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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.)

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.)

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.)

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]

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.

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).)

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.

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]

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]

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.)

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]

Depth to bedrock influences or controls many of the Earth's physical and chemical processes. It plays important roles in soil science, geology, hydrology, land surface processes, civil engineering, and other related fields. However, information about depth to bedrock in China is very deficient, and there is no independent map of depth to bedrock in China currently. This paper describes the materials and methods to produce high-resolution (100 m) depth-to-bedrock maps of China. For different research and application needs, two sets of data are provided for users. One is the prediction by the ensemble of the random forests and gradient boosting tree models, and the other is the prediction and the uncertainty of prediction based on quantile regression forests model. In comparison with depth-to-bedrock maps of China extracted from previous global predictions, our predictions showed higher accuracy and more spatial details. These data sets can provide more accurate information for Earth system research compared with previous depth-to-bedrock maps. Measurement(s) depth Technology Type(s) computational modeling technique Factor Type(s) biomass yield • slope • wetness • rock type • soil type • geographic location Sample Characteristic - Environment land Sample Characteristic - Location China Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11358929 [ABSTRACT FROM AUTHOR]

The deterioration of water quality has become a primary environmental concern worldwide. Understanding the status of water quality and identifying the influencing factors are important for water resources management. However, reported analyses have mostly been conducted in small and focused areas. It is still unclear if factors driving spatial variation in water quality would be different in extended spatial scales. In this paper, we analyzed spatial pattern of inland surface water quality in China using a dataset with four water quality parameters (i.e., pH, DO, NH4+-N and CODMn) and the water quality level. We tested the effects of anthropogenic (i.e., land use and socio-economic) and natural (i.e., climatic and topographic) factors on spatial variation in water quality. The study concluded that the overall inland surface water quality in China was at level III (fair). Water quality level was strongly correlated with CODMn and NH4+-N concentration. In contrast to reported studies that suggested land use patterns were the determinants of inland surface water quality, this study revealed that both anthropogenic and natural factors played important roles in explaining spatial variation of inland surface water quality in China. Among the tested explanatory variables, mean elevation within watershed appeared as the best predictor for pH, while annual precipitation and mean air temperature were the most important explanatory variables for CODMn and DO, respectively. NH4+-N concentration and water quality level were most strongly correlated with the percent of forest cover in watershed. Compared to studies at smaller spatial scales, this study found different influencing factors of surface water quality, suggesting that factors may play different roles at different spatial scales of consideration. Therefore management policies and measures in water quality control must be established and implemented accordingly. Since currently adopted parameters for monitoring of inland surface water quality in China are largely influenced by natural variables, additional physicochemical and biological indicators are needed for a robust assessment of human impacts on water quality. [ABSTRACT FROM AUTHOR]

This paper demonstrates the impact of an endemic fossorial animal, plateau pika (Ochotona curzoniae), on soil properties and N2O flux at the Zoige Wetland. Pika burrow and control sites without disturbance by pika were selected to measure the soil water content, bulk density, soil organic matter (SOM), NH4-N content and NO3-N content in August 2012. N2O fluxes were measured with static opaque chambers at these sites in June and August 2012. Pika burrowing altered soil aeration by transferring deeper soil to the surface and by constructing underground burrows, which significantly increased bulk density, and reduced soil water content, SOM and NH4-N content at 0–10 cm and 10–20 cm soil depth. N2O flux had a significant correlation with bulk density, SOM and NH4-N content. Pika burrowing significantly influenced N2O flux by increasing N2O flux at the control site from near zero to 0.063±0.011 mg m-2 h-1. Our findings described how pika burrowing influences the soil traits and significantly increases the principal greenhouse gas N2O emission. As plateau pika was commonly considered as a pest, our findings give a novel clue to effectively manage populations of plateau pika on the Qinghai-Tibet Plateau from the perspective of greenhouse gas emission. [ABSTRACT FROM AUTHOR]

