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The 2008 Wenchuan earthquake-induced landslides destroyed larger areas of mountain vegetation and produced large volume of landslide-debris, which made the vegetation's hydrological adjusting function diminished and made the hydrological progresses in slopes changed, resulting in severe erosion and catastrophic debris flows for a rather long time. Since 2008, the landslide-damaged vegetation and its hydrological function have been recovering. In this paper, the Minjiang Upstream watersheds around Yingxiu Town were selected. First, the landslide-damaged vegetation was identified and monitored via multi-temporal (2001-2014) satellite images. Then, the slope materials stabil ity was assessed through topographic analysis of the vegetation survival environments. Then, the hydrological connectivity index (HCI) was defined to describe the upstream sediment production and downstream transport pathway. Finally, results indicated that HCI decreased annually with the vegetation recovery after the obvious increases during the earthquakes. While, analysis of 2008-2013 debris flow events indicated that the areas, the vertical drop to river<1000m and the horizontal distance to river<2500m, have high HCI increases and are more susceptible for debris flow formation. Monitoring the landslide-damaged vegetation recovery processes can contribute to assess the hydrological connectivity changes and understand the debris flow formation. [ABSTRACT FROM AUTHOR]

Climate change and intensified human activities are exacerbating the frequency and severity of extreme precipitation events, necessitating more precise and timely flood risk assessments. Traditional models often fail to dynamically and accurately assess flood risks due to their static nature and limited handling of spatiotemporal variations. This study confronts these challenges head-on by developing a novel coupled hydrological-hydrodynamic model integrated with a Block-wise use of the TOPMODEL (BTOP) and the Rainfall-Runoff-Inundation (RRI) model. This integrated approach enables the rapid acquisition of high-precision flood inundation simulation results across large-scale basins, addressing a significant gap in dynamic flood risk assessment and zoning. A critical original achievement of this research lies in developing and implementing a comprehensive vertical-horizontal combined weighting method that incorporates spatiotemporal information for dynamic evaluation indicators, significantly enhancing the accuracy and rationality of flood risk assessments. This innovative method successfully addresses the challenges posed by objective and subjective weighting methods, presenting a balanced and robust framework for flood risk evaluation. The findings from the Min River Basin in China, as a case study, demonstrate the effectiveness of the BTOP-RRI model in capturing the complex variations in runoff and the detailed simulations of flood processes. The model accurately identifies the timing of these peaks, offering insights into the dynamic evolution of flood risks and providing a more precise and timely assessment tool for policymakers and disaster management authorities. The flood risk assessment results demonstrate good consistency with the actual regional conditions. In particular, high-risk areas exhibit distinct characteristics along the river channel, with the distribution area significantly increasing with a sudden surge in runoff. Intense precipitation events expand areas classified as moderate and high risk, gradually shrinking as precipitation levels decrease. This study significantly advances flood risk assessment methodologies by integrating cutting-edge modeling techniques with comprehensive weighting strategies. This is essential for improving the scientific foundation and decision-making processes in regional flood control efforts., 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 © 2024 Elsevier Ltd. All rights reserved.)

Eutrophication is a serious threat to water quality and human health, and chlorophyll-a (Chla) is a key indicator to represent eutrophication in rivers or lakes. Understanding the spatial-temporal distribution of Chla and its accurate prediction are significant for water system management. In this study, spatial-temporal analysis and correlation analysis were applied to reveal Chla concentration pattern in the Fuchun River, China. Then four exogenous variables (wind speed, water temperature, dissolved oxygen and turbidity) were used for predicting Chla concentrations by six models (3 traditional machine learning models and 3 deep learning models) and compare the performance in a river with different hydrology characteristics. Statistical analysis shown that the Chla concentration in the reservoir river segment was higher than in the natural river segment during August and September, while the dominant algae gradually changed from Cyanophyta to Cryptophyta. Moreover, air temperature, water temperature and dissolved oxygen had high correlations with Chla concentrations among environment factors. The results of the prediction models demonstrate that extreme gradient boosting (XGBoost) and long short-term memory neural network (LSTM) were the best performance model in the reservoir river segment (NSE = 0.93; RMSE = 4.67) and natural river segment (NSE = 0.94; RMSE = 1.84), respectively. This study provides a reference for further understanding eutrophication and early warning of algal blooms in different type of rivers., 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 © 2024. Published by Elsevier Ltd.)

The Budyko framework, widely used to quantify the watershed hydrological response to the watershed characteristics and climate variabilities, is continuously refined to overcome the disadvantages of steady state assumption. However, dynamic variations in vegetations and climate variables are not fully integrated including coverages and precipitation regimes of intensity, frequency, and duration. To address this, we developed an innovative approach for determining the parameter ω in the Budyko framework to quantify the hydrological effects of vegetation restoration in a mesoscale watershed located in northern China. We found that fractional vegetation coverage (FVC), heavy precipitation amount (95pTOT), and the number of precipitation days (R01mm) are significant variables for estimating ω to improve the predictive capability of the watershed response. This extended time-varying Budyko framework can rigorously capture the temporal variations and underlying mechanisms of interactions between vegetation dynamic and precipitation regime partitioning precipitation (P) to R. Under the Budyko-Fu framework, compared to constant ω (ω‾) or ω that only considers FVC (ω P ) or precipitation regimes (ω FVC ) for simulating R, using ω that integrated FVC and precipitation regimes (ω P-FVC ) can improve Nash-Sutcliffe efficiency coefficient (NSE) by 24.81%, while reduced the root mean squared error (RMSE) and relative error (RE) by 64.08% and 65.77%, respectively. Although the increase in climatic dryness (PET/P) resulted in decreased R, the increase in FVC has also a significant contribution to this decrease due to vegetation restoration. We highlight that decrease precipitation intensity (95pTOT) and frequency (R01mm) amplified the hydrological effects of vegetation restoration, causing a 79.09∼100.31% increase in R compared to the independent impact of changes in FVC. We conclude that the extended time-varying Budyko framework by precipitation regime is more rigorous for quantifying the hydrological effects of ecological restoration under climate change and providing more reliable approach for adaptive watershed management., 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 © 2024 Elsevier Inc. All rights reserved.)

Humans have played a fundamental role in altering lake wetland ecosystems, necessitating the use of diverse data types to accurately quantify long-term changes, identify potential drivers, and establish a baseline status. We complied high-resolution historical topographic maps and Landsat imagery to assess the dynamics of the lake wetlands in the Yangtze Plain over the past century, with special attention to land use and hydrological connectivity changes. Results showed an overall loss of 45.6 % (∼11,859.5 km 2 ) of the lake wetlands over the past century. The number of lakes larger than 10 km 2 decreased from 149 to 100 due to lake dispersion, vanishing, and shrinkage. The extent of lake wetland loss was 3.8 times larger during the 1930s-1970s than that in the 1970s-1990s. Thereafter, the lake wetland area remained relatively stable, and a net increase was observed during the 2010s-2020s in the Yangtze Plain. The significant loss of lake wetland was predominately driven by agricultural activities and urban land expansion, accounting for 81.1 % and 4.9 % of the total losses, respectively. In addition, the changes in longitudinal and lateral hydrological connectivity further exacerbated the lake wetland changes across the Yangtze Plain through isolation between lakes and the Yangtze River and within the lakes. A total of 130 lakes have been isolated from the Yangtze River due to the construction of sluices and dykes throughout the Yangtze Plain, resulting in the decrease in the proportion of floodplain marsh from 28.3 % in the 1930s to 8.0 % in the 2020s. Furthermore, over 260 sub-lakes larger than 1 km 2 (with a total area of 1276.4 km 2 ) are experiencing a loss of connectivity with their parent lakes currently. This study could provide an improved historical baseline of lake wetland changes to guide the conservation planning to wetland protection and prioritization area in the Yangtze Plain., 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 © 2024 Elsevier Ltd. All rights reserved.)

