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ABSTRACT The reliability of seasonal snow cover information is constrained by limitation of in situ observations and uncertainties in remote sensing data and model simulations in alpine region, thus posing important challenges to understanding the climate system and water resource management in alpine region. Here, the assimilation of daily cloud‐free Moderate Resolution Imaging Spectroradiometer (MODIS) normalised difference snow index (NDSI) product into an intermediate complexity snow mass and energy balance model—Flexible Snow Model (version FSM2_MO)—was implemented. The aim is to improve the model simulations of seasonal snow cover (snow‐covered extent; SCE, snow depth; SD, snow water equivalent; SWE, and snowmelt runoff; SMR) in the alpine region (a case of the upper‐middle reaches of the Heihe River basin, Northwest China). The results indicate comprehensive improvement in the simulation of SCE, SD, and SMR in the study area through data assimilation, with the ability to significantly reduce prior biases of the FSM2_MO. Based on the independent daily cloud‐free Advanced Very High Resolution Radiometer (AVHRR) SCE product, the updated SCE simulation (i.e., data assimilation) showed a reduction in mean absolute error (MAE) from 10.46% to 7.16%, root mean square error (RMSE) from 16.14% to 12.26%, and an increase in Pearson's correlation coefficient (CC) from 0.18 to 0.67 compared with the open loop simulation (i.e., without assimilation). The evaluation results of SD observation data showed that data assimilation improved SD simulation compared with the open loop run (OL). And utilising the monthly discharge observations at the Yingluoxia hydrological station, data assimilation slightly improved the SMR simulation. The updated SMR simulation achieved a CC of 0.91, Nash‐Sutcliffe efficiency coefficient (NSE) of 0.73, and Kling‐Gupta efficiency coefficient (KGE) of 0.76. Moreover, the Landsat 8‐derived snow cover map and Sentinel‐1‐derived SD also indicated that the updated simulation effectively filled in the missing snow cover and removed the superfluous snow cover predicted by the OL simulation in terms of spatial distribution. [ABSTRACT FROM AUTHOR]

Understanding the changes of sediment concentration in rivers, especially under heavy rains, is of great significance to accurately evaluate the effectiveness of soil and water conservation measures in the Loess Hilly Area. On July 26, 2017, an extremely heavy rain (maximum rain intensity of 66.6 mm/h, the highest rainfall of 256.8 mm in 10 h, and a return period of 100 years) occurred over the 821 km2 Xiaoli River watershed in the Wuding River watershed. In order to understand the sediment concentration during the heavy rain event, 10 dam‐controlled catchments in the center of the rainstorm (3 in the Xiaoli River watershed and 7 in its adjacent watersheds) without drainage and damage were selected. All the retained runoff and sediment in the check dams were measured by the cross‐sectional survey according to the flood marks left by the heavy rain. Combined with the observed runoff and sediment transport data by the hydrological station at the outlet of the Xiaoli River watershed as well as the deposited sediment investigated in the watershed during the heavy rain event, the change of sediment concentration and the role of check dam were analyzed. Results showed that under heavy rain, all the sediment concentrations of runoff in the dam‐controlled catchments ranged from 344 to 552 kg/m3, suggesting that the sediment retaining effect of slope measures (woodland, grassland, and terrace) is limited and cannot prevent the occurrence of hyperconcentrated flows. The gully measures (check dams) in the Xiaoli River watershed can hold a large amount of sediment under heavy rain and make the runoff no longer a hyperconcentrated flow at the watershed outlet. In order to control the transport of hyperconcentrated flows to the downstream, more attention should be paid to the construction of check dams while carrying out vegetation ecological construction in the Loess Hilly Area. [ABSTRACT FROM AUTHOR]

Channel sandbars are extremely sensitive to basin‐wide natural processes and human activities, and their modifications considerably affect channel stability and river ecosystem health. However, quantitatively detecting the three‐dimensional dynamics of channel sandbars at a high spatial resolution over a large area remains challenging. In this study, we propose a semi‐automated process to address this challenge by extracting sandbar contours from Sentinel‐2 images in the Google Earth Engine (GEE) platform. We then generate contour datasets for each sandbar based on the spatial relationship between contours and water levels at nearby hydrological stations. Subsequently, digital elevation models (DEMs) are created for each sandbar using the contour dataset, and non‐linear relations between sandbar areas and water levels are fitted through polynomial curves of degrees 3–6 to calculate changes in sandbar volumes. Finally, we comprehensively analysed the driving mechanisms of sandbar changes in different sub‐reaches. Our findings reveal the area and volume of sandbars in three of the four sub‐reaches increased significantly between 2018 and 2019; however, these values decreased significantly and continuously between 2019 and 2022. Sandbars located downstream near the dam experienced more severe erosion compared to those farther downstream. Although the morphodynamic processes of each sub‐reach were different, extremely low rainfall in 2019–2020 and the operation of the Xayaburi Dam are significant global factors leading to the shrinkage of the sandbars. Furthermore, abnormal erosion with a change rate of −9.62% in area and −8.95% in volume was observed in the sub‐reach between Vientiane and Khong Chiam hydrological stations between 2018 and 2019, with the susceptibility of the channel to flow scour and anthropogenic sand mining being significant factors. Although the sediment replenishment from tributaries diminishes the impact of upstream dams and droughts on the reach farther downstream, the threat to channel stability due to excessive sand mining should be given high priority. Our study highlights how satellite remote sensing, specifically utilizing time series images with fine spatio‐temporal resolutions, effectively detects three‐dimensional variations in sandbars and river geomorphic changes. Additionally, it demonstrates the significant post‐dam alteration of erosion patterns and deposition dynamics within the sandbar region of the lower Mekong River. [ABSTRACT FROM AUTHOR]

Climate change and human activities combine to alter river hydrology, thereby threatening the health of river ecosystems. Quantifying the impacts of climate change and human activities on ecological flow assurance is essential for water resource management and river ecological protection. However, fewer studies quantify the impacts of climate change and human activities on ecological flow assurance based on a complete set of frameworks. The present study introduces an integrated assessment framework designed to quantify the impacts of climate change and human activities on ecological flow security. The framework includes the following steps: (1) natural river runoff reconstruction utilizing a semi‐distributed hydrological model (SWAT), (2) calculation of the most suitable ecological stream flow of the watershed ecosystem by using the non‐parametric kernel density estimation method, (3) calculation of the safety and security levels under minimum ecological flow and appropriate ecological flow conditions in the watershed and (4) quantification of the influences of climate change and human activities on the security of ecological flow in the watershed through the application of a quantitative attribution method. The impact of climate change and human activities on the ecological flow assurance level was analysed using three hydrological stations in Xiangtan, Hengyang and Laobutou, which are the main tributaries of the Xiangjiang River Basin, as a case study. The findings indicated a substantial decrease in ecological flow assurance levels across the basin during the period of human impact (1991–2019). The quantitative assessment results suggest that human activities predominantly drive the degradation of ecological flow assurance throughout the period of human impact, accounting for 57.05% of the total impact. Extensive gradient reservoir scheduling and anthropogenic water withdrawals were the main factors contributing to the degradation of ecological flow assurance in the study basin. The methodology and findings presented in this study offer insights into the evolutionary characteristics and driving forces behind ecological flow security in a dynamic environment. Furthermore, they establish a scientific foundation for local water resource management and river ecosystem protection. [ABSTRACT FROM AUTHOR]