Catastrophic flooding resulting from extreme meteorological events has occurred more frequently and drawn great attention in recent years in China. In coastal areas, extreme precipitation and storm tide are both inducing factors of flooding and therefore their joint probability would be critical to determine the flooding risk. The impact of storm tide or changing environment on flooding is ignored or underestimated in the design of drainage systems of today in coastal areas in China. This paper investigates the joint probability of extreme precipitation and storm tide and its change using copula-based models in Fuzhou City. The change point at the year of 1984 detected by Mann-Kendall and Pettitt’s tests divides the extreme precipitation series into two subsequences. For each subsequence the probability of the joint behavior of extreme precipitation and storm tide is estimated by the optimal copula. Results show that the joint probability has increased by more than 300% on average after 1984 (α = 0.05). The design joint return period (RP) of extreme precipitation and storm tide is estimated to propose a design standard for future flooding preparedness. For a combination of extreme precipitation and storm tide, the design joint RP has become smaller than before. It implies that flooding would happen more often after 1984, which corresponds with the observation. The study would facilitate understanding the change of flood risk and proposing the adaption measures for coastal areas under a changing environment. [ABSTRACT FROM AUTHOR]

The solid Earth deforms elastically in response to variations of surface atmosphere, hydrology, and ice/glacier mass loads. Continuous geodetic observations by Global Positioning System (CGPS) stations and Gravity Recovery and Climate Experiment (GRACE) record such deformations to estimate seasonal and secular mass changes. In this paper, we present the seasonal variation of the surface mass changes and the crustal vertical deformation in the South China Block (SCB) identified by GPS and GRACE observations with records spanning from 1999 to 2016. We used 33 CGPS stations to construct a time series of coordinate changes, which are decomposed by empirical orthogonal functions (EOFs) in SCB. The average weighted root-mean-square (WRMS) reduction is 38% when we subtract GRACE-modeled vertical displacements from GPS time series. The first common mode shows clear seasonal changes, indicating seasonal surface mass re-distribution in and around the South China Block. The correlation between GRACE and GPS time series is analyzed which provides a reference for further improvement of the seasonal variation of CGPS time series. The results of the GRACE observations inversion are the surface deformations caused by the surface mass change load at a rate of about -0.4 to -0.8 mm/year, which is used to improve the long-term trend of non-tectonic loads of the GPS vertical velocity field to further explain the crustal tectonic movement in the SCB and surroundings. [ABSTRACT FROM AUTHOR]

Coal mining is one of the core industries that contribute to the economic development of a country but deteriorate the environment. Being the primary source of energy, coal has become essential to meet the energy demand of a country. It is excavated by both opencast and underground mining methods and affects the environment, especially hydrological cycle, by discharging huge amounts of mine water. Natural hydrological processes have been well known to be vulnerable to human activities, especially large scale mining activities, which inevitably generate surface cracks and subsidence. It is therefore valuable to assess the impact of mining on river runoff for the sustainable development of regional economy. In this paper, the impact of coal mining on river runoff is assessed in one of the national key coal mining sites, Gujiao mining area, Shanxi Province, China. The characteristics of water cycle are described, the similarities and differences of runoff formation are analyzed in both coal mining and pre-mining periods. The integrated distributed hydrological model named MIKE SHE is employed to simulate and evaluate the influence of coal mining on river runoff. The study shows that mining one ton of raw coal leads to the reduction of river runoff by 2.87 m3 between 1981 and 2008, of which the surface runoff decreases by 0.24 m3 and the baseflow by 2.63 m3. The reduction degree of river runoff for mining one ton of raw coal shows an increasing trend over years. The current study also reveals that large scale coal mining initiates the formation of surface cracks and subsidence, which intercepts overland flow and enhances precipitation infiltration. Together with mine drainage, the natural hydrological processes and the stream flows have been altered and the river run off has been greatly reduced. [ABSTRACT FROM AUTHOR]