Understanding the relationship between hydrological connectivity (HC) and water level (WL) is crucial for effective water resource management and wetland restoration. However, current knowledge regarding this relationship is limited. This study proposed an integrated nonstationary and uncertain analysis framework (INUAF) to investigate the HC-WL relationship with reference to the Baiyangdian wetland, which is a fragmented wetland in North China. With the INUAF, the interannual and intra-annual variations of both HC and WL were examined, together with the wavelet coherence and lag effects between the two variables at multiple scales. The results highlighted marked nonstationarity in HC, WL, and the relationship between them. Scale-dependent lag effects revealed that HC lags WL by 37 days (131 days) at the 1 a scale (4 a scale), and leads WL by 190 days at the 8 a scale, indicating a complex coupled relationship between HC and WL. Additionally, the INUAF was applied to evaluating the uncertainty in the response of lagged HC to varied WL. Results indicated that every 0.2-m increase in WL led to a 2.2%-2.4% higher probability of maintaining high HC for WL between 6.0 and 8.0 m, but a 10%-11% higher probability for WL between 8.0 and 9.0 m. We suggest that a WL of > 8.4 m would produce a probability of > 50% for achieving high HC. These findings provide valuable insights into the HC-WL relationship and could contribute to wetland restoration efforts., 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 © 2024 Elsevier Ltd. All rights reserved.)

Although enhancing the knowledge of nitrogen (N) dynamics in aquatic systems is crucial for basin N management, there is still a lack of theories on the patterns of basin N sources and transport because of the intricate influence of human activities, climatic conditions, landscape patterns, and topography on the trajectory of basin N. To shed new light on the patterns of basin N sources and transport in the Chinese subtropical monsoon region, this study provides a comprehensive approach combining multiple isotopes and hydrological model based on monthly records of hydro-chemistry and isotopes ( 18 O-NO 3 - / 15 N-NO-3 and 18 O-H 2 O / 2 H-H 2 O) for river water, groundwater and rainfall in three basins over multiple years. Our observations of hydro-chemistry showed that fluvial N levels in highly urbanized basins (3.05 ± 1.42 mg·L -1 ) were the highest and were characterized by higher levels in the dry season. In the agricultural basin, fluvial N levels in February and March were approximately 1.9 times higher than those in the other months. The fluvial N load was higher in agricultural basins (0.624-0.728 T N km -2 y -1 ) than in urban basins (0.558 T N km -2 y -1 ), primarily because of variations in sewage treatment rates and fertilizer application. In highly urbanized basin, manure and sewage (46.9 %) were the dominant sources of fluvial N, which were discharged into rivers after treatment. In the plain agricultural basin, a substantial portion of diffused residential sewage leaches into aquifers and is stored. In the hilly agro-forest mixed basin, the high baseflow coefficient (75.8 %) and the key role of groundwater N, mainly from soil N (27.3 %), chemical fertilizers (20.2 %), manure and sewage (46.6 %), to fluvial N (26.5 %) indicated that a high proportion of the N sources leached into the aquifer and were then transported to rivers. For the first time, this study integrated multiple methods to substantiate the proposed typical patterns of N sources and transport within the basins. These findings have significant implications for tailored basin-specific N management strategies., 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 © 2024 Elsevier Ltd. All rights reserved.)

Hydrological models are vital tools in environmental management. Weaknesses in model robustness for hydrological parameters transfer uncertainties to the model outputs. For streamflow, the optimized parameters are the primary source of uncertainty. A reliable calibration approach that reduces prediction uncertainty in model simulations is crucial for enhancing model robustness and reliability. The optimization of parameter ranges is a key aspect of parameter calibration, yet there is a lack of literature addressing the optimization of parameter ranges in hydrological models. In this paper, we introduce a parameter calibration strategy that applies a clustering technique, specifically the Self-Organizing Map (SM), to intelligently navigate the parameter space during the calibration of the Soil and Water Assessment Tool (SWAT) model for monthly streamflow simulation in the Baishan Basin, Jilin Province, China. We selected the representative algorithm, the Sequential Uncertainty Fitting version 2 (SUFI-2), from the commonly used SWAT Calibration and Uncertainty Programs for comparison. We developed three schemes: SUFI-2, SUFI-2-Narrowing Down (SUFI-2-ND), and SM. Multiple diagnostic error metrics were used to compare simulation accuracy and prediction uncertainty. Among all schemes, SM outperformed the others in describing watershed streamflow, particularly excelling in the simulation of spring snowmelt runoff (baseflow period). Additionally, the prediction uncertainty was effectively controlled, demonstrating the SM's adaptability and reliability in the interval optimization process. This provides managers with more credible prediction results, highlighting its potential as a valuable calibration tool in hydrological modeling., 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 © 2024 Elsevier Ltd. All rights reserved.)

Dams and reservoirs have significantly altered river flow dynamics worldwide. Accurately representing reservoir operations in hydrological models is crucial yet challenging. Detailed reservoir operation data is often inaccessible, leading to relying on simplified reservoir operation modules in most hydrological models. To improve the capability of hydrological models to capture flow variability influenced by reservoirs, this study proposes a hybrid hydrological modeling framework, which combines a process-based hydrological model with a machine-learning-based reservoir operation module designed to simulate runoff under reservoir operations. The reservoir operation module employs an ensemble of three machine learning models: random forest, support vector machine, and AutoGluon. These models predict reservoir outflows using precipitation and temperature data as inputs. The Soil and Water Assessment Tool (SWAT) then integrates these outflow predictions to simulate runoff. To evaluate the performance of this hybrid approach, the Xijiang Basin within the Pearl River Basin, China, is used as a case study. The results highlight the superiority of the SWAT model coupled with machine learning-based reservoir operation models compared to alternative modeling approaches. This hybrid model effectively captures peak flows and dry period runoff. The Nash-Sutcliffe Efficiency (NSE) in daily runoff simulations shows substantial improvement, ranging from 0.141 to 0.780, with corresponding enhancements in the coefficient of determination (R 2 ) by 0.098-0.397 when compared to the original reservoir operation modules in SWAT. In comparison to parameterization techniques lacking a dedicated reservoir module, NSE enhancements range from 0.068 to 0.537, and R 2 improvements range from 0.027 to 0.139. The proposed hybrid modeling approach effectively characterizes the impact of reservoir operations on river flow dynamics, leading to enhanced accuracy in runoff simulation. These findings offer valuable insights for hydrological forecasting and water resources management in regions influenced by reservoir operations., 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 © 2024 Elsevier Ltd. All rights reserved.)

This paper explores whether the sponge city construction implemented in China can restore the hydrological condition of the river basins through runoff depth. The annual runoff depth was calculated based on the volume capture ratio of annual rainfall (VCRAR) and compared with undeveloped and before sponge city construction. The results conclude as follows: the current rainwater source control standard benefits the hydrology recovery in China. But the difference between before sponge city construction and undeveloped is large in 12.9% of the regions. The adjustment recommendations of the VCRAR proposed in this paper are favourable to restoring the river basin hydrology. [ABSTRACT FROM AUTHOR]

Climate change is the dominant factor affecting the hydrological process, it is of great significance to simulate and predict its influence on water resources management, socio-economic activities, and sustainable development in the future. In this paper, the Xiying River Basin was taken as the study area, China Atmospheric Assimilation Driven Data Set (CMADS) and observation data from the Jiutiaoling station were used to simulate runoff of the SWAT model and calibrate and verify model parameters. On this basis, runoff change of the basin under the future climate scenario of CMIP6 was predicted. Our research shows that: (1) The contribution rates of climate change and human activities to runoff increase of the Xiying River are 89.17% and 10.83%, respectively. Climate change is the most important factor affecting runoff change of the Xiying River. (2) In these three different emission scenarios of SSP1-2.6, SSP2-4.5 and SSP5-8.5 in CMIP6 climate model, the average temperature increased by 0.61, 1.09 and 1.74 °C, respectively, in the Xiying River Basin from 2017 to 2050. Average precipitation increased by 14.36, 66.88, and 142.73 mm, respectively, and runoff increased by 15, 24, and 35 million m³, respectively. The effect of climate change on runoff will continue to deepen in the future. [ABSTRACT FROM AUTHOR]