Human activities are the main reasons for reducing sediment transport in the Yellow River, with thousands of check dams playing a crucial role. Quantifying the sediment reduction efficiency and analyzing the future development of check dams can help ecological construction and management in the Yellow River basin. This study developed a calculation method for sediment reduction by check dams and calculated the annual sediment reduction, and further estimated the sediment reduction efficiency at different periods. In addition, this study also analyzed the construction intensity and proposed construction strategies of check dams in the Yellow River basin. The results show that from 1952 to 2011, the cumulative sediment reduction of check dams in the middle reaches of the Yellow River was 8056 million tons, the annual sediment reduction varied from 0 to 403 million tons, with a multiyear average of 134 million tons. Among the major tributaries in the middle reaches of the Yellow River, the sediment reduction efficiency of check dams ranged from 0.51% to 76.88% due to the ecological management of slopes and the loss of sediment retention capacity by small‐ and medium‐sized check dams, the sediment reduction efficiency from 1980 to 1999 was higher than from 2000 to 2011. Following the analysis of the suitability of check dam construction, we calculated the potential and intensity of check dam construction in the Yellow River basin. The intensity of check dam construction exceeded 50% in the TDG‐LM region (Toudaoguai hydrological station to Longmen hydrological station) in the middle reaches of the Yellow River. We analyzed the siltation situation of large‐sized check dams and proposed strategies for the construction and management of check dams. [ABSTRACT FROM AUTHOR]

The critical role of macrophytes in aquatic environments cannot be overstated, but little attention has been paid to macrophytes in Moroccan rivers. This study aims to investigate the environmental factors that affect the presence and distribution of macrophytes in the Hydrological Basin of Sebou (HBS) in Morocco. The study focused on 39 hydrological stations, distributed across the five hydro‐ecoregions of the basin. The results show that the number of aquatic species is limited and significantly lower than that of riparian species, which are more diverse. Analysis of similarity (ANOSIM) revealed that there is a significant difference in the riparian species communities between the various hydro‐ecoregions (R = 0.1853, Bonferroni corrected α = 0.0022). However, when only aquatic species were considered, ANOSIM showed no significant difference (R = 0.05524, Bonferroni corrected α = 0.1453), and the results were confirmed by the PERMANOVA test. Furthermore, ANOSIM did not reveal a clear difference in the composition of aquatic species between stations with low and high nutrients (R = 0.01348, p = 0.4245). The Student's t‐test also showed no significant difference in the variation of riparian and aquatic species numbers between the two groups (all species combined: t = 0.1639, p = 0.8723; riparian species: t = 0.4740, p = 0.6434; aquatic species: t = 0.9869, p = 0.3417). These findings highlight the need for further research into environmental factors limiting aquatic species diversity and nutrient thresholds affecting macrophyte abundance. Understanding these elements is crucial for addressing species distribution constraints and elucidating nutrient dynamics that influence macrophyte populations, enriching ecosystem management and conservation strategies. [ABSTRACT FROM AUTHOR]

The construction and operation of upstream reservoirs have significantly altered downstream hydrologic regime. Appropriate and quantifiable assessment method for the alteration of hydrologic regime is considerably vital and emergent for ecological protection and restoration. The Range of Variability Approach (RVA) and modified RVA methods have been widely used in practice to assess the hydrological alteration. However, these methods have failed to concurrently describe the distribution of indicator and morphological features in detail, which might inevitably lead to the misjudgment of alteration. This paper proposes a Joint Probability Density Difference Approach (JPDDA) method to address the major drawbacks of these previous methods with the introduction of Gaussian Kernel Density Estimation (KDE) and copula function. The annual average flow is selected as the reference variable to construct a proper joint probability density function between itself and other hydrological alteration indicators. The JPDDA method could describe the marginal distribution in detail through Gaussian KDE and also link the morphological features with copula function. Along with pervious methods, the hydrological alterations at Yichang hydrological station, Yangtze River are estimated based on the measured flow from 1949 to 2022. It is shown that the hydrologic regime has suffered from a moderate or even heavy alteration under the influence of massive upstream cascade reservoirs, and the JPDDA outperforms the other methods in terms of rationality and stability for practical assessments. Thus, the proposed JPDDA method is strongly advised to handle the hydrological alteration and could provide a reasonable reference for ecological operation. [ABSTRACT FROM AUTHOR]

Determining the precise placement of hydrological stations on a simulated digital river network is crucial for constructing hydrological models applicable to process simulation, water resource management, and flood forecasting endeavors. To solve this problem, we categorized and scrutinized deviations between the simulated and their actual station locations, and proposed a novel automatic hydrological station relocation algorithm (ASRA). The algorithm was first validated in the Amazon Basin using Global Runoff Data Centre (GRDC) hydrological stations and 90 m × 90 m Shuttle Radar Topography Mission (SRTM) data, successfully correcting the spatial position and corresponding catchment area (CCA) of each station. Findings revealed that CCA inaccuracies were notably decreased, transitioning from an initial 7.62% when employing a conventional 5‐km search radius to 5.43% after adopting an iteratively optimized, objective, and rational 8‐km search radius. The ASRA method was subsequently applied to GRDC stations within the HDMA and HydroSHEDS data sets, successfully repositioning 8,339 and 8,026 stations respectively, all with catchment area deviations of less than 5%, thus either exceeding or at least equaling the precision of prior research efforts. A Python program was developed and incorporated into an ArcGIS toolbox that features user‐friendly attributes, enabling swift computation and accurate rectification, as a result of building upon our method. In short, our study presents a fresh approach and a robust tool for tackling the inconsistencies of hydrological station locations. The updated global GRDC hydrological station locations specifically tailored for both HDMA and HydroSHEDS data sets, together with the toolbox developed, were accessible for download on the figshare platform. Plain Language Summary: As a result of the inherent limitations posed by DEM resolution, hydrological stations' actual positions frequently diverge from their corresponding simulated locations on the digital river network derived from DEM data. These discrepancies can vary across different DEM data sets. While traditional manual methods have been reliable in terms of accuracy, they suffer from inefficiency, while automatic approaches, conversely, have offered speed but at the cost of precision. Hence, this study introduces an automated method and ArcGIS‐based toolbox that combines both high accuracy and efficiency, exemplifying its application in the Amazon basin as well as globally. Key Points: The deviation of hydrological station locations on a digital river network were categorized into three types according to the catchment area and locationA new ASRA was developed to deal with all deviation types with the advantages of convenience, efficiency, and easy integration with ArcGISThis method provides an objective and reasonable search radius to decrease the catchment area deviation based on an empirical search radius [ABSTRACT FROM AUTHOR]

Supra‐ and sub‐permafrost groundwater are the two main components of groundwater in permafrost regions. However, due to the lack of groundwater observational data, the spatial‐temporal differentiation of these groundwater components in permafrost basins remains unclear. Based on flow data from 17 hydrological stations in five permafrost rivers within the Eurasian Arctic and Qinghai‐Tibet Plateau permafrost regions, this study tries to determine the proportion of supra‐ and sub‐permafrost groundwater through the corresponding relationship between baseflow separation and baseflow index. The results showed that the annual average contribution of supra‐ and sub‐permafrost groundwater in river runoff to total streamflow in the Yangtze River source basin was 36.81% and 14.56%, respectively. Correspondingly, the Yellow River source basin was 36.58% and 24.46%, the Ob River basin was 37.05% and 26.83%, the Yenisei River basin was 28.80% and 36.56%, and the Lena River basin was 39.13% and 9.54%. Over the past 50–80 years, the ratio of sub‐permafrost groundwater discharge to river runoff and the flux of sub‐permafrost groundwater have shown an increasing trend in all study basins, which was significantly affected by air temperature and permafrost area. Relative contribution of supra‐permafrost groundwater exhibits a significant positive correlation with precipitation and permafrost area. Air temperature has both positive and negative effects on supra‐permafrost groundwater discharge, leading to a rising or falling trend of supra‐permafrost groundwater discharge. In the future, it is necessary to further explore the complex effects of groundwater discharge variations on streamflow in permafrost regions under climate warming. Key Points: Based on the relationship between baseflow and baseflow index, groundwater components can be separated in permafrost regionsAir temperature exhibits a significant positive and negative correlation with sub‐ and supra‐permafrost groundwater components, respectivelyThe relative proportions of supra‐ and sub‐permafrost groundwater show spatial and temporal heterogeneity [ABSTRACT FROM AUTHOR]