Quantifying the effects of forest changes on hydrology in large watersheds is important for designing forest or land management and adaptation strategies for watershed ecosystem sustainability. Minjiang River watershed, located in the upper reach of the Yangtze River basin, plays a strategic role in the environmental protection and economic and social well-being for both the watershed and the entire Yangtze River basin. The watershed lies in the transition zone from Sichuan Basin to Qinghai-Tibet Plateau with a size of 24 000 km². Due to its strategic significance, severe historic deforestation and high sensitivity to climate change, the watershed has long been recognized as one of the highest priority watersheds in China for scientific research and resource management. The purpose of this review paper is to provide a state-of-the-art summary on what we have learned from several recently completed research programs (one of them known as "973 of the China National Major Fundamental Science" from 2002 to 2008). This summary paper focused on how land cover or forest change affected hydrology at both forest stand and watershed scales in this large watershed. Inclusion of two different spatial scales is useful, because the results from a small spatial scale (e.g. forest stand level) can help interpret the findings on a large spatial scale. Our review suggests that historic forest harvesting or land cover change has caused significant water yield increase due to reduction of forest canopy interception and evapotranspiration caused by removal of forest vegetation on both spatial scales. The impact magnitude caused by forest harvesting indicates that the hydrological effects of forest or land cover changes can be as important as those caused by climate change, while the opposite impact directions suggest their offsetting effects on water yield in the Minjiang River watershed. In addition, different types of forests have different magnitudes of evapotranspiration (ET), with the lowest in old-growth natural coniferous forests (Abies faxoniana Rehd. et Wils.) and the highest in coniferous plantations (e.g. Picea asperata Mast.) among major forest types in the study watershed. This suggests that selection of different types of forests can have an important role in ET and consequently water yield. Our synthesis indicates that future reforestation and climate change would likely produce the hydrological effects in the same direction and thus place double the pressure on water resource as both key drivers may lead to water yield reduction. The findings can support designing management strategies for protection of watershed ecological functions in the context of future land cover and climate changes. [ABSTRACT FROM AUTHOR]

Abstract  Whilst the Yingxiu-Beichuan fracture is considered to be the primary seismic fracture of the Wenchuan earthquake, surface ruptures, geohazards, abnormal hydrological phenomena and aftershocks occurred not only along this central fracture but also along the so-called “secondary seismic fractures” parallel to it. The paper reports some of the geohazards associated with these secondary seismic fractures and concludes that the contribution of these is important in the overall scale of the effect of the Wenchuan earthquake. [ABSTRACT FROM AUTHOR]

The development of the leather industry in the Aojiang watershed of Zhejiang province increased the release of waste water. In the waste water, ammonium nitrogen (NH+ 4-N and Ge harms human health and biological species. This paper focuses on assessing the trends of NH+-N and Ge concentrations in the released waste water in Aojiang watershed and on understanding their relationships with the released waste water using regression and correlation statistics. The paper also utilizes the integrated pollution index to evaluate the water quality in the watershed. Preliminary results show that, from 1992 to 1998, the concentrations of NH4-N and Ge harms human health and biological species. This paper focuses on assessing the trends of NH+ 4-N and Ge concentrations in the released waste water in Aojiang watershed and on understanding their relationships with the released waste water using regression and correlation statistics. The paper also utilizes the integrated pollution index to evaluate the water quality in the watershed. Preliminary results show that, from 1992 to 1998, the concentrations of NH+ 4-N and total Ge increased 13 and 14 times, respectively, and they decreased somewhat after 1998. The concentrations of NH+ 4-N and total Ge are positively correlated to the amount of released waste water. These concentrations of NH+ 4-N and Ge, respectively, exceed 12 and 3 times, of the water standards. The water quality in the watershed degraded from Type III in 1992 to over Type V in 2003 when they were compared with the national water quality standards. It appeared that the pollution had positive correlation with leather industry production. The degraded water has no doubt affected human health and the ecosystem health. These results can provide scientific information for the local government to reasonably adjust the industry structure and reduce the pollution to protect the environment. [ABSTRACT FROM AUTHOR]

Construction and operation of the Three Gorges Dam (TGD) has significantly altered the downstream hydrological regime along the Yangtze River, which has in turn affected the environment, biodiversity and morphological configuration, and human development. The ecological and environmental systems of the middle and lower Yangtze River have been affected adversely, with the ecosystems of Poyang Lake and its deltas being among the most damaged. Besides posing a potential threat to the survival of migrant birds and aquatic species, operation of the TGD has also affected the human population, particularly with respect to water and food security. Though the above mentioned effects have been studied in previous papers, a comprehensive discussion has never been conducted. This paper provides the first ever summary of the impacts of the TGD on the downstream reaches of the Yangtze River. The costs and benefits identified provide a constructive reference that can be used in decision-making for sustainable development of water resources in other nations, especially those in the developing world. [ABSTRACT FROM AUTHOR]