Drought is a common natural disaster that greatly affects the crop yield and water supply in China. However, the spatiotemporal characteristics of drought in China are not well understood. This paper explores the spatial and temporal distributions of droughts in China over the past 40 years using multiscale standardized precipitation evapotranspiration index (SPEI) values calculated by monthly precipitation and temperature data from 612 meteorological stations in China from 1980 to 2019 and combines the space–time cube (STC), Mann–Kendall test, emerging spatiotemporal hot-spot analysis, spatiotemporal clustering, and local outliers for the analysis. The results were as follows: 1) the drought frequency and STC show that there is a significant difference in the spatiotemporal distribution of drought in China, with the most severe drought in Northwest China, followed by the western part of Southwest China and the northern part of North China. 2) The emerging spatiotemporal hot-spot analysis of SPEI6 over the past 40 years reveals two cold spots in subregion 4, indicating that future droughts in the region will be more severe. 3) A local outlier analysis of the multiscale SPEI yields a low–low outlier in western North China, indicating relatively more severe year-round drought in this area than in other areas. The low–high outlier in central China indicates that this region was not dry in the past and that drought will become more severe in this region in the future. [ABSTRACT FROM AUTHOR]

River hydrology is an important proxy for changes in river runoff and an important factor affecting the ecology of rivers. To quantitatively evaluate the hydrology of the Wuijang River basin, this paper uses various tests to analyze runoff. The IHA-RVA method combined with FDC ecohydrological indicators was used to evaluate the hydrology of the Wuijang River basin and to analyze and calculate the contribution of human activities and climate change to runoff. The results show that (1) the runoff in the Wujiang River basin has shown a decreasing trend over the years, with a sudden change in 2005 and mainly two inter-annual cycles; (2) the overall hydrological change in runoff is 48%, which is a moderate change; (3) The changes in FDC ecological indicators are significantly correlated with rainfall, and the correlation between FDC ecological indicators and IHA hydrological indicators is strong; (4) human activities are the main influencing factors of runoff changes in the Wujiang River. The results of this paper have some reference value for the management of the Wujiang River basin and the improvement and restoration of river ecology. [ABSTRACT FROM AUTHOR]

Afforestation has been initiated in Northeast Asia to improve ecological status. The responses of the regional hydrological cycle to vegetation restoration remain insufficiently explored. This study uses a variety of satellite-derived vegetation variables and hydrological cycle components to scan the eco-hydrological regimes in the Three-North Region of China and Mongolia during the past four decades. We observe that vegetation productivity increases mainly in North China (NC), Northeast China (NEC), Northwest China (NWC), and the north of Inner Mongolia and Mongolia. Precipitation and runoff show a decreasing trend (-0.4 mm/year and - 0.6 mm/year, respectively), yet they are less correlated to the normalized difference vegetation index and leaf area index. Along with increasing vegetation productivity, evapotranspiration increases (0.05 mm/year) obviously in NC and NEC, while root soil moisture (-0.001 m 3 /m 3 /year) and terrestrial water storage (-2.0 mm/year) decrease in NC and parts of NEC and NWC. The correlation coefficient between evapotranspiration and vegetation variables is up to 0.73. Collectively, results imply one potential adverse response of terrestrial water fluxes to increasing vegetation. Independent ecological and hydrological datasets further corroborate our work. Climatic factors (i.e., downward shortwave radiation and air temperature) and human activities (i.e., aerosol optical depth, carbon dioxide, and water withdrawal) substantially affect regional hydrological cycles. Considering the increasing vegetation productivity in the Three-North Region of China and Mongolia is likely to continue in the 21st century based on the Sixth Coupled Model Intercomparison Project (CMIP6) simulations, the terrestrial water fluxes may undergo deficit pressure. Overall, this study comprehensively investigates the vegetation and hydrology interplays, and provides a reference for protecting and improving ecological-hydrological conditions in Northeast Asia., 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.)

Understanding spatiotemporal heterogeneity of streamflow and baseflow and revealing their changes contributed by climatic factors and human activities in the alpine region of inland river basin are critical for regional water management. However, the hydrology heterogeneity in the alpine region has remained unclear, which limits the scientific understanding of the interaction mechanism between the hydrological cycle and terrain, and further constrains the effective utilization of regional water resources in the water-shortage areas. In this study, the hydrological process and regimes for headstreams of Tarim River Basin (HTRB) during 1985-2011 were simulated by the Soil and Water Assessment Tool. We systematically characterized the spatial and temporal patterns of streamflow and baseflow through geostatistical and trend analyses, and subsequently investigated their heterogeneity responses to climate change and human activities at different sub-basins and elevation zones. Results show that the spatial distributions of streamflow and baseflow are highly related to terrain and river direction. Increased trends in precipitation enhanced with altitude, whereas decreased trends in potential evapotranspiration (PET) weakened with altitude, meanwhile, increased trends in streamflow and baseflow of HTRB are most pronounced in mid-altitude areas during 1985-2011. The climate elasticities of streamflow and baseflow are highly reliant on the altitudinal gradient. Increases in streamflow and baseflow in high-lying areas are more sensitive to precipitation variation, while they are more sensitive to PET change in low-lying areas. The magnitude and change rate with altitude bands of the precipitation has greater effects on streamflow and baseflow variations than those of PET. Furthermore, the percentage of sub-basins where climate changes dominate streamflow variation in each elevation band increases with height but decreases abruptly at elevations above 5000 m. The percentage of sub-basins where climate changes dominate baseflow variations gradually decreases in elevation bands above 3000 m. Our results indicate that climate change rather than human activities dominants the variation in streamflow and baseflow in most sub-basins and elevation bands., 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.)

Hydraulic Engineering Infrastructure Projects (HEIPs) typically show profound effects on hydrological systems and ecosystems. However, data restrictions have limited the exploration of the influences of compound HEIPs on ecosystems to a few studies. This study proposes a watershed-wide ecosystem assessment framework to investigate the impact of HEIPs in the Tarim River Headwaters-Hotan River Basin on the ecosystem of the arid zone. The framework includes a deep learning-meta cellular automata algorithm (DLMCAA) based on the spatiotemporal characteristics of HEIPs and hydro-meteorological and human activities. Moreover, the spatiotemporal relationships between compound HEIPs and ecosystem variances were quantified. The framework including DLMCAA showed a good performance in simulating landcover in 2020, with a Kappa coefficient of 0.89. Therefore, the DLMCAA could be used to simulate and predict ecosystem changes under the HEIPs, which suggested that the framework is effective and practical. An analysis of the spatiotemporal distribution of each ecosystem from 1980 to 2020 showed that the low shrub ecosystems changed most significantly (26.38 %) between 1980 and 2020. Also, the use of spatially driven hydrological project data from different ABC scenarios showed that ecosystems driven by HEIPs were more stable compared to those without HEIPs under future climate change. In particular, the DLMCAA indicated that compound HEIPs had a more positive impact on ecosystem oases in arid lands compared with that of single HEIPs. The results of this study can serve as a scientific reference for assessing the impact of HEIPs, as well as for understanding ecosystem changes and facilitating sustainable water resource management in the arid regions., 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.)