The flow duration curve (FDC) is the cumulative distribution function, which represents the relationship between the frequency and magnitude of streamflow, and the precipitation duration curves (PDC) follows the same principle. Nowadays, the correlation between the shape of PDC and FDCs, their respective physical control factors including human activities, and their fitting conditions in unmeasured catchments across China have not been fully understood. In this paper, daily precipitation and streamflow data with 30 years records from 224 hydrological stations in the middle and lower Yangtze River basin were chosen to fit PDC and FDCs through gamma distribution. Framework was proposed for modelling FDCs to analyse the relationship, similarity, regional patterns and response mechanism of fitting parameters between PDC and FDCs, dividing the streamflow time series into fast and base flow and stations into three categories in consideration of human activities to attribute the shapes of PDC and FDCs to catchment meteorological and geographical characteristics and physical processes under natural conditions. Results indicate that the parameters of PDC and certain FDCs (TFDC, FFDC, SFDC) share similar spatial patterns but vary for the different duration and interactions of the processes. The climate and catchment characteristics such as extreme properties of precipitation, base flow index (BFI), Pmax*αp and concentration ratio index (CIM) will influence the shape of PDC and FDCs. The relationship between BFI and SFDC/TFDC can be better reflected in "Regulated watersheds", while CIM/Pmax*αp and PDC/FFDC in "watersheds in the mainstream" are more related. This paper provides a deeper understanding and more accurate way of the application of these parameters in describing and predicting hydrological processes and estimation of PDC and FDCs in unmeasured catchments, and can be applied to more future research about processes based on catchment rainfall‐runoff responses and physical controls. [ABSTRACT FROM AUTHOR]

The channel sediment transport capacity is an important parameter in soil erosion models, and it determines the proportion of soil erosion that is sent outside the watershed. However, the calculation and judgment methods for the sediment transport capacity of channel are still incomplete, and further research is needed. Therefore, this paper takes Chabagou, a typical watershed in the hilly and gully region of the Loess Plateau, as an example and, based on the measured hydrological and sediment data collected during rainstorm floods in 1961–1969 at three hydrological stations, Caoping, Shejiagou, and Tuanshangou, studies the sediment transport capacity of channels in a small watershed from the perspective of energy dissipation. Clearly, the sediment transport capacity is better determined by using a single flood and sediment concentration peak process. The discriminant conditions are determined for the sediment concentration to reach sediment transport capacity during the flood rising and falling sections of the sediment process of the small watershed storm flood. When determining sediment transport capacity based on the characteristics of the flood and sediment concentration peak, we find that sediment transport capacity is reached in the flood discharge peak when the flood discharge peak occurs earlier than the sediment concentration peak. When determining sediment transport capacity based on the flow discharge and sediment concentration characteristics of the sediment fall section, we find that when the flood event exhibits a counterclockwise hysteresis curve and a time‐lagged effect occurs, the sediment concentration at that time reaches sediment transport capacity. In this study, the sediment concentration as a function of run‐off amount is logarithmic at different subbasin scales when run‐off reaches its maximum capacity to transport sediment. The R2 is high, ranging from 0.78 to 0.92. The results of this research provide a reference for the study of sediment transport capacity. [ABSTRACT FROM AUTHOR]

Variations of water discharge and sediment load in the Red River basin have received considerable attention due to its drastic reduction during the past several decades. This paper presents a more specifically investigating of the seasonal variations in water discharge and sediment load from 1958 to 2021, both before and after the impoundment of all large dam‐reservoirs, using daily observations from the Son Tay hydrological gauging station, the outlet of the Red River system and entry to the delta. Sediment loads have decreased progressively since the early 1990s due to sediment yield reduction and dams in the upper basin, with a reduction of about 91% (from 116 × 106 to 11 × 106 t/year) over the 64‐year observation period. Prior to the impoundment of the Hoa Binh dam‐reservoir in 1988, the hydrological processes in the Red River system exhibited seasonal anomalies (clockwise mode on the hysteresis of rating curve), which implies that sediment load is highly proportional to water discharge and precipitation. The hysteresis loops between mean monthly water discharge and suspended sediment concentration after 1988 were altered by tributary dam‐reservoirs and a phenomenon known as 'temporal monsoon moving', which shifted the rating curve from clockwise to counterclockwise mode. Our long‐term analysis indicates that approximately 57.5% and 79% of sediments were trapped during the periods 1989–2008 (after Hoa Binh dam‐reservoir impoundment) and 2009–2021 (a series of new dam‐reservoirs went into operation), respectively, primarily during the high‐discharge months (June–October). Additionally, we concluded that the contribution of climate components (e.g., rainfall) to the dramatic decline in sediment load of the Red River system was less than the human impact. [ABSTRACT FROM AUTHOR]

The sediment regime in the middle Yangtze River has been significantly changed from quasi‐equilibrium to nonequilibrium since the impoundment of the Three Georges Reservoir (TGR). To understand the effects of the TGR on vertical distribution of suspended sediment concentration (SSC) and estimation accuracy of mean concentration, vertical sediment concentration and flow velocity data at the Shashi and Jianli hydrological stations in the reach before and after the impoundment were collected. Comparisons and analysis of vertical profiles of SSC before and after the TGR impoundment show that after the impoundment of the TGR, due to the coarsening of sediment particle size, the reduction in sediment load, and the significant decrease in sediment saturation, the vertical distribution of SSC in the downstream reaches became more uneven under medium and low water flows, which was reflected in the vertical gradient and the fluctuation degree of SSC significantly increased. In addition, the depth‐average sediment concentrations were calculated by the selected‐point method and the mean values calculated by the "multi‐point method" were regarded as the "true mean" to evaluate the accuracy of the mean value calculated by the "few‐point method." It was found that the relative errors for the selected‐point method were mainly positive before impoundment but mainly negative after impoundment. Additionally, the correction factors of one‐point, two‐point, and three‐point methods and the position of the near‐bed substituted point for the five‐point method were given to reduce the error when the point measurements were used to calculate the depth‐average sediment concentration in the downstream reaches. [ABSTRACT FROM AUTHOR]

Accurate runoff forecasting plays a vital role in issuing timely flood warnings. Whereas, previous research has primarily focused on historical runoff and precipitation variability while disregarding other factors' influence. Additionally, the prediction process of most machine learning models is opaque, resulting in low interpretability of model predictions. Hence, this study develops an ensemble deep learning model to forecast runoff from three hydrological stations. Initially, time‐varying filtered based empirical mode decomposition is employed to decompose the runoff series into several internal mode functions (IMFs). Subsequently, the complexity of each IMF component is evaluated by the multi‐scale permutation entropy, and the IMFs are classified into high‐ and low‐frequency portions based on entropy values. Considering the high‐frequency portions still exhibit great volatility, robust local mean decomposition is adopted to perform secondary decomposition of the high‐frequency portions. Then, the meteorological variables processed by the Relief algorithm and variance inflation factor features are employed as inputs, the individual subsequences of secondary and preliminary decomposition as outputs to the bidirectional gated recurrent unit and extreme learning machine models. Random forests (RF) are introduced to nonlinear ensemble the individual predicted sub‐models to obtain the final prediction results. The proposed model outperforms other models in various evaluation metrics. Meanwhile, due to the opaque nature of machine learning models, shapley is employed to assess the contribution of each selected meteorological variable to the long‐term trend of runoff. The proposed model could serve as an essential reference for precise flood prediction and timely warning. Plain Language Summary: The volatility of a river's runoff has increased in recent years due to various factors, including extreme rainfall and storms. This has further intensified the frequency and severity of flooding disasters. To address this issue, our study has developed an ensemble deep learning model that combines data from multiple sources to accurately predict river runoff. This model not only enhances the interpretability of the data, but also provides a crucial reference for effective flood forecasting and early warning systems. Model concerns include: meteorological variables affecting runoff are feature‐selected and incorporated into the model, so that the inclusion of multi‐source information makes the model richer; historical data are secondarily decomposed and differentiated into high‐frequency and low‐frequency components to mine more informative features; high and low‐frequency components are predicted separately using the applicable model and ensembled in a non‐linear way, so that the prediction results are more closed to the reality; explainable artificial intelligence is applied to mine important hydrological elements that affect runoff. Key Points: The proposed ensemble deep learning model achieves high prediction accuracy for runoff from multiple stationsClassify internal mode functions (IMFs) into high‐frequency and low‐frequency components and use secondary mode decomposition to extract more informative featuresRelief and variance inflation factor (VIF) as feature selection methods to extract key meteorological factors and interpretable analyses by shapley [ABSTRACT FROM AUTHOR]