Soil sealing (loss of soil resources due to extensive land covering for the purpose of house building, road construction etc.) and subsequent soil landscape pattern changes constitute typical environmental problems in many places worldwide. Previous studies concentrated on soil sealing in urbanized regions, whereas rural areas have not been given sufficient attention. Accordingly, this paper studies soil landscape pattern dynamics (i.e., landscape pattern changes in response to rural anthropogenic activities) in the Tiaoxi watershed (Zhejiang province, eastern China), in which surface sealing is by far the predominant component of human forcing with respect to environmental change. A novel approach of quantifying the impacts of rural anthropogenic activities on soil resources is presented. Specifically, quantitative relationships were derived between five soil landscape pattern metrics (patch density, edge density, shape index, Shannon’s diversity index and aggregation index) and three rural anthropogenic activity indicators (anthropogenic activity intensity, distance to towns, and distance to roads) at two landscape block scales (3 and 5 km) between 1985 and 2010. The results showed that the Tiaoxi watershed experienced extensive rural settlement expansion and high rates of soil sealing. Soil landscapes became more fragmented, more irregular, more isolated, and less diverse. Relationships between soil landscape pattern changes and rural anthropogenic activities differed with the scale (spatial and temporal) and variable considered. In particular, the anthropogenic activity intensity was found to be the most important indicator explaining social development intensity, whereas the other two proximity indicators had a significant impact at certain temporal interval. In combination with scale effects, spatial dependency (correlation) was shown to play a key role that should be carefully taken into consideration in any relevant environmental study. Overall, the findings of this work suggest that soil sealing can be a critical human forcing issue with considerable consequences deserving serious attention by the experts, the public and the government alike. [ABSTRACT FROM AUTHOR]

The arid region of Northwest China, located in the central Asia, responds sensitively to global climate change. Based on the newest research results, this paper analyzes the impacts of climate change on hydrology and the water cycle in the arid region of Northwest China. The analysis results show that: (1) In the northwest arid region, temperature and precipitation experienced "sharply" increasing in the past 50 years. The precipitation trend changed in 1987, and since then has been in a state of high volatility, during the 21st century, the increasing rate of precipitation was diminished. Temperature experienced a "sharply" increase in 1997; however, this sharp increasing trend has turned to an apparent hiatus since the 21st century. The dramatic rise in winter temperatures in the northwest arid region is an important reason for the rise in the average annual temperature, and substantial increases in extreme winter minimum temperature play an important role in the rising average winter temperature; (2) There was a significant turning point in the change of pan evaporation in the northwest arid area in 1993, i.e., in which a significant decline reversed to a significant upward trend. In the 21st century, the negative effects of global warming and increasing levels of evaporation on the ecology of the northwest arid region have been highlighted; (3) Glacier change has a significant impact on hydrology in the northwest arid area, and glacier inflection points have appeared in some rivers. The melting water supply of the Tarim River Basin possesses a large portion of water supplies (about 50%). In the future, the amount of surface water will probably remain at a high state of fluctuation., (Copyright © 2015 Elsevier Inc. All rights reserved.)

The Wei River is the largest tributary of the Yellow River in China. The relationship between runoff and precipitation in the Wei River Basin has been changed due to the changing climate and increasingly intensified human activities. In this paper, we determine abrupt changes in hydro-climatic variables and identify the main driving factors for the changes in the Wei River Basin. The nature of the changes is analysed based on data collected at twenty-one weather stations and five hydrological stations in the period of 1960-2010. The sequential Mann-Kendall test analysis is used to capture temporal trends and abrupt changes in the five sub-catchments of the Wei River Basin. A non-parametric trend test at the basin scale for annual data shows a decreasing trend of precipitation and runoff over the past fifty-one years. The temperature exhibits an increase trend in the entire period. The potential evaporation was calculated based on the Penman-Monteith equation, presenting an increasing trend of evaporation since 1990. The stations with a significant decreasing trend in annual runoff mainly are located in the west of the Wei River primarily interfered by human activities. Regression analysis indicates that human activity was possibly the main cause of the decline of runoff after 1970., (Copyright © 2015. Published by Elsevier Inc.)