Hydrological processes in mid-latitude mountainous regions are greatly affected by changes in vegetation cover that induced by the climate change. However, studies on hydrological processes in mountainous regions are limited, because of difficulties in building and maintaining basin-wide representative hydrological stations. In this study, a new method, remote sensing technology for monitoring river discharge by combining satellite remote sensing, unmanned aerial vehicles and hydrological surveying, was used for evaluating the runoff processes in the Changbai Mountains, one of the mid-latitude mountainous regions in the eastern part of Northeast China. Based on this method, the impact of vegetation cover change on hydrological processes was revealed by combining the data of hydrological processes, meteorology, and vegetation cover. The results showed a decreasing trend in the monitored river discharge from 2000 to 2021, with an average rate of -5.13 × 10 5 m 3 yr -1 . At the monitoring section mainly influenced by precipitation, the precipitation-induced proportion of changes in river discharge to annual average river discharge and its change significance was only 6.5 % and 0.23, respectively, showing the precipitation change was not the cause for the decrease in river discharge. A negative impact of evapotranspiration on river discharge was found, and the decrease in river discharge was proven to be caused by the increasing evapotranspiration, which was induced by the drastically increased vegetation cover under a warming climate. Our findings suggested that increases in vegetation cover due to climate change could reshape hydrological processes in mid-latitude mountainous regions, leading to an increase in evapotranspiration and a subsequent decrease in river discharge., 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 climate aridity since the mid-20th century has raised concerns about water resources on the Chinese Loess Plateau (CLP). A lack of extended observation-like precipitation records for the eastern CLP (ECLP) means that it remains unclear whether or not the current arid state of the CLP is unprecedented, and the spatial-temporal characteristics of hydroclimatic variability across the CLP over past centuries are not well understood. Here we present a regional hydrological-year precipitation reconstruction for the Heichashan Mountains, which successfully captures hydroclimate changes on the ECLP since 1773 CE. The reconstruction explains 48.72 % of the observed variance for 1957-2019 CE and reveals a wetting trend since the early 2000s and shows 2014-2020 CE to have been the second wettest period over the past 248 years. 1910-1932 CE was the longest and driest period over the past centuries. Furthermore, the 19th century was relatively wet, whereas the 20th century was dry. We demonstrate that droughts tend to occur in warm periods. Combining our new reconstruction with previously published hydroclimatic reconstructions, we find that hydroclimate has changed synchronously on the ECLP and the western CLP (WCLP) for most of the past two centuries. Some regional differences do exist, for example in the 1890s-1920s, when aridity gradually intensified across the ECLP, no similar drying is evident in records for the WCLP, although the 1920s megadrought occurred in both the ECLP and WCLP. Another difference is in the onset of the 20th-century aridity, which began in the 1950s on the ECLP, around 20 years later than it began on the WCLP. In addition to the known influences of the Asian Summer Monsoon and related large-scale circulations, this work highlights a major finding that the 1920s megadrought may be related to a regime shift in Northern Hemisphere temperature., 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.)

Model calibration has always been one major challenge in the hydrological community. Flood scaling properties (FS) are often used to estimate the flood quantiles for data-scarce catchments based on the statistical relationship between flood peak and contributing areas. This paper investigates the potential of applying FS and multivariate flood scaling properties [multiple linear regression (MLR)] as constraints in model calibration. Based on the assumption that the scaling property of flood exists in four study catchments in northern China, eight calibration scenarios are designed with adopting different combinations of traditional indicators and FS or MLR as objective functions. The performance of the proposed method is verified by employing a distributed hydrological model, namely, the Soil and Water Assessment Tool (SWAT) model. The results indicate that reasonable performance could be obtained in FS with fewer requirements of observed streamflow data, exhibiting better simulation of flood peaks than the Nash-Sutcliffe efficiency coefficient calibration scenario. The observed streamflow data or regional flood information are required in the MLR calibration scenario to identify the dominant catchment descriptors, and MLR achieves better performance on catchment interior points, especially for the events with uneven distribution of rainfall. On account of the improved performance on hydrographs and flood frequency curve at the watershed outlet, adopting the statistical indicators and flood scaling property simultaneously as model constraints is suggested. The proposed methodology enhances the physical connection of flood peak among sub-basins and considers watershed actual conditions and climatic characteristics for each flood event, facilitating a new calibration approach for both gauged catchments and data-scarce catchments. [ABSTRACT FROM AUTHOR]

In order to better cope with water environmental problems as part of the whole world's climate change, much data are needed. As citizens are more concerned about the safety of the water environment, the role of citizen data in promoting the development of hydrology is a subject of attention. Hydrological data based on smartphones are expected to become a key research direction for new breakthroughs in hydrology. This paper explores the three functions of smartphones in the field of hydrology, summarizes the application advances of smartphones and puts forward the possible future development direction in China. [ABSTRACT FROM AUTHOR]

Hydropower plays an important role in the supply of renewable energy, but it also exerts a great influence on the river continuum. Understanding nutrient cycling and microbial community succession in hydropower reservoirs is key to weighing hydroelectric pros and cons. However, the underlying control mechanisms are still not well known, especially with respect to the impacts of hydrological conditions. Based on a comprehensive survey of hydropower reservoirs along the Wujiang River in SW China and an integration of published data, we found that reservoir physicochemical and biological stratifications and planktonic microbial community assembly were synergistically evolving, and reservoir hydraulic load (i.e., mean water depth per unit retention time) was a key factor controlling the strength of stratifications, CO 2 and N 2 O fluxes, nutrient retention efficiency, and bacterioplankton diversity. Hydraulic loads are artificially designed for hydropower reservoirs, and nutrient cycling and biological succession in reservoirs are thus governed by anthropogenic regulation. This study provides a theoretical basis to mitigate the environmental impacts of hydropower dams by regulating reservoir hydraulic load., 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.)

Understanding the temporal and spatial distribution characteristics of the cultural heritage of the Yellow River Basin can effectively improve the scientific understanding of the historical changes, environmental evolution, and cultural and economic development of the Yellow River Basin and thus provide a scientific and reasonable decision-making basis for the protection and development of its cultural heritage. The research object of this paper are the national cultural relic protection units. These are examined using the GIS spatial analysis method to explore the spatial and temporal distribution characteristics and spatial structure of 2,102 national material cultural heritage sites in the Yellow River basin. The results show that the spatial distribution of cultural heritage has a significant spatial agglomeration effect. The whole basin is concentrated in stable high- and low-value areas, and the difference between the high- and low-value areas is clear. Some aspects of the spatial structure heterogeneity are strong, showing a low value dispersion distribution trend. In different periods, the distribution direction and scope of cultural heritage have low ranges of rotation, a clear direction, and a high degree of centripetal distribution. The spatial and temporal distribution of cultural heritage is the result of the combined action of natural geographical environment such as climate change, topography, river hydrology, and human environment such as administrative institutional changes, ideological evolution, and social and economic development., Competing Interests: The authors have declared that no competing interests exist.

It is of great practical significance to ensure ecological water requirements (EWRs) for the maintenance of river health and the sustainable development of human socioeconomics. How to scientifically determine the comprehensive EWRs and estimate the uncertainty of hydro-ecological tools performed in the process of conducting remains one of the most important yet most complicated issues. In this study, the ecological water requirements framework (EWRsF) of the Lower Yellow River (LYR), which considers instream ecological base flow, survival and reproduction of indicator fish species, equilibrium of erosion and siltation and ecological function of the estuary, was constructed by integrating hydrological, hydraulic and ecological habitat methods. The framework contains three crucial components - determination of instream EWRs and estuarine EWRs, uncertainty analysis of hydro-ecological tools. For instream ecological base flow, we proposed an improved Tennant method, which took into account both seasonality and sediment transport characteristics of the LYR, and could better reflect the actual hydrological regime. For the hydrological ecological response relationship of indicator fish species, we estimated the uncertainty of the model output of River2D to improve its credibility of the simulation results. The results demonstrated that: 1) Two-grade intra-annual monthly EWRs process of suitable and minimum for four instream sections and estuary area were obtained. The flood season (June-October) is the period with the largest proportion of intra-annual instream EWRs, whereas in estuary area, is the spawning period (April-July) of dominant species. 2) The uncertainty of HSI curves directly leads to the uncertainty of model output. Although the shape and position of the WUA curve can be uncertain, it does not affect the judgment of EWRs threshold. 3) The research results can provide scientific basis for water resource management decision-making in the LYR. Additionally, the ideas also have reference significance for similar basins., 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.)