The runoff change in a large river is significant for hydrological event monitoring, such as floods and droughts. In this paper, we attempt to invert the river flow change based on the surface displacements observed by the continuous global navigation satellite system (GNSS) stations in the Wuhan section of the Yangtze River (WYR). We establish a two‐dimensional model accounting for deformation from a line load in an elastic half‐space to estimate the annual water load change from the GNSS data. The results show that the inverted line load from the annual maximum displacement change observed by the GNSS is Ne=2.30×108N·m−1 ${N}_{e}=2.30\times {10}^{8}\mathrm{N}\cdot {\mathrm{m}}^{-1}$, which is in good agreement with the river load from the hydrological station. This paper demonstrates a low‐cost and practical method to river flow research in local areas, which is also a creative application for the GNSS. Plain Language Summary: The runoff change in large rivers is an important element for flood and drought monitoring. Hydrological stations are used to monitor the water load change. Because of the high cost of construction and maintenance, there are few hydrological stations in most areas, and the unpredictable noise of hydrological stations influences the stability and precision of the results. We use the vertical displacements observed by the global navigation satellite system (GNSS) to estimate the river load and find that the results agree with the calculated water load change from hydrological stations. Thus, the GNSS can be an alternative for runoff change research, with low cost and high efficiency. In this study, we find a new application for the GNSS to water runoff change in local areas. Key Points: We propose a new method for estimate the river load change using the continuous global navigation satellite system (GNSS) dataA simple two‐dimensional line load on Elastic half‐space can invert the river load with considerable accuracy in local areasThe forward modeling prove that the modeled displacement agrees with the observed displacement from the GNSS [ABSTRACT FROM AUTHOR]

The Weihe River has experienced a significant runoff decline in the past few decades, but the detailed and systematic analysis of different sub‐regions of the Weihe River basin (WRB) for a long time is insufficient. Based on the data of five hydrological stations from 1957 to 2018, this study investigated the variation of annual runoff both in the whole Weihe River basin (WWRB) and its sub‐regions: the upper, middle, and lower reaches of the Weihe River (URWR, MRWR, LRWR, respectively), the Jing River basin (JRB), and the Beiluo River basin (BLRB). Moreover, the contribution of climate change and anthropogenic activities on runoff change was quantified by double mass curve (DMC) and hydrological sensitivity analysis (HSA) methods. The results showed that runoff of the URWR, MRWR, JRB, BLRB, and WWRB showed significant downward trends, and with the change‐point years of 1993, 1990, 1996, 1994, and 1993, respectively. Both results of DMC and HSA showed that anthropogenic activities were the main factors for runoff reduction. The contribution of human activities was largest in the JRB and BLRB, whereas lowest in the MRWR. Over the study period, land use has changed significantly in the basin, mainly manifested in the reduction of farmland, and the increase of construction land and grassland, indicating that intense anthropogenic activities have taken place. Moreover, the total water consumption of the WWRB increased evidently, which exacerbated the contradiction between supply and demand of water resources. The results of HSA showed that runoff was more sensitive to precipitation than to Ep. Precipitation reduced the runoff, while Ep increased runoff in the basin. The results of this study are helpful for understanding the regional hydrological situation in more detail, and can act as a reference for formulating reasonable water resources allocation schemes. [ABSTRACT FROM AUTHOR]

THE REMARKABLE RISE OF PROCESS HYDROLOGY IN CHINA Gu was at the leading edge of process hydrology in China during its remarkable ascent in the past several decades. Through the 1980s and 1990s, Gu authored a number of papers in the Chinese and English literature (Gu, [4]; Gu, [5]; Gu, [6]; Gu, [7]; Gu, [8]; Gu, [9], [10] - summarized in an important review paper in Gu et al., [11]) that showed - in many cases for the first time - the controls on the spatial and temporal evolution of soil water, groundwater and streamflow from the catchment. WEI-ZU GU AND HYDROHILL Gu was a research professor at the Nanjing Institute of Hydrology and Water Resources when he set up the Chuzhou Hydrology Laboratory and now-famous Hydrohill catchment. Following the USGS delegation to China, the USGS team reciprocated, and Gu came to the United States about a year later and toured the Mattole watershed, the Panola watershed in Georgia and other USGS research sites. [Extracted from the article]

Under the changing climate, the natural characteristics of hydrological processes are assumed to have been intensified, and the volatility of these processes to have increased significantly. However, the applicability of traditional time series analysis methods and the commonly used Gaussian GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) to streamflow modeling has been limited. Although SV-type (stochastic volatility) models have appeared as competitive alternatives to GARCH-type models owing to their flexibility in modeling volatilities, they have not been applied in hydrological studies. Therefore, this study assesses the applicability of SV models to streamflow modeling using daily streamflow series from 21 hydrological stations in the Yellow River basin. Considering the influence of different types of GARCH and residual distributions, 7 hybrid models with variance fluctuation (fractional autoregressive integrated moving average-GARCH) based on 9 distributions are compared to determine the optimal model for each station. Then 4 SV-type models are introduced and compared with the results of the optimal GARCH-type model to verify their applicability. The results show that: (a) the Gaussian distribution is not applicable in both GARCH-type and SV-type models for modeling daily streamflow; (b) although the GARCH-type models are shown to describe the volatility of streamflow processes and improve the modeling performance, large residuals have been observed in the results of the analysis during the peak flow period; and (c) SV-type models can better describe the streamflow series with time-varying variance and accurately capture the occurrence of peak streamflow. The findings of this study offer practical and promising time series analysis methods for daily streamflow modeling. [ABSTRACT FROM AUTHOR]

After decades of comprehensive management, the hydrology and sediment dynamics of the middle Yellow River Basin have changed significantly. However, the comprehensive evaluation of the water and sediment regimes and its potential attribution at the regional scale are limited. In this study, the hydrological characteristics and in‐reach sediment budget in the Coarse Sandy Hilly Catchments (CSHC) region and their potential attribution were investigated by using data from hydrological stations in the mainstream and tributaries and data from soil and water conservation measures (SWCMs) in different river reaches. The results indicated that the runoff and sediment load of the mainstream showed obvious spatial heterogeneity, both of which revealed a very significant decreasing trend from 1956 to 2018 (P < 0.01). The spatial heterogeneity of sediment load along the mainstream was more obvious than that of streamflow, and the Toudaoguai and Fugu stations had the largest difference in sediment transport trends. During the P1 period (1956‑1968), the streamflow of each reach was sufficient, and the riverbeds of the mainstream and channel on both banks were subject to serious scouring. In the P2‑P3 period (1969‑2018), in‐reach water decreased continuously, and the mainstream began to show a process from slight scouring to no scouring and even sediment deposition. Except for climate change being the main factor in streamflow reduction during the P2 period (1969‑1999) at the Fugu and Wubao stations, anthropogenic activities were the primary factors leading to the reduction in streamflow and sediment load in the CSHC region. Under the influence of the same measures, the sediment reduction rate in this region was greater than the runoff reduction rate. Furthermore, the SWCMs in different reaches indicated great diversity in the benefits of water and sediment reduction. Therefore, zoning regulation of the CSHC region should be carried out in the future, and the sustainable development of the regional vegetation ecosystem should be maintained. [ABSTRACT FROM AUTHOR]