The land surface model (LSM) is extensively utilized to simulate terrestrial processes between land surface and atmosphere in the Earth system. Hydrology simulation is the key component of the model, which can directly reflect the capability of LSM. In this study, three offline LSM simulations were conducted over China using the Community Land Model version 5.0 (CLM5) driven by different meteorological forcing datasets, namely China Meteorological Forcing Dataset (CMFD), Global Soil Wetness Project Phase 3 (GSWP3), and bias-adjusted ERA5 reanalysis (WFDE5), respectively. Both gridded and in situ reference data, including evapotranspiration (ET), soil moisture (SM), and runoff, were employed to evaluate the performance levels of three CLM5-based simulations across China and its ten basins. In general, all simulations realistically replicate the magnitudes, spatial patterns, and seasonal cycles of ET over China when compared with remote-sensing-based ET observations. Among ten basins, Yellow River Basin (YRB) is the basin where simulations are the best, supported by the higher KGE value of 0.79. However, substantial biases occur in Northwest Rivers Basin (NWRB) with significant overestimation for CMFD and WFDE5 and underestimation for GSWP3. In addition, both grid-based or site-based evaluations of SM indicate that systematic wet biases exist in all three CLM5 simulations for shallower soil layer over nine basins of China. Comparatively, the performance levels in simulating SM for deeper soil layer are slightly better. Moreover, all three types of CLM5 simulate reasonable runoff spatial patterns, among which CMFD can capture more detailed information, but GSWP3 presents more comparable change trends of runoff when compared to the reference data. In summary, this study explored the capacity of CLM5 driven by different meteorological forcing data, and the assessment results may provide important insights for the future developments and applications of LSM. [ABSTRACT FROM AUTHOR]

Global management of wetlands to suppress greenhouse gas (GHG) emissions, facilitate carbon (C) sequestration, and reduce atmospheric CO2 concentrations while simultaneously promoting agricultural gains is paramount. However, studies that relate variability in CO2 and CH4 emissions at large spatial scales are limited. We investigated three-year emissions of soil CO2 and CH4 from the primary wetland types of the Liaohe Delta, China, by focusing on a total wetland area of 3287 km2. One percent is Suaeda salsa, 24% is Phragmites australis, and 75% is rice. While S. salsa wetlands are under somewhat natural tidal influence, P. australis and rice are managed hydrologically for paper and food, respectively. Total C emissions from CO2 and CH4 from these wetland soils were 2.9 Tg C/year, ranging from 2.5 to 3.3 Tg C/year depending on the year assessed. Primary emissions were from CO2 (~98%). Photosynthetic uptake of CO2 would mitigate most of the soil CO2 emissions, but CH4 emissions would persist. Overall, CH4 fluxes were high when soil temperatures were >18°C and pore water salinity <18 PSU. CH4 emissions from rice habitat alone in the Liaohe Delta represent 0.2% of CH4 carbon emissions globally from rice. With such a large area and interannual sensitivity in soil GHG fluxes, management practices in the Delta and similar wetlands around the world have the potential not only to influence local C budgeting, but also to influence global biogeochemical cycling. [ABSTRACT FROM AUTHOR]

Estimating gross primary production (GPP) and net primary production (NPP) are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ) Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (FPAR) using a light use efficiency (LUE) model. The autotrophic respiration (Ra) was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H) and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m-2 d-1 and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m-2 d-1 and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of our modelling results. This research suggested that the utilization of multi-source data with various scales would help to the establishment of an appropriate model for calculating GPP and NPP at regional scales with relatively high spatial and temporal resolution. [ABSTRACT FROM AUTHOR]

Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature correction methods in downscaling RCM simulations applied over the Kaidu River basin, one of the headwaters of the Tarim River basin. Precipitation correction methods applied include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and quantile mapping (QM), while temperature correction methods are LS, variance scaling (VARI) and DM. The corrected precipitation and temperature were compared to the observed meteorological data, prior to being used as meteorological inputs of a distributed hydrologic model to study their impacts on streamflow. The results show (1) streamflows are sensitive to precipitation, temperature and solar radiation but not to relative humidity and wind speed; (2) raw RCM simulations are heavily biased from observed meteorological data, and its use for streamflow simulations results in large biases from observed streamflow, and all bias correction methods effectively improved these simulations; (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g., standard deviation, percentile values) while the LOCI method performed best in terms of the time-series-based indices (e.g., Nash-Sutcliffe coefficient, R2); (4) for temperature, all correction methods performed equally well in correcting raw temperature; and (5) for simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with those of corrected precipitation; i.e., the PT and QM methods performed equally best in correcting flow duration curve and peak flow while the LOCI method performed best in terms of the time-series-based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other areas and models. [ABSTRACT FROM AUTHOR]