Arid area is very sensitive to global warming and are extremely vulnerable to climate change. Moreover, the water resources system in the arid area is fragile and will undergo tremendous changes with climate change. Therefore, the interaction of climate and hydrology in arid area has an important impact on the formation of regional microclimate and hydrological changes. Daihai Lake is a typical closed inland lake in arid area of China, and a key area for ecological protection in North China. In this paper, WRF-Hydro model is used to simulate the climate hydrological coupling situation of Daihai Basin from 1980 to 2020, and the coupling results are verified and calibrated by meteorological statistics, runoff calculation and remote sensing analysis. Based on the synopsis of climate and hydrology in the past 40 years, the causes and future trends of the hydrological elements in Daihai Basin are analyzed. Through the analysis, it is found that the interannual variation of precipitation in Daihai Basin is sharp, with 401.75 mm as the average from 1980 to 1994; and drastic fluctuations from 1995 to 2011, with a difference of nearly 400 mm between the interannual maximum and minimum; From 2012 to 2020, the fluctuation is small. Although the interannual variation of evaporation fluctuated, it showed an upward trend with a slope of 8.855 mm/year. The annual average temperature showed an obvious upward trend with a slope of 0.040 °C/year. From 1980 to 2020, the inflow of Daihai Lake shows a downward trend; Since 2013, the runoff into the lake has tended to be flat. Climate change and human activities are the decisive factors leading to the change of water quantity in Daihai, among which human activities play a greater role. Cultivated land irrigation and industrial water use are highly correlated with the lake discharge, and these two factors have a great influence on the lake discharge. If the current agricultural and industrial water consumption does not increase, Daihai still has a lifespan of nearly 120 years. If human activities do not change and any protective measures are not taken in time, under the background of global climate change, the flow of the Daihai Lake into the lake will be reduced to zero in 2025, and the Daihai Lake will completely dry up in 2031-2033. The study of climate hydrological coupling of long time series in Daihai Basin can not only make up for the lack of runoff data, but also provide the basis for water resources management, disaster prevention and mitigation., (© 2022. The Author(s).)

Urban stormwater management measures, such as permeable pavement systems (PPSs), have been widely implemented to alleviate increasingly severe urban water-related problems. However, the effectiveness of PPSs in runoff control under different rainfall conditions has not been fully investigated, particularly in China. Therefore, there is an urgent need to study the hydrological benefits of different PPSs in China. In this paper, five PPSs at the Zhenjiang sponge base, including one pervious concrete (PC), two permeable interlocking concrete pavements (PICP1 and PICP2), and two permeable bricks (PB1 and PB2), were selected as study cases. Surface runoff coefficients, underdrain runoff coefficients, total runoff volume reductions, and peak flow reductions during rainfall events throughout the flood seasons of 2019 and 2020 were calculated. The influence of rainfall characteristics, pavement type, and pavement age on PPS hydrological performance were evaluated by statistical analyses (p<0.05). The results revealed that the average values of surface runoff coefficients, underdrain runoff coefficients, total runoff volume reductions, and peak flow reductions by the PPSs were approximately 0.025, 0.003, 98.1%, and 96.4%, respectively, in 2019 and changed to 0.045, 0.001, 96.3%, and 92.4%, respectively, in 2020. PC performed best with regard to surface runoff control at the initial stage of operation, followed by PB and PICP. Both rainfall depth and rainfall intensity had a significant correlation with each hydrological performance metric. The increase in surface runoff generation from 2019 to 2020 mainly resulted from the clogging problem, which was closely related to pavement type and surroundings of PPSs. PB performed better than PC and PICP in terms of sustainable hydrological performance. The results provide a scientific reference for the design, construction, and operation of PPSs and can aid with the sustainable construction of sponge cities in China. This study evaluated the runoff reduction performance of five PPSs under natural rainfall events, which were observed during the flood seasons of 2019 and 2020 in Zhenjiang, Yangtze River Delta of China. In total, approximately 96% of the rainfall was captured by the PPSs during the monitoring period, and the PPSs performed better in lower-intensity rainfall events. However, the runoff reduction performance of the PPSs decreased markedly with operation time due to clogging, which is closely related to the pavement type and site surroundings of the PPS. To maintain the function of PPS for runoff control in a long period of time, the permeable brick system is the best type of PPS compared with PC systems and PICP systems. The results indicated that the application of PPSs in sponge city construction could be beneficial in the mitigation of urban floods, and adequate attention should be paid to the clogging problem of PPSs at every stage of PPS design, construction, and operation. [ABSTRACT FROM AUTHOR]

With the rapid growth of population and economy, shortage and mismatch of land and water resources have deepened the need for cropping pattern optimization. In the context of the sustainable development of agriculture, cropping pattern optimization should not only pursue economic benefits, but the consequent environmental effects also deserve equal attention. Meanwhile, climate change increases the complexity of balancing conflicts of economic-environmental system by cropping pattern optimization. Therefore, this paper builds a multi-objective programming model for Economic-Environmental Synergistic Optimization for Cropping Pattern under Climate Change (EESO-CP-CC) model, with the goals of economic benefit increment and environmental pollutants emission reduction. The EESO-CP-CC model couples a non-point source pollution input-output model, a one-dimensional water quality model and an economic benefit function into an integrated framework. Fuzzy method was used to solve the optimization model, and the stochastic uncertainty of water supply under climate change was quantified by the integration of Bayesian approach and interval linear regression. The model was applied to Jinxi Irrigation District (JXID) in Heilongjiang Province, northeast of China. Results show that by adjusting the acreage of rice, corn and soybean, the harmony degree of economy-society-environment system increased by 10.7% compared to the current situation, indicating that the model tends to achieve the best possible economic benefits while ensuring the environmental effects. Compared with actual cropping pattern, the pollutants emissions reduced by 24.7% and 3% from corn and soybean, respectively. However, this led to a decrease of economic benefit by 8% in exchange, showing the trade-off between environmental pollution reduction and economic benefits improvement. The output coefficients of nitrogen and phosphorus pollutants were optimized, with the optimal output reducing by 20% compared to the standard. Cropping pattern and water resources allocation vary with different climate change conditions, however, the amplitude of variation is modest, indicating that the model can cope well with the changing environment. The developed model can help achieve synergistic development of economic benefits and environmental effects, and thus promote sustainable development of irrigation areas, and improve the coping capacity of agricultural water and land under climate change, by cropping pattern optimization and planning., 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 © 2021 Elsevier B.V. All rights reserved.)

Drought incidents and the pressure on water resources have increased in recent years, which has threatened sustainable development. Recently, research has been conducted on drought propagation. However, few studies have investigated the characteristics and mechanisms of drought propagation in plateau mountainous regions with complex topography, which limits the efforts to mitigate drought. We used the Longchuan River Basin (LRB) in Southwest China as a case study to analyze the spatiotemporal variations of meteorological, hydrological, and agricultural droughts and the process of drought propagation in plateau mountainous regions. Our results demonstrated that: (1) the variation in the intensity, frequency, and coverage of droughts indicated that meteorological droughts and hydrological droughts were increasingly serious, while agricultural droughts were eased from 2000 to 2015; (2) the propagation time between different types of droughts was approximately 2 months; and (3) the propagation sequences of droughts varied by altitude; in particular, agricultural droughts propagated to hydrological droughts at higher altitudes, and the opposite occurred at lower altitudes. We concluded that elevation plays a critical role in the time-space differentiation of drought propagation in plateau mountains. More attention should be paid to the spatial differentiation of drought propagation based on land use under different topographic conditions. The results of this study can provide a new perspective for future drought propagation studies., 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 © 2021 Elsevier B.V. All rights reserved.)