The Double‐Excess (DE) model is a flood forecasting model which was developed to reflect the characteristics of runoff generation in semi‐arid and semi‐humid areas. However, the empirical unit hydrograph used in the subbasin confluence module often has low precision because of the difficulty associated with parameter quantification. This study improves the subbasin confluence module of the DE model by coupling the geomorphologic instantaneous unit hydrograph (GIUH) to establish the improved DE model (DE‐GIUH) to calculate the subbasin confluence based on topographic physical characteristics. The improved model is applied to the Wangjiahui Hydrological Station Basin in Northern China. Compared with the conventional DE model and the widely used hydrologic modelling system (HEC‐HMS) model, the results show that DE‐GIUH improved flood forecasting, including the component peak discharge, flood peak appearance time and flood progress. The qualified rate (QR) of all three models reached grade A (QR ≥ 85.0%). However, the proportion of the deterministic coefficient (DC) reaching grade B or above (DC ≥ 0.70) improved from 50% (HEC‐HMS) and 30% (DE) to 90% (DE‐GIUH) in the calibration period, and from 62.5% and 25% to 75% in the validation period. In particular, for large and medium floods, the proportion of DC reaching grade B and above is 100% for DE‐GIUH, which is much higher than that of the other two models. The proposed improved model provides an alternative method for flood prediction in ungauged areas. [ABSTRACT FROM AUTHOR]

Water resources systems in arid regions are sensitive to climate change, which critically impacts the water cycle. In this study, we applied historical hydrometeorological data, CMIP5 data, and a large‐scale hydrological model (Community Land Model–Distributed Time‐Variant Gain Model [CLM–DTVGM]) to study the impact of climate change on the hydrological cycle (i.e., runoff, actual evapotranspiration (ETa), and terrestrial water storage [TWS]) under different scenarios at the Aksu River basin (ARB) located in the arid region of northwest China. The primary findings of this study: (a) As the determination coefficient (R2) and Nash–Sutcliffe efficiency coefficient (NSE) reached desirable levels (R2 ≥ 0.583, NSE ≥ 0.371, and root‐mean‐square error ≤ 155.727), the CLM–DTVGM achieved a better simulation of runoff in the ARB; under climate change, the runoff depth in the irrigation area became shallower and followed a decreasing trend, with a minimum depth of 0.5 mm and a significant decreasing trend of −8 mm·a−1. (b) Along with changes in the precipitation and temperature of the baseline period (i.e., 1980–2010), runoff, ETa, and TWS were predicted to change significantly in future scenarios. (c) Climate change significantly impacted the historical runoff from the Shaliguilanke and Xiehela hydrological stations, with correlation coefficients larger than 0.9; however, the runoff from the Alaer hydrological station was not affected. However, runoff, ETa, and TWS in the ARB were very closely correlated with climate change in the future scenarios, with correlation coefficients exceeding 0.9. Related research in the future would be important for guiding the sustainable development of the ARB. [ABSTRACT FROM AUTHOR]

In large‐scale watersheds, only the calibration of parameters for the outlet may ignore spatial heterogeneity and fail to meet the simulation accuracy of local areas. Based on the runoff observation data of three hydrological stations (Qingyang, Yangjiaping and Zhangjiashan) in the Jinghe River Watershed, single‐ and multi‐site calibration strategies were designed to investigate the performance and applicability of the Soil and Water Assessment Tool (SWAT) in predicting the monthly runoff of nested catchments and evaluate the differences in parameter sensitivity between the upstream and downstream. (i) The two calibration strategies showed little difference in the simulation accuracy of the watershed outlet; the Nash–Sutcliffe efficiency (NSE) and determination coefficient (R2) were approximately 0.8 and 0.6, respectively, and the percentage of bias (PBIAS) was mostly <15%. The single‐site one‐by‐one calibration was significantly better than the multi‐site joint calibration at the interior points of the watershed. Among them, Qingyang decreased most obviously in the joint calibration with Zhangjiashan, with both NSE and R2 < 0.5, whereas Yangjiaping was >0.5 in combination with the other two sites. (ii) The sensitive parameters obtained by the two calibration strategies were different, and different parameters were effective for different‐sized catchments because hydrological processes exhibit astounding variability at all scales. The single‐site one‐by‐one calibration was mainly affected by the hydrological processes of the local catchment, whereas the multi‐site joint calibration was largely constrained by the sensitive parameters of the single‐site calibration. (iii) Parameters at different scales and locations were related to the problem of scaling and regionalization. The multi‐site joint calibration did not significantly improve the model performance of the watershed outlet but increased the capacity for synchronous identification of local sensitive parameters when compared to single‐site calibration. These findings are expected to provide experience for parameter calibration in other similar large‐scale watersheds and to lay a good foundation for the accurate identification of other related hydrological behaviours at watershed scales. [ABSTRACT FROM AUTHOR]

Sediment load of China's Yellow River has dramatically decreased due to the interplay of climate variability and human activities in the past decades. However, the contribution of individual driving factors and the detailed spatial distribution of sediment load at a catchment scale were not well understood. In the study, we quantitatively assessed the relative contributions of individual climatic (i.e. precipitation) and anthropogenic (i.e. vegetation restoration, terrace construction) driving factors to sediment load variations in the largest tributary of the Yellow River, Weihe River. The employed annual sediment load measurements and rainfall data for 1961–2015 were collected at 15 hydrological and 60 meteorological stations that were widely distributed in the basin. Changing trends, periodicity, and abrupt changes of hydro‐climatic variables were detected using the non‐parametric Mann–Kendall test, the empirical mode decomposition method, and Pettitt's test. Results showed that annual sediment load presented significantly decreasing trends at 12 hydrological stations. Annual rainfall erosivity showed a mixed tendency, with the changing trends varying among different regions. A 3‐year periodicity was identified in the annual sediment load at three main stream gauging stations. Abrupt changing points in sediment load primarily occurred in the 1990s and early 2000s at all of the 15 hydrological stations, which were largely attributed to human activities. The increase in vegetation cover was responsible for approximately 40.6%, 37.4%, and 54.7% of the sediment load reduction in the main stream of the Weihe River, the Jinghe River, and the Beiluohe River, respectively. Meanwhile, terrace construction accounted for 19.7%, 43.8%, and 9.9% of the sediment variation, respectively. Conversely, precipitation change accounted for 5.7%, 12.4%, and 8.3% of sediment load reduction, respectively. Overall, vegetation restoration and terrace construction were found to be the two dominating factors for sediment load reduction in the study area. [ABSTRACT FROM AUTHOR]

