn and dissolved oxygen: DO) at 18 monitoring stations were selected to analyze their spatio-temporal variations in the highly disturbed Huai River Basin using seasonal Mann-Kendall test and Moran's I method. Relationship between surrounding water environment and anthropogenic activities (point source emission, land use) was investigated by regression analysis. The results indicated that water environment was significantly improved on the whole from 1994 to 2005. CODMn and NH3-N concentrations decreased at half of the stations, and DO concentration increased significantly at 39% (7/18) stations. The high pollution cluster centers for both NH3-N and CODMn were in the middle stream of Shaying River and Guo River in the 2000s. Water quality of Huai River Basin was mainly influenced by point source pollution emission, flows regulated by dams, water temperature and land use variations and so on. This study was expected to provide insights into water quality evolution and foundations for water quality management in Huai River Basin, and scientific references for the implementation of water pollution prevention in China., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Water quantity and quality joint operation is a new mode in the present dams' operation research. It has become a hot topic in governmental efforts toward integrated basin improvement. This paper coupled a water quantity and quality joint operation model (QCmode) and genetic algorithm with Soil and Water Assessment Tool (SWAT). Together, these tools were used to explore a reasonable operation of dams and floodgates at the basin scale. Wenyu River Catchment, a key area in Beijing, was selected as the case study. Results showed that the coupled water quantity and quality model of Wenyu River Catchment more realistically simulates the process of water quantity and quality control by dams and floodgates. This integrated model provides the foundation for research of water quantity and quality optimization on dam operation in Wenyu River Catchment. The results of this modeling also suggest that current water quality of Wenyu River will improve following the implementation of the optimized operation of the main dams and floodgates. By pollution control and water quantity and quality joint operation of dams and floodgates, water quality of Wenyu river will change significantly, and the available water resources will increase by 134%, 32%, 17%, and 82% at the downstream sites of Sha River Reservoir, Lutong Floodgate, Xinpu Floodgate, and Weigou Floodgate, respectively. The water quantity and quality joint operation of dams will play an active role in improving water quality and water use efficiency in Wenyu River Basin. The research will provide the technical support for water pollution control and ecological restoration in Wenyu River Catchment and could be applied to other basins with large number of dams. Its application to the Wenyu River Catchment has a great significance for the sustainable economic development of Beijing City.