Quantifying the climatic and anthropogenic effects on hydrological processes has received considerable attention. However, diverse conclusions could be drawn when different models and forcing datasets are used. This is particularly uncertain and challenging in poorly gauged arid regions. Here we aim to tackle this issue in the poorly gauged Xiangride River Basin within the Qaidam Basin, one of the three prominent inland basins in China. We applied two distinct models (Budyko Mezentsev-Choudhurdy-Yang and process-based SWAT) to a poorly-gauged inland basin in West China. The model simulations were driven by four precipitation products including Tropical Rainfall Measuring Mission (TRMM) 3B42 V7, Global Precipitation Measurement (GPM) IMERG V6, Multi-Source Weighted-Ensemble Precipitation (MSWEP) and China Meteorological Assimilation Driving Datasets (CMADS). Our results indicate that MSWEP performed best (NSE = 0.64 vs. 0.36-0.59 for other datasets) in the baseline period (2009-2012), whereas CMADS was more accurate during the impacted period (2013-2016); CMADS and GPM might underestimate the precipitation in the baseline and impacted period, respectively. Hydrological processes during the impacted period are presumed to be influenced by climate variation and/or human activities, compared to the relatively natural status in the baseline period. We conclude that runoff decline between the two periods was mainly affected by human activities (-66 to 94%), whereas the contribution of climate variation was more likely positive. A literature survey reveals that major anthropogenic effects in the study area includes reservoir, road construction and cropland expansion that could lead to runoff decrease. We recommend the use of process-based model (e.g., SWAT) in studies like this, as process-based models driven by high-quality remote-sensed or reanalysis climate datasets, better represents the spatiotemporal hydrological change under altered conditions, whereas the steady-state assumption of soil water for the Budyko model may not be fully satisfied during a short period., 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 © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

In order to make the sponge city construction model more consistent with the inherent characteristics of the city, this paper constructs classification of the sponge city construction index system. We carry out multivariate statistical and cluster analysis based on geographic information system (GIS) and classify the different regions of mainland China, putting forward key points of construction for different types of regions. The results show that climatic factor, hydrological factor and soil factor are the main factors affecting sponge city construction, followed by city scale and level of urban economic development; the third is underlying surface type and geomorphological type. The cities are classified into ten clusters, and they present a continuously zonal or flaky distribution from northeast to southwest on the whole; more than 80% of cities obviously present a continuously zonal or flaky distribution. Each of the nine clusters has at least one pilot city, which can be used as a reference for construction.

In water ecosystems, zoobenthos are one of the most important communities. Maintenance of healthy zoobenthos community is essential for water ecosystems remediation. Understanding the hydrology and water quality factors that drive the variation of zoobenthos is the priority for water ecosystems remediation. The present study used canonical correlation analysis to select the main habitat factors affecting zoobenthic communities based on field sampling of the river zoobenthos in the first pilot city for the construction of civilized water ecosystems in China—Jinan City. In addition, analysis was performed based on geoscience methods of Global Moran's I and Anselin local Moran's I spatial autocorrelation of main habitats factors. The results show that the key water quality physical factors affecting Jinan City zoobenthic communities were pH and conductivity; the key water quality chemical factors were K+, Na+, and permanganate index; and the key hydrological factor was water depth. The sodium ions and conductivity exhibited significant spatial autocorrelation in all seasons. And the regions exhibiting spatial autocorrelation were generally stable. Moreover, the characteristics of benthic animals are closely related to human activities of domestic sewage discharge in the central and agricultural activities in northern parts of the study area. All methods in this paper can be extended to the researches on other communities, for example, algae, zooplankton, and fish in water ecosystems. The methods and results in the paper can provide significant references for managers to protect and restore degraded water ecosystems in global water. [ABSTRACT FROM AUTHOR]

Quantitative analysis of the contribution rate of China’s hydraulic science and technology and analysis of the underlying reasons behind changes provide an important foundation upon which the government can formulate water policies. This paper abandons the assumption of a scale economy and separates the changes of benefits brought about by the scale from scientific and technological progress, thus changing the C-D production function from linear to nonlinear. Based on a feedforward neural network, it calculates the coefficient of the output elasticity, the economic contribution rate of China’s hydraulic science and technology and the scale economies for each year using relevant data from 1981 to 2016. The results show that (1) the average contribution rate of capital investment from 1981 to 2016 was 47.3%, and the average contribution rate of labor from 1981 to 2016 was 9.1%. It is not obvious that the significant increase in the labor force has contributed to the growth of China’s water conservancy industry. (2) The average contribution rate of scale economies in 1981–2016 was 26.7%, and the contribution rate of scale economies is negatively correlated with the capital contribution rate. (3) The average contribution rate of China’s hydraulic science and technology was 43.6% from 1981 to 2016, and the average contribution rate of the total factor productivity after removing scale economies from 1981 to 2016 was 16.9%. During the period of the 6th Five-Year Plan(1981~1985), the contribution rate of water conservancy science and technology was relatively high. Since that time, it has remained at 40%. In recent years, as water conservancy reforms in key areas have made positive progress, scientific and technological progress has increased the growth of water conservancy benefits annually. [ABSTRACT FROM AUTHOR]

Modern geodetic technologies, including high-precision ground-based gravity measurements, satellite gravimetry, satellite altimetry, Global Navigation Satellite Systems (GNSS), and Interferometric Synthetic Aperture Radar(InSAR), offer a wealth of observations for monitoring global hydrological processes with exceptional accuracy and spatio-temporal resolutions. Mass redistribution and Earth's surface deformation over land related to global and regional water cycling can be inferred from modern gravimetry, altimetry, GNSS, and InSAR techniques. Hydrogeodesy becomes an emerging field of geodesy aiming to analyze the changes of water in the Earth system. The paper introduces the China's advances in hydrogeodesy in recent years. It brings together multiple geodetic teams' work from China, showcasing the application of modern geodetic technologies in the field of hydrology, including research on terrestrial water storage, groundwater storage, glaciers/ice sheets, and reservoir water storage. [ABSTRACT FROM AUTHOR]

The impacts of human activities on hydrological connectivity disturb the network topology of transport paths, which has gradually evolved from natural terrain features to dual natural-artificial features. In this study, a new framework is proposed to extract information from natural-artificial transport paths and related hydrological connectivity dominated by agricultural practices and ditch networks. Graph theory and connectivity indexes are integrated for the comprehensive classification and the parallel processing of potential flow transport networks and their upstream drainage areas. Based on high-resolution remote sensing data and detailed field investigations, this new framework, which combines graph theory and connectivity indexes, is applied to a typical agriculture-intensive catchment in China. The results show that artificial factors greatly influence the transport paths and the related drainage areas. With the development of ditch construction, the hydrological transport paths become shorter and more fragmented. In addition, key ditch segments are identified by connectivity indexes, and recommendations are given for future planning. This new framework offers an approach for the hydrological connectivity analysis of complex networks and provides effective strategies for agricultural development., Competing Interests: Declaration of Competing Interest All 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 © 2021 Elsevier Ltd. All rights reserved.)

Due to human activity and global climate change, the Yellow River Delta, the youngest delta wetland in China, is suffering serious degradation. The study of hydrological connection provides new perspectives and technical support for the protection and restoration of delta wetlands. To quantify the interaction between the hydrological connection and the root-soil complex, the current study took dye-tracing experiments to examine the small-scale hydrological connectivity in soil where Phramites australis grew. The dye coverage was selected as the indicator of hydrological connectivity after preliminary analysis in this study. The main results were that (1) the strength of hydrological connectivity was negatively related to the microaggregates content, but had little to do with other soil physical properties; (2) there was a notable positive correlation between the indexes of thick root (D > 5 mm) and the dye coverage hydrological connectivity, while root biomass had little effect on hydrological connectivity; and (3) the influence of the microaggregate content dominated in the combined effect of the total surface area of the root (D > 5 mm) and the microaggregate content on hydrological connectivity in each soil layer., 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 © 2020 Elsevier Ltd. All rights reserved.)