Bohai Sea, with the highest suspended sediment concentration in the world, has experienced a sharp decrease in sea surface suspended sediment concentration (SSSC) in the latest two decades. However, limited by the shortage of long‐term field observations, the spatiotemporal characteristics and mechanisms of the long‐term variation in the SSSC are still unclear. Based on remote sensing data, this study reconstructed the spatiotemporal SSSC distribution from 2003 to 2016, and found significant spatial difference in decadal SSSC variation in the Bohai Sea. The largest decadal SSSC decrease was observed in the southern Bohai Sea with an average annual decrease of 1.3 mg/L (decrease of 4.4% per year), while significant SSSC increase was observed in the central Bohai Sea with largest annual increase of 0.4 mg/L (increase of 5.0% per year). Significant seasonal differences in the SSSC decreasing were also revealed, and the SSSC decrease in winter and spring (0.46 mg/L/a) was 27.8% higher than that in summer and autumn (0.36 mg/L/a). Decadal wind speed data measured at 14 meteorological stations around the Bohai Sea indicated that wind speed reduction played the most important role in the decadal decrease in SSSCs, and significant SSSC decrease can only be found in sea areas with a significantly reduced wind speed. In addition, although the runoff and sediment discharge of the Yellow River also decreased during 2003–2016, they were not related to the spatiotemporal variation of SSSCs and their direct impact was limited to the range of 15 km from the estuary. Plain Language Summary: Long‐term and drastic changes in suspended sediment concentration (SSC) have been observed in the seas all over the world. The drastic changes of SSC inevitably have a significant impact on the marine ecological environment, geomorphic evolution, and biogeochemical cycle, and their variation mechanism have become the focus of geoscience research. It is generally believed that the long‐term changes of SSC in the seas near the large rivers were mainly affected by the changes of river runoff and sediment discharge. However, taking the Bohai Sea of China as an example, based on the data of satellite remote sensing, meteorological and river hydrological stations, this study clarifies that although the sediment discharge of the Yellow River, which ranks second in the world, has decreased greatly, its direct impact on SSC variation is limited to the adjacent estuarine areas. This work also points out that wind speed reduction plays the most important role in the decadal SSC decrease in the Bohai Sea. Influenced by climate change and human activities, estuaries and coastal seas around the world are facing the same problem of long‐term SSC variation. The conclusions of this work provide useful information for the long‐term SSC variation and regulation mechanism study. Key Points: Decadal decreasing trend of the suspended sediment concentration in the Bohai Sea was revealed using MODIS remote sensing dataWind speed reduction played the most important role in the decadal decrease in SSSCsThe direct impact of the Yellow River discharge decreasing on the decadal SSSC variations was limited to within 15 km from the estuary [ABSTRACT FROM AUTHOR]

Despite the potential of remote sensing for monitoring reservoir operation, few studies have investigated the extent to which reservoir releases can be inferred across different spatial and temporal scales. Through evaluating 21 reservoirs in the highly regulated Greater Mekong region, remote sensing imagery was found to be useful in estimating daily storage volumes for within‐year and over‐year reservoirs (correlation coefficients [CC] ≥ 0.9, normalized root mean squared error [NRMSE] ≤ 31%), but not for run‐of‐river reservoirs (CC < 0.4, 40% ≤ NRMSE ≤ 270%). Given a large gap in the number of reservoirs between global and local databases, the proposed framework can improve representation of existing reservoirs in the global reservoir database and thus human impacts in hydrological models. Adopting an Integrated Reservoir Operation Scheme within a multi‐basin model was found to overcome the limitations of remote sensing and improve streamflow prediction at ungauged cascade reservoir systems where previous modeling approaches were unsuccessful. As a result, daily regulated streamflow was predicted competently across all types of reservoirs (median values of CC = 0.65, NRMSE = 8%, and Kling‐Gupta efficiency [KGE] = 0.55) and downstream hydrological stations (median values of CC = 0.94, NRMSE = 8%, and KGE = 0.81). The findings are valuable for helping to understand the impacts of reservoirs and dams on streamflow and for developing more useful adaptation measures to extreme events in data sparse river basins. Key Points: Satellite images are useful to estimate daily storage volumes for within‐year, over‐year reservoirs, but not for run‐of‐river reservoirsThe proposed framework can improve representation of local dams in the global reservoir databases and human impacts in hydrological modelsDaily regulated streamflow can be reasonably modeled by an integrated reservoir operation scheme of a multi‐basin model and satellite images [ABSTRACT FROM AUTHOR]

Sediment deposition and intensified eutrophication of the Miyun Reservoir are directly affecting the water quality in Beijing, China, owing to water pollution issues in the Chaohe River Basin, which contains the main inflow river of the reservoir. This study analysed the runoff, sediment, total nitrogen and total phosphorus load simulation results from three observation stations using the Hydrological Simulation Program–FORTRAN model (Nash efficiency coefficient [NSE] = 0.65–0.8, R2 = 0.62–0.92) and a statistical regression model (R2 = 0.55–0.79). Results indicate that applying these models in combination to basins from which pollution source data are difficult to obtain can fully utilize the advantages of both models. The parameter uncertainty analysis of the model's runoff and pollution‐related parameters is discussed from the basis of the generalized likelihood uncertainty estimation analysis method. Further, using the Mann–Kendall test and the double cumulative curve method, an attribute analysis of climate change and human activities in the basin was carried out. Results show that in the context of global climate change, fundamental ways to achieve the goal of adaptive catchment management include adjusting the land use structure, optimizing the land use mode and carrying out comprehensive management of soil and water loss with vegetation restoration as the main body. [ABSTRACT FROM AUTHOR]

Incorporating 50 years of flood data for the Manas River Kenswat Hydrological Station from 1957 to 2006, the Pettitt test and Mann–Kendall trend test are used to analyse non‐stationarity of the flood characteristic sequences. Moreover, the Pearson type‐III (P‐III) distribution, the mixed distribution (MD) and conditional probability distribution (CPD) models are employed to analyse frequency and to calculate the design flood process line. The results showed that the annual maximum peak discharge and the annual maximum flood volume are most likely to change in 1993. The MD model considering the non‐stationarity of the flood sequence is more accurate than the CPD model and the traditional P‐III distribution model. There are significant differences in the design flood process lines of the 1996 typical flood process obtained by the three methods using the same frequency scaling method. In addition, under different design standards, the design value of the MD model is 20–53% smaller than the design value approved in 2008 (approved by China Renewable Energy Engineering Institute) and 4–48% higher than the traditional P‐III distribution design value. The results can provide a new reference for the management of non‐stationary floods in Manas River. [ABSTRACT FROM AUTHOR]

Runoff signatures, including low flow, high flow, mean flow and flow variability, have important implications on the environment and society, predominantly through drought, flooding and water resources. Yet, the response of runoff signatures has not been previously investigated at the global scale, and the influencing mechanisms are largely unclear. Hence, this study makes a global assessment of runoff signature responses to the El Niño and La Niña phases using daily streamflow observations from 8217 gauging stations during 1960–2015. Based on the Granger causality test, we found that ~15% of the hydrological stations of multiple runoff signatures show a significant causal relationship with El Niño–southern oscillation (ENSO). The quantiles of all runoff signatures were larger during the El Niño phase than during the La Niña phase, implying that the entire flow distribution tends to shift upward during El Niño and downward during La Niña. In addition, El Niño has different effects on low and high flows: it tends to increase the low and mean flow signatures but reduces the high flow and flow variability signatures. In contrast, La Niña generally reduces all runoff signatures. We highlight that the impacts of ENSO on streamflow signatures are manifested by its effects on precipitation (P), potential evaporation (PET) and leaf area index (LAI) through ENSO‐induced atmospheric circulation changes. Overall, our study provides a comprehensive picture of runoff signature responses to ENSO, with valuable insights for water resources management and flood and drought disaster mitigation. [ABSTRACT FROM AUTHOR]