One of the potential impacts of global warming is likely to be experienced through changes in flood frequency and magnitude, which poses a potential threat to the downstream reservoir flood control system. In this paper, the downscaling results of the multimodel dataset from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively) were coupled with the Variable Infiltration Capacity (VIC) model to evaluate the impact of climate change on the Feilaixia reservoir flood control in the Beijiang River basin for the first time. Four emissions scenarios [A1B and representative concentration pathway (RCP) scenarios RCP2.6, RCP4.5, and RCP8.5] were chosen. Results indicate that annual distribution and interannual variability of temperature and precipitation are well simulated by the downscaling results of the CMIP3 and CMIP5 multimodel dataset. The VIC model, which performs reasonably well in simulating runoff processes with high model efficiency and low relative error, is suitable for the study area. Overall, annual maximum 1-day precipitation in 2020-50 would increase under all the scenarios (relative to the baseline period 1970-2000). However, the spatial distribution patterns of changes in projected extreme precipitation are uneven under different scenarios. Extreme precipitation is most closely associated with extreme floods in the study area. There is a gradual increase in extreme floods in 2020-50 under any of the different emission scenarios. The increases in 500-yr return period daily discharge of the Feilaixia reservoir have been found to be from 4.35% to 9.18% in 2020-50. The reservoir would be likely to undergo more flooding in 2020-50. [ABSTRACT FROM AUTHOR]

Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China. [ABSTRACT FROM AUTHOR]

• Geological disasters in hilly areas are related to Land-Use and Land-Cover Changes. • The number of geological disasters in the cultivated land area is the largest. • The point density of geological disasters and vegetation coverage is limited. • Geological disasters are more likely to occur in the period of heavy rainfall. • The closer geological disaster to river, the greater probability/scale of occurrence. Sichuan hilly area is located in southwest China, which have many hilly area, is a densely populated, economically active, frequent geological disasters area. In this paper, Neijiang City in the region is taken as the test sample. This article, which analyzes Land-Use and Land-Cover Changes (LUCC), meteorological and hydrological data from 2015 to 2020, takes Neijiang City in this region as the research object. We explored the relationship between geological disasters such as collapse and landslides that often occur in the natural ecological environment with LUCC and meteorological and hydrological factors, using GIS spatial analysis and statistical analysis methods. The research results indicate that geological disasters mainly occur in farmland areas. The density of geological disaster points is highest within urban areas, making them the most prone to geological disasters. Geological disasters are more densely distributed in the area within 600 to 800 m from the river. There is a strong correlation between the average rainfall amount and the probability of geological disasters occurring. This study provides a scientific basis for the geological disaster risk assessment, prevention and control in this region. It has certain reference significance for the ecological environment governance, land resources planning and management in other similar regions. [ABSTRACT FROM AUTHOR]

Hydrological simulation in regions with a large number of water storages is difficult due to inaccurate water storage data. To address this issue, this paper presents an improved version of SWAT2005 (Soil andWater Assessment Tool, version 2005) using Landsat, a satellite-based dataset, an empirical storage classification method and some empirical relationships to estimate water storage and release from the various sizes of flow detention and regulation facilities. The SWAT2005 is enhanced by three features: (1) a realistic representation of the relationships between the surface area and volume of each type of water storages, ranging from small-sized flow detention ponds to medium- and large-sized reservoirs with the various flow regulation functions; (2) water balance and transport through a network combining both sequential and parallel streams and storage links; and (3) calibrations for both physical and human interference parameters. Through a real-world watershed case study, it is found that the improved SWAT2005 more accurately models small- and medium-sized storages than the original model in reproducing streamflows in the watershed. The improved SWAT2005 can be an effective tool to assess the impact of water storage on hydrologic processes, which has not been well addressed in the current modelling exercises. [ABSTRACT FROM AUTHOR]

Flood frequency analysis plays a fundamental role in dam planning, reservoir operation, and risk assessment. However, conventional univariate flood frequency analysis carried out by flood peak inflow or volume does not account for the dependence between flood properties. In this paper, we proposed an integrated approach to estimate reservoir risk by combining the copula-based bivariate flood frequency (peak and volume) and reservoir routing. Through investigating the chain reaction of "flood frequency—reservoir operation-flood risk", this paper demonstrated how to simulate flood hydrographs using different frequency definitions (copula "Or" and "And" scenario), and how these definitions affect flood risks. The approach was applied to the Meishan reservoir in central China. A set of flood hydrographs with 0.01 frequency under copula "Or" and "And" definitions were constructed, respectively. Upstream and downstream flood risks incorporating reservoir operation were calculated for each scenario. Comparisons between flood risks from univariate and bivariate flood frequency analysis showed that bivariate flood frequency analysis produced less diversity in the results, and thus the results are more reliable in risk assessment. More importantly, the peak-volume combinations in a bivariate approach can be adjusted according to certain prediction accuracy, providing a flexible estimation of real-time flood risk under different prediction accuracies and safety requirements. [ABSTRACT FROM AUTHOR]