China is facing severe pressure on its water resources and water environments. Calculating the industrial water efficiency of each province is an important index for the central government to evaluate local governments. In the traditional water resources evaluation index, the industrial water use efficiency and pollutant discharge are evaluated separately. In this paper, we collected industrial input data, output data and pollutant discharge data with a four-stage data envelopment analysis to calculate China's industrial water use efficiency with and without considering pollutant discharge, and then analyzed the factors influencing the industrial water use efficiency. The results show that the eastern coastal provinces of China have the highest water use efficiency and are less affected by pollutant discharge than other provinces. The industrial water use efficiency of the central and western provinces is lower than that of the other provinces, and the industrial water use efficiency in the central provinces is greatly affected by pollutant discharge. Factor endowment, economic development level, scientific and technological progress, industrial structure, proportion of foreign investment, water consumption per 10000 yuan of value-added by industry, industrial sewage treatment capacity and educational investment have a significant influence on the industrial water use efficiency of China. We suggest that the government strengthen the construction of sewage plants and other related infrastructure in central provinces when conducting the industrial transfer of heavy polluting enterprises. [ABSTRACT FROM AUTHOR]

This paper explores the relationship between vegetation in the Liangzhou Oasis in the Upper Shiyang River watershed (USRW) of west-central Gansu, China, and within-watershed precipitation, soil water storage, and oasis self-support. Oases along the base of the Qilian Mountains receive a significant portion of their water supply (over 90%) from surface and subsurface flow originating from the Qilian Mountains. Investigation of vegetation control on oasis water conditions in the USRW is based on an application of a process model of soil water hydrology. The model is used to simulate long-term soil water content (SWC) in the Liangzhou Oasis as a function of (i) monthly composites of Moderate Resolution Imaging Spectroradiometer (MODIS) images of land surface and mean air temperature, (ii) spatiotemporal calculations of monthly precipitation and relative humidity generated with the assistance of genetic algorithms (GAs), and (iii) a 80-m-resolution digital elevation model (DEM) of the area. Modeled removal of vegetation is shown to affect within-watershed precipitation and soil water storage by reducing the exchange of water vapor from the land surface to the air, increasing the air’s lifting condensation level by promoting drier air conditions, and causing the high-intensity precipitation band in the Qilian Mountains to weaken and to be displaced upward, leading to an overall reduction of water to the Liangzhou Oasis. [ABSTRACT FROM AUTHOR]

Taking two typical rivers in high mountains and steep gorge areas as example, this paper analyzes the spatiotemporal variability of the eco-hydrological characteristics and the driving forces leading to changes. Firstly, based on the species-environmental data processing, this paper adopts canonical correspondence analysis (CCA) method to identify the environmental factors influencing the distribution of river bank vegetation. Secondly, this study uses the ecological diversity index to represent the spatiotemporal variability of ecological characteristics. Thirdly, this paper uses the multiple correlation method to analyze the relationship between the hydrological factors and meteorological factors, and to identify the key factors leading to the hydrological regime changes. At last, based on the analysis of basin water quality data, this paper analyzes the regularity of spatiotemporal variability and its driving forces. By the systematic analysis on the outcome, we could get that the spatiotemporal distribution of eco-hydrological characteristics shows the regular changes from the upstream to downstream (from the north to the south), and the spatiotemporal variability of eco-hydrological characteristics is typical from the east to the west. Altitude, aspect and water distribution are the primary natural driving forces leading to the spatiotemporal variability of eco-hydrological characteristics; and exploitation and operation of hydroelectric power station, construction of road on the river bank, and basin land utilization are the main human driving forces. [ABSTRACT FROM AUTHOR]

West Dongting Lake in China is important for human livelihoods and habitat of migratory waterfowl and other wildlife. The waterway re‐engineering and agriculture intensification have contributed to changes in hydrology, sediment, and vegetation on the floodplain. This paper describes an EcoPartnership program conducted by the U.S. Geological Survey, Wetland and Aquatic Research Center, and Beijing Forestry University. It focused on the development of a wetland ecosystem network in West Dongting Lake with technical support from the U.S. partner using a number of related studies to examine wetland vegetation dynamics from upstream to downstream along the tributaries. The results of U.S. studies showed that the regeneration potential of species might be altered by changes in climate and local environment, and seed bank depletion by germination may be a major conservation threat in a future with recurring droughts in swamps of the southeastern United States. In the monsoonal wetlands of West Dongting Lake, the soil seed bank could be used as a seed source for revegetation after hydrologic restoration with the introduction of certain foundational species and the removal of poplar plantations. Also, West Dongting Lake is at high ecological risk of mercury pollution. Wetland ecosystem monitoring may allow managers to use the information to predict effects of climate change, water level and flow changes on sedimentation, and to manage for desired vegetation to support waterfowl and ecosystem services. The cooperation of two countries through the EcoPartnership program is now well established and poised for extensive research projects in the future. [ABSTRACT FROM AUTHOR]

Based on field survey in the southwestern Yellow Sea (SWYS) during April-September 2017, the spatiotemporal variations in the hydrological characteristics and nutrient conditions were coupled and analyzed; the intra-seasonal variations in the upwelling in the front of the Yellow Sea Cold Water Mass (YSCWM) and impacts on nutrient transport were explored. The coastal area was controlled by the low-salinity high-nutrient Lubei Coastal Current, Subei Coastal Current, and Yangtze River Diluted Water from north to south; at bottom, the northeastern SWYS was controlled by the low-temperature high-salinity high-nutrient YSCWM. Temperature, salinity and nutrient fronts formed around YSCWM. The upwelling velocity in the front increased during April to late June and decreased in early September; the upwelled fluxes of dissolved inorganic nitrogen (0.29×10 3 -7.77×10 3 μmol·m -2 d -1 ), phosphate (0.02×10 3 -0.27×10 3 μmol·m -2 d -1 ) and silicate (0.98×10 3 -8.75×10 3 μmol·m -2 d -1 ) showed similar variations during April-September. The upwelled nutrients could potentially contribute to local green tide development and phytoplankton growth during spring-summer., 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 © 2020 Elsevier Ltd. All rights reserved.)

The stationarity of observed hydrological series has been broken or destroyed in many areas worldwide due to changing environments, causing hydrologic designs under stationarity assumption to be questioned and placing designed projects under threat. This paper proposed a data expansion approach-namely, the cross-reconstruction (CR) method-for frequency analysis for a step-changed runoff series combined with the empirical mode decomposition (EMD) method. The purpose is to expand the small data on each step to meet the requirements of data capacity for frequency analysis and to provide more reliable statistics within a stepped runoff series. Taking runoff records at three gauges in western China as examples, the results showed that the cross-reconstruction method has the advantage of data expansion of the small sample runoff data, and the expanded runoff data at steps can meet the data capacity requirements for frequency analysis. In addition, the comparison of the expanded and measured data at steps indicated that the expanded data can demonstrate the statistics closer to the potential data population, rather than just reflecting the measured data. Therefore, it is considered that the CR method ought to be available in frequency analysis for step-changed records, can be used as a tool to construct the hydrological probability distribution under different levels of changing environments (at different steps) through data expansion, and can further assist policy-making in water resources management in the future.

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 km 2 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., (Copyright © 2019. Published by Elsevier Ltd.)

China produced 17.1 billion cubic meters (BCM) of methane sourced from coal seams in 2015, of which 4.43 BCM is from wells drilled from the surface. This level of production is a clear indicator that China has gone into early stage large-scale coalbed methane (CBM) development. CBM resources in China have been extensively investigated since the 1980s. Research has focused on the geological controls of reservoir character. There have been significant advances over the last 37 years that have aided China’s CBM industry. CBM resources less than 2000 m in depth in China are estimated to be 36.81 trillion cubic meters, of which more than 84% occur in nine large-scale basins, such as the Qinshui, Ordos, Junggar, Qianxi, Erenhot, and Hailar. CBM accumulation and coal reservoir characteristics are controlled by the deposition, structure, coal rank, hydrology as well as other geological factors. Each basin has its own unique geological controls that influence the character of CBM reservoirs in both subtle and obvious ways. Coal reservoir geology in some basins or regions in China are still not well understood because of the complexity of the geological settings. At present, large-scale CBM production in China only occurs within the Qinshui and Ordos basins, mostly sourced from middle-to-high rank coal reservoirs. The CBM geology in other basins needs further investigation in order to achieve large-scale commercial production. To this end, the geological research in the paper should address issues such as how to stimulate economic gas flow from deep low permeability reservoirs and how best to efficiently produce from multiple horizons simultaneously. This paper summarizes these and other key issues that are significant scientific and technical challenges for the CBM industry within China. [ABSTRACT FROM AUTHOR]