Ice reserve estimates is a fundamental prerequisite for water resources management. We selected the UIB (upper Indus river basin) as study area because it contains the most abundant mid‐latitude glaciers outside the polar region, however, the ice reserve estimates remain unclear due to the harsh topography. In this study, we validated the parameters of the GlabTop2 model (Glacier Bed Topography version 2) using the ice thickness measured by GPR (ground‐penetrating radar) and compared the "GPR‐measured ice thickness and ice bed elevation" versus "the estimated results obtained from GlabTop2." Integrated with IDW (inverse distance weighted) interpolated results of glaciers of various sizes, a reasonable parametric scheme (τ = 120 kPa and f = 0.8) of GlabTop2 was applied on vast amounts of glaciers in the UIB region. The GlabTop2 estimates indicated that the ice thickness of the UIB varied from 0 to 736.0 ± 110.0 m, with an average value of 74.5 ± 11.2 m. A significant spatial heterogeneity exists in the sub‐basins. The Shyok, Shigar and Hunza that contain the most abundant ice reserve. Lesser quantities are stored in the Western Himalaya and Hindu Kush ranges, which account for 11.3 % and 6.7 % of the total ice reserve in the UIB, respectively. A total volume of 1162.4 ± 175.1 km3 of glacier can be converted to 1046.2 ± 157.6 Gt ice reserve; this is 13.6 times the annual average discharge obtained from the outlet of the Besham hydrological station. We aim to present estimates that can provide the baseline information for glaciology study of the Indus river. [ABSTRACT FROM AUTHOR]

The longitudinal functional connectivity of a river–lake–marsh system (RLMS) refers to the actual water‐mediated transport of material from upstream to downstream areas along a spatial gradient and is fundamental to understand hydrological and biogeochemical cycles. However, due to a lack of consensus on appropriate data and methods, the quantification of connectivity is still a challenge, especially at the catchment scale. We developed a new method to evaluate longitudinal functional connectivity based on fluxes of materials (water, sediment, and chemicals) along a RLMS. The calculation of fluxes is based on the longitudinal pattern of terrain gradient, which influences transport efficiency, and on contributions from hillslopes, which set the initial spatial template of material loading to the RLMS. We evaluate the contributions from hillslopes to RLMS based on a new modified version of the index of sediment connectivity (IC) proposed by Borselli et al. (2008) and revised by Chartin et al. (2017).We applied this method to the Baiyangdian Basin covering an area of 3.4 × 104 km2 in China and quantified longitudinal functional connectivity during normal, wet, and dry periods(April, July and December) in year 2016. We found that areas with good structural connectivity exhibited poor functional connectivity during the normal and dry periods. Modelling testing with discharge data from hydrological stations and measured chemicals from Baiyangdian Lake was satisfactory in test periods. We conclude that public data and Digital Elevation Model‐derived information can be used to reliably map the longitudinal functional connectivity of RLMSs. The proposed method provides a useful tool for monitoring and restoring the longitudinal functional connectivity of RLMSs and our results indicate that efforts aimed at restoring functional connectivity in RLMSs should take into account landscape patterns that can greatly influence fluxes in the watershed. [ABSTRACT FROM AUTHOR]

Establishing reliable streamflow time series is essential for hydrological studies and water‐related decisions, but it can be both time‐consuming and costly since streamflow is typically calculated from water level using rating curves based on numerous calibration measurements (gaugings). It can take many years of gauging data collection to estimate reliable rating curves, and even then extreme‐flow estimates often still depend on rating curve extrapolation. Hydraulically modeled rating curves are a promising alternative to traditional methods as they can be rapidly derived with few concurrent stage‐discharge gaugings. We introduce a novel framework for Rating curve Uncertainty estimation using Hydraulic Modelling (RUHM), based on Bayesian inference and physically based hydraulic modeling for estimating stage‐discharge rating curves and their associated uncertainty. The framework incorporates information from the river shape, hydraulic configuration, and the control gaugings as well as uncertainties in the gaugings and model parameters. We explored the interaction of uncertainty sources within RUHM by (1) assessing its performance at two Swedish stations, (2) investigating the sensitivity of the results to the number and magnitude of the calibration gaugings, and (3) evaluating the importance of prior information on the model parameters. We found that rating curves with constrained uncertainty could be estimated using only three gaugings for either low or low and medium flows that have a high probability of occurrence, thereby enabling rapid rating curve estimation. Prior information about the water‐surface slope‐stage relation, obtainable from site surveys, was needed to adequately constrain uncertainty estimates. Plain Language Summary: Reliable streamflow time series are essential for water‐related decisions. However, it can take several years and numerous measurements to establish a reliable streamflow time series, and these may still be associated with large uncertainty. To address these issues, we developed a novel framework that couples uncertainty assessment with hydraulic modeling of the relation between water level and streamflow at a hydrological monitoring station using information about the physical characteristics of the channel. This relation between water level and streamflow, known as the rating curve, is the basis for calculating streamflow time series from the water level time series measured at hydrological monitoring stations. We explored the interaction of different uncertainty sources on rating curve estimation at two Swedish stations and found that rating curves could be modeled with high confidence (i.e., low uncertainty) using only three observations for either low flows or low and medium flows. Since such flow conditions occur often and are easy to measure (at least relative to the rare and hard‐to‐measure high flows) our framework has an advantage over traditional approaches by potentially allowing for more rapid rating curve estimation. Key Points: An uncertainty framework using physically based hydraulic modeling was developed for rapid rating curve estimationRating curves with constrained uncertainty were estimated using only three gaugings for either low or low and medium flowsPrior information about the water‐surface slope‐stage relation was needed to obtain reliable results [ABSTRACT FROM AUTHOR]

This study analyses the changes in sediment transport regimes in the middle Yellow River basin (MYRB) using sediment rating parameters. Daily streamflow and suspended sediment concentration data were collected at 35 hydrological stations from the 1950s to 2016, which can be divided into three periods based on the type and intensity of human activities: the base stage before 1970, the restraining stage from 1971 to 1989, and the restoration stage after 2002. Data within each period were fitted by log‐linear sediment rating curves and the sediment rating parameters were utilized to analyse the spatial and temporal variations in sediment transport regimes. The results show that sediment rating parameters are indicative of sediment transport regimes. In the base stage and the restraining stage, the hydrological stations can be categorized into four groups based on their locations on the rating parameter plot. The stations with small drainage basins were characterized by the highest sediment transport regime, followed by those located in the coarse‐particle zone, the loess zone, and the mountainous/forest zone. In the restoration stage, the difference in sediment transport regimes between different geomorphic zones became less distinguishable than in previous stages. During the transition from the base stage to the restraining stage, sediment rating parameters showed no significant changes in sediment transport regimes in all four geomorphic groups. During the transition from the restraining stage to the restoration stage, significant changes were observed in the coarse‐particle zone and the mountain/forest zone, indicating that the revegetation programme and large reservoirs imposed a stronger influence on sediment transport regimes in these two zones than in the rest of the MYRB. This study provides theoretical support for evaluating sediment transport regimes with sediment rating parameters. [ABSTRACT FROM AUTHOR]