The Tarim River is the major water source for all kinds of human activities and for the natural ecosystems in the Tarim Basin, Xinjiang, China. The major water consumer is irrigation agriculture, mainly cotton. As the area under irrigation has been increasing ever since the 1950s, the lower and middle reaches of the Tarim are suffering from a water shortage. Within the framework of the Water Law and two World Bank projects, the Tarim River Basin Water Resource Commission was founded in 1997 in order to foster integrated water resource management along the Tarim River. Water quotas were fixed for the water utilization along the upstream and downstream river stretches. Furthermore, along each river stretch, quotas were set for water withdrawal by agriculture and industry and the amount of water to remain for the natural ecosystems (environmental flow). Furthermore, huge investments were undertaken in order to increase irrigation effectiveness and restore the lower reaches of the Tarim River. Still, a regular water supply for water consumers along the Tarim River cannot be ensured. This paper thus introduces the hydrology of the Tarim River and its impacts on land use and natural ecosystems along its banks. The water administration in the Tarim Basin and the water allocation plan are elaborated upon, and the current water supply situation is discussed. Finally, the adaptations made due to issues of water allocation and water scarcity on the farm level are investigated and discussed. [ABSTRACT FROM AUTHOR]

In this paper we analyse the effects of different spatial input data resolution on water balance simulation using a simple distributed hydrological model: PCRXAJ model. A data set consisting of land use and digital elevation model at 25m resolution of Xitiaoxi catchment in South China is used for investigation. The model was first calibrated and validated at 50m cell size, thereafter an aggregation of the digital elevation model (DEM) and land use maps at 100 m, 200 m, 300 m, 500m and 1 km are applied to evaluate the effects of spatial data resolution on simulated discharge. The simulation results at a grid size of 50m show a good correlation between measured and simulated daily flows at Hengtangcun station with Nash-Suttcliffe efficiency larger than 0.75 for both calibration and validation periods. In contrast, the model performs slightly worse at Fanjiacun station. The increasing grid size affects the characteristics of the slope and land use aggregation and causes important information loss. The aggregation of input data does not lead to significant errors up to a grid of 1 km. Model efficiencies decrease slightly with cell size increasing, and more significantly up to the grid size of 1 km. [ABSTRACT FROM AUTHOR]

A major research challenge in ungauged basins is to quickly assess the dominant hydrological processes of watersheds. In this paper we present a top-down approach from first field reconnaissance to perceptual model development, model conceptualization, evaluation, rejection and eventually, to a more substantial field campaign to build upon the initial modeling. This approach led us from an initial state where very little was known about catchment behavior towards a more complete view of catchment hydrological processes, including the preliminary identification of water sources and an assessment of the effectiveness of our sampling design. [ABSTRACT FROM AUTHOR]

The hydrological impact of forest removal on the southeast Tibetan Plateau during the second half of the last century is investigated in this study using an atmospheric general circulation model. The effects of deforestation are investigated by examining the differences between the forest replacement and control experiments. Model results demonstrate that deforestation of the southeast Tibetan Plateau would influence the local and the remote climate as well. It would lead to decreased transpiration and increased summer precipitation in the deforested area and a wetter and warmer climate on the Tibetan Plateau in summer. This may produce more runoff into the rivers originating from the Tibetan Plateau and worsen flooding disasters in the downstream areas. The numerical experiments also show that deforestation would remotely impact Asian climate, and even global climate, although the statistical significance is small. A strong drought is found at middle and lower reaches of the Yellow River, where livelihoods and economics have suffered from recent droughts. Ecosystem research on the Tibetan Plateau is a relatively new topic and needs further interdisciplinary investigation. [ABSTRACT FROM AUTHOR]