The post-earthquake debris flows in the Wenjia Gully led to the exposure of the shortcomings in the design of the original conventional debris flow mitigation system. A predicament for the Wenjia mitigation system is a large amount of loose material (est. 50 × 10 m) that has been deposited in the gully by the co-seismic landslide, providing abundant source material for debris flows under saturation. A novel design solution for the replacement mitigation system was proposed and constructed, and has exhibited excellent performance and resilience in subsequent debris flows. The design was governed by the three-phase philosophy of controlling water, sediment, and erosion. An Early Warning System (EWS) for debris flow that uses real-time field data was developed; it issues alerts based on the probabilistic and empirical correlations between rainfall and debris flows. This two-fold solution reduces energy of the debris flow by combining different mitigation measures while minimizing the impact through event forecasting and rapid public information sharing. Declines in the number and size of debris flows in the gully, with increased corresponding rainfall thresholds and mean rainfall intensity-duration ( I- D) thresholds, indicate the high efficacy of the new mitigation system and a lowered debris flow susceptibility. This paper reports the design of the mitigation system and analyzes the characteristics of rainfall and debris flow events that occurred before and after implementation of the system; it evaluates the effectiveness of one of the most advanced debris flow mitigation systems in China. [ABSTRACT FROM AUTHOR]

The Gezhouba Reservoir (GR) and Three Gorges Reservoir (TGR) are the two largest water-storage projects in the middle reach of the Yangtze River. The impoundments of the reservoirs have changed natural flow-regimes in the river. This paper uses the Yichang Hydrological Station as a proxy for water-storage projects along the Yangtze River to assess alterations in river-flow conditions in three separate periods. The periods coincide with the start of water storage in the GR and TGR. The ecohydrological conditions in the river system are assessed based on annual discharge, water level, water temperature, and suspended-sediment concentration. More importantly, the entire analysis is done in relation to the Chinese sturgeon species, which face the danger of extinction in the Yangtze River. Based on the research reported in this paper, the impoundment of the GR and TGR increases downstream average annual water-temperature. In contrast, it decreases downstream average annual runoff, water level, and suspended-sediment concentration. The change of hydrological conditions negatively influences the spawning and hatching conditions of Chinese sturgeon. This change is the key reason that causes the fertilized rate of Chinese sturgeon eggs to decline. [ABSTRACT FROM AUTHOR]

Rainfall infiltration in unsaturated slopes alters the effective stress through pore water pressure changes, thus causing ground deformation. Although important to assess the timescale over which the margin of safety of a slope decreases, such coupled processes are rarely accounted in the context of spatially distributed hazard assessment procedures. In this paper, a physically based, spatially distributed model accounting for full hydro-mechanical coupling is discussed. The model relies on a vectorized finite element (FE) solver to calculate the stability of deformable unsaturated infinite slopes subjected to transient flow. First, the FE solver is used to study the response of individual slopes to a prolonged rainfall for three scenarios (i.e., rigid, swelling, and collapsible soil). Then, the model is used in the context of spatially distributed computations to assess spatiotemporal variations of factor of safety over a large area. For this purpose, a series of shallow landslides occurred in a mountainous landscape covered by collapsible loess deposits in northwestern China was used as test site. The analyses show that hydro-mechanical couplings affect the performance of the model in terms of computed failure time and areal extent of the unstable zones. Specifically, volume collapse due to suction decrease is found to reduce the time of failure compared with uncoupled computations obtained for a rigid soil scenario. The most substantial advantages of using coupled analyses have been reported with reference to gentle slopes, for which the higher rate of suction reduction driven by volume change was crucial to capture landslide source areas that would otherwise be overlooked by uncoupled analyses. The proposed methodology offers a complete tool for landslide hazard assessment, in that it incorporates sources of coupling between hydrology and mechanics that are crucial to replicate the physics of landslide initiation. [ABSTRACT FROM AUTHOR]

A dataset of landslides from Sichuan Province in China, containing 1551 historical individual landslides, is a result of two teams' effort in the past few years to map the susceptibility to landslides. Considering complex internal relations among the triggering factors, logistic regression (LR) and shallow neural networks, such as back-propagation neural network (BPNN), are often limited. In this paper, we make a straightforward development that the deep belief network (DBN) based on deep learning technology is introduced to map the regional susceptibility to landslides. Seven factors with respect to geomorphology, geology and hydrology are considered and verified through the collinearity test. A DBN model containing three pre-trained layers of restricted Boltzmann machines by stochastic gradient descent method is configured to obtain the susceptibility to landslides. Susceptibility results evaluated by DBN model are compared with those by LR and BPNN in the receive operator characteristic (ROC) analysis, showing that DBN has a better prediction precision, with a lower rate of false alarms and fake alarms. The case study also indicates different sensitivities of the triggering factors to the landslide susceptibility, that the factors of altitude, distance to drainage network and average annual rainfall have significant impact in mapping the susceptibility to landslides in the region. This research will contribute to a better-performance model for regional-scale mapping for the susceptibility to landslides, in particular, at the area where triggering factors show complex relations and relative independence. [ABSTRACT FROM AUTHOR]

This paper proposes an asymmetric benefit compensation model for stimulating rational agents, who often have disparate geography, hydrology, climate, and socio-economies, to participate in cooperative transboundary water management. A social planner model is initially developed to maximize the total water benefit of a river system under the assumption of perfect cooperation among the agents. Subsequently, a Stackelberg game-theoretical model is used to derive the agents' disagreement utility based on considering their spatial heterogeneity in water accessibility. Based on the agents' bargaining weights produced by several multi-attribute decision analysis methods, the aggregate water benefit is then redistributed among the agents by adopting the asymmetric Nash bargaining solution. The possible benefit compensation solutions are finally compared by using a composite index that can synthetically consider optimality, equity and stability criteria. The Qujiang River Basin in China is used to demonstrate the applicability of the suggested model. The results show that this integrated model can offer useful insights for conflict resolution in river sharing problems. [ABSTRACT FROM AUTHOR]

Meeting landscape environmental water demand is one of the necessary conditions for realizing the stability and sustainablity of landscape environment. According to the characteristics of medium and small rivers in the northern cities, based on the river function, the concept of landscape environmental water demand was proposed, also its calculation method is studied in this paper. The landscape environmental water demand for medium and small rivers in the northern area can be divided into two parts according to the river functional types: environmental water demand and landscape water demand. To environmental water demand, according to river function, hydrological characteristics and water resources in different periods, the method to calculate the water demand by stages is put forward in the paper. Then integrating with landscape water demand, the landscape environmental water demand is calculated. Taking Shenyang Pu River ecological corridor as an example, it is divided into 9 sections combined with practical application and the landscape environmental water demand is calculated by the partition and staging. The results show that the landscape environmental water demand of Pu River ecological corridor is 6749.56x104 m³/year. [ABSTRACT FROM AUTHOR]

• A revised temperature model is built to study the thermal stratification. • The reservoir has a reverse thermal stratification and two overturning in a year. • Low water level can weaken the stability and lengthen the spring overturning. • High inflow volume can strength the stability and defer the spring overturning. Thermal structure plays a significant role in the aquatic ecosystem of reservoirs. In this paper, thermal structure of a large reservoir for water supply in northeast China has been studied. Considering the reservoir has a 150 days icebound period and the ice cover can affect the heat transfer process, we built a revised numerical simulation model based on EFDC to study the temporal and spatial variation of thermal stratification. The absolute mean error (AME) and mean absolute relative error (MARE) between modeled and observed water temperature are 0.40 °C and 7.15%, respectively. The results indicate that the validated model can successfully reproduce the temporal and spatial variation of water temperature. The model results indicate that the reservoir has a reverse thermal stratification in icebound season and there are two over-turning events in a year. Six hypothetical scenarios including the extreme change in the air temperature, inflow discharge, and the water level had been built to quantify the influences of changes in climate and hydrology conditions on the thermal structure. This paper provides a simplified method for the simulation of the water temperature in the reservoir with an icebound season, which can provide a reference for other reservoirs. [ABSTRACT FROM AUTHOR]