The Gravity Recovery and Climate Experiment (GRACE) mass concentration (mascon) solutions provide enhanced signal and spatial resolution of surface mass changes by using regularization techniques to reduce striping errors. To further improve the computational efficiency and capture the same benefits as GRACE mascon solutions, we presented an estimation of regional mascon solutions from GRACE-based geopotential differences by using spatio-temporal constraints with the unconstrained spherical harmonic solutions as a priori information. As a case study, the changes in the basin-scale terrestrial water storage (TWS) over the Yangtze River Basin (YRB) on 2° × 2° grids at monthly intervals were estimated using GRACE-based geopotential differences, for the period of 2003 January—2013 December. The estimates were validated through official GRACE mascon solutions and in situ observations (i.e. time derivative of TWS change derived from precipitation, evapotranspiration and river run-off based on the water mass balance equation). The results demonstrate that the spatial and temporal patterns of TWS changes in the YRB inferred from geopotential differences adequately agree with the official mascon solutions; however, differences in amplitudes can be observed at the subbasin scale because of different regularizations applied in different solutions. In situ validations demonstrate that seasonal changes of mascon solutions and in situ observations agree well in the YRB; however, there are evident discrepancies in amplitudes over the subbasins owing to leakage biases in mascon solutions. For the entire YRB, the statistical evaluation and cross-wavelet transform demonstrate that our regional mascon solutions appear more consistent with in situ observations than the official mascon solutions. In addition, compared with the results estimated by spatial constraints, regional mascon solutions estimated by spatio-temporal constraints using observations from three consecutive months adjacent to the given month were improved. Our method provides an alternative option to use different regularization constraints, which is helpful for fine-tuning analysis of basin-scale TWS changes. [ABSTRACT FROM AUTHOR]

The concepts and calculation of basic, suitable, and fine ecological flow are put forward, and an integrated multi-method to calculate the ecological flow in rivers under multi-objectives is explored. Based on this, a refined calculation theory and method of a multi-objective ecological flow division based on time and space is proposed. That is, three commonly used methods, namely, the hydrology method, the hydraulics method, and the habitat method, are selected to finely calculate the ecological flow demand at different periods, in different sections, and under different ecological objectives. This approach breaks through the traditional ecological water demand calculation method based on hydrology and develops a river ecological flow calculation method based on water environmental protection objectives. A refined calculation method of ecological flow division based on time and space is developed to ensure that the ecological-hydrological process in rivers and lakes meets the ecological flow demand in different periods, different reaches, and different ecological objectives. Taking eight rivers entering Baiyangdian Lake as an example, the ecological flow demand in different river sections under different ecological objectives at different times is calculated to ensure the ecological flow process. The results show that the range of basic ecological flow demand range is 0.07–3.87 m3/s, the range of suitable ecological flow demand is 0.51~10.74 m3/s, and the range of fine ecological flow demand is 0.71~20.29 m3/s. In terms of spatial distribution, Ping River has the lowest demand for ecological flow, and the Zhulong River has the largest. In terms of the interannual ecological demand, those of the Baigou River, Fu River, Xiaoyi River, and Zhulong River are larger. In the demand process across the year, the demand is the largest from July to September, while the demand is the smallest from March to May. Similarly, most rivers face such problems as a sharp decline in runoff, drying up of the river, and an urgent need to restore ecology in northern China. This study also has insights and reference significance for other regions. [ABSTRACT FROM AUTHOR]

The Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) provides new-generation satellite precipitation datasets with high spatio-temporal resolution and accuracy, which is widely applied in hydrology and meteorology. However, most examinations of the IMERG were conducted on daily, monthly, and annual scales, and inadequate research focused on the sub-daily scale. Thus, this study set up four sub-daily scales (1 h, 3 h, 12 h, and 24 h at 0.1° spatial resolution) and four spatial scales (0.1°, 0.25°, 0.5°, and 1° at 1 h temporal resolution) to finely evaluate the performance of IMERG products in the summer seasons from 2014 to 2019 over mainland China. The precipitation amount (PA), frequency (PF), and intensity (PI) were adopted to assess the performance of the IMERG referenced by the ground-based precipitation product of the China Meteorological Administration (CMA). The results show that the IMERG can capture the spatial patterns of precipitation characters over mainland China, but the PA and PI are overestimated and the PF is underestimated, and the evaluation results are highly sensitive to the different temporal and spatial resolutions. Compared with fine spatio-temporal scales, the performance of the IMERG is significantly improved when scaled up to coarser scales. Moreover, the IMERG shows a better performance of PA and PI in larger regions and during longer periods. This study provided a reference for the application of IMERG products in different spatial and temporal scales. [ABSTRACT FROM AUTHOR]