The increase in hydrological extremes during the last two decades has had a significant impact on natural and social environments. These hydrological extremes depend greatly on changes in the meteorological parameters. The task of this research was to evaluate the impact of meteorological factors (snow water equivalent and heavy rainfall) on the formation of spring floods in the basins of the Nemunas, Lielupė and Venta rivers. Five Lithuanian rivers (Venta, Šešuvis, Mūša, Merkys and Žeimena) from these basins were analysed in detail. These rivers fall within the Western, Central and Southeastern hydrological regions of Lithuania. Long‐time‐series data for daily discharge, precipitation and thickness of snow cover from 12 meteorological and five hydrological gauging stations were used. The evaluation of the relation between these factors was carried out for two periods: 1961–1987 and 1988–2014. The relation between the maximum discharge of the spring flood, the maximum snow water equivalent before the flood and the precipitation amount 10 days before the flood was analysed by multiple regression analysis. The high correlation co‐efficients between the observed and predicted maximum discharges of the spring flood for the created regression models fluctuated between 0.63 and 0.86. The verification of the selected regression model was performed with Hydrologiska Byråns Vattenbalansavdelning (HBV) software, which also showed a high correlation co‐efficient (0.71). The applied methodology of this research could be used for better perception of flood‐formation consequences in different hydrological regions of Europe. The multiple regression analysis of the maximum discharge of spring flood (Qmax, m3/s) conducted with the maximum snow water equivalent before the flood (SWEmax, mm) and the precipitation amount 10 days before the flood (P10, mm) was carried out for five rivers in Lithuania. The reliability of the regression models shows high correlation co‐efficients (0.63–0.86) between the observed and predicted Qmax. To verify the regression models, hydrological modelling with Hydrologiska Byråns Vattenbalansavdelning (HBV) software was performed. The analysis revealed close correlation co‐efficients (0.71–0.78) related to the observed Qmax (Obs), the modelled Qmax of the HBV (Mod), the predicted Qmax of the regression model of the reference period (RegRef), the predicted Qmax of the regression model of 1961–1987 (Reg1), the predicted Qmax of the regression model of 1988–2014 (Reg2), and their range for the verification period (1986–2005). [ABSTRACT FROM AUTHOR]

Quantification of climate forcing of glacial hydrological systems at the decadal scale is rare because most measurement stations are too far downstream for glacier impacts to be clearly detected. Here we apply a measure of daily hydrograph entropy to a unique set of reliable, high‐altitude gauging stations, dating from the late 1960s. We find a progressive shift to a greater number of days with diurnal discharge variation as well as more pronounced diurnal discharge amplitude. These changes were associated with the onset of rapid warming in the 1980s as well as declining end of winter snow depths as inferred from climate data. In glaciated catchments, lower winter snow depths reduce the magnitude and duration of snowpack buffering and encourage the earlier onset of glacier ice exposure, with associated lower surface albedo and more rapid melt. Together, these processes explain the increase in the observed intensity of diurnal discharge fluctuations. Plain Language Summary: River basins that have a high proportion of ice cover are particularly sensitive to climate warming. Daily variations in insolation and temperature typically lead to fluctuations in snow and/or ice melt and thus a daily rise and fall in river flow. Snow, and the glaciers themselves, can buffer this rise and fall. For six high mountain Alpine basins, we show that daily discharge fluctuations are changing due to climate warming at the decadal scale, with both increasing daily discharge maxima and reducing daily discharge minima. These changes reflect decreased snow accumulation at the end of winter, reducing the buffering and increasing the onset of rapid glacier melt. Key Points: A Shannon Entropy Index is used to quantify changing daily hydrograph shape for six high‐altitude Alpine basins, with a range of degrees of glacier cover, between 1969 and 2014For the five most glaciated basins, there has been an increase in the frequency and amplitude of diurnal discharge fluctuations since the onset of more rapid warming in the 1980sThese changes in diurnal discharge are driven by reduced snow buffering of ice melt and runoff resulting from declining end of winter snow depths and greater mean annual temperatures [ABSTRACT FROM AUTHOR]

Climate change and human activities are strongly influencing the eco-hydrological processes of the Chinese Loess Plateau. It is challenging to investigate the spatiotemporal changes of water and sediment yields and identify their potential causes. In this study, we used the annual runoff index (WI) and specific sediment yield (SSY) derived from 58 hydrological stations to quantify the changes and attempted to explain their potential causes. The WI exhibited significant ( P < 0.05) decrease ranging from −0.1 to −2.6 mm yr−1 during 1957-2012 in 44 sub-catchments. Similarly, the SSY in 52 sub-catchments reduced in a range between −2.86 and −636 Mg km−2 yr−1. The region of Toudaoguai-Longmen has extremely high SSY ranging from 8000 to 41 000 Mg km−2 yr−1 during 1957-1969. Budget analysis suggested that the area of Lanzhou-Toudaoguai contributed limited sediment but extracted large amount of water. The areas with negative SSY were increasing and mainly distributed along the mainstream of the Yellow River. The Loess plateau was becoming drier and warmer since the 1950s, whereas the intensive human activities including water withdrawal, soil and water conservation projects and the operation of dams and reservoirs are the dominant factors for the decline in WI and SSY on the Loess Plateau. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Natural Flood Management (NFM) techniques aim to reduce downstream flooding by storing and slowing the flow of stormwater to river channels. These techniques include a range of measures, including setback stormwater outfalls and the physical restoration of channels and floodplains, to improve the natural functioning of catchments. An additional benefit of NFM measures is the potential reduction in sediment and pollutant delivery to the channel. Urban development releases a variety of heavy metal and nutrient pollutants that enter rivers through stormwater outfalls with adverse effects on the aquatic ecosystem. In this study, the influence of channel modification and quality of the river habitat on the sediment quality surrounding stormwater outfalls was assessed. Sediment samples were taken at several outfalls within the Johnson Creek catchment, Oregon, USA, and analysed for a variety of urban pollutants. The level of river habitat quality and modification at each site were assessed using a semi-quantitative scoring methodology. Significant increases in pollutant levels were observed at outfalls, with a greater and more variable increase at direct compared to setback outfalls. Removal efficiency of certain pollutants was found to be significantly correlated to the level of habitat quality or modification (for Fe, Ba, Sn, Mg, P, K) indicating that more natural reaches had greater potential for pollutant removal. The findings highlight the multiple benefits associated with NFM and river restoration approaches in relation to sediment quality and pollutant content. © 2016 The Authors River Research and Applications Published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The effects of mountain pine beetle (MPB)-induced tree mortality on a headwater hydrologic system were investigated using an integrated physical modeling framework with a high-resolution computational grid. Simulations of MPB-affected and unaffected conditions, each with identical atmospheric forcing for a normal water year, were compared at multiple scales to evaluate the effects of scale on MPB-affected hydrologic systems. Individual locations within the larger model were shown to maintain hillslope-scale processes affecting snowpack dynamics, total evapotranspiration, and soil moisture that are comparable to several field-based studies and previous modeling work. Hillslope-scale analyses also highlight the influence of compensating changes in evapotranspiration and snow processes. Reduced transpiration in the Grey Phase of MPB-induced tree mortality was offset by increased late-summer evaporation, while overall snowpack dynamics were more dependent on elevation effects than MPB-induced tree mortality. At the watershed scale, unaffected areas obscured the magnitude of MPB effects. Annual water yield from the watershed increased during Grey Phase simulations by 11 percent; a difference that would be difficult to diagnose with long-term gage observations that are complicated by inter-annual climate variability. The effects on hydrology observed and simulated at the hillslope scale can be further damped at the watershed scale, which spans more life zones and a broader range of landscape properties. These scaling effects may change under extreme conditions, e.g., increased total MPB-affected area or a water year with above average snowpack. [ABSTRACT FROM AUTHOR]

As a result of climate change/variation and its aggravation by human activities over the past several decades, the hydrological conditions in the middle Yellow River in China have dramatically changed, which has led to a sharp decrease of streamflow and the drying up of certain tributaries. This paper simulated and analysed the impact of sediment-trapping dams (STDs, a type of large-sized check dam used to prevent sediment from entering the Yellow River main stem) on hydrological processes, and the study area was located in the 3246 km2 Huangfuchuan River basin. Changes in the hydrological processes were analysed, and periods of natural and disturbed states were defined. Subsequently, the number and distribution of the STDs were determined based on data collected from statistical reports and identified from remote sensing images, and the topological relationships between the STDs and high-resolution river reaches were established. A hydrological model, the digital Yellow River integrated model, was used to simulate the STD impact on the hydrological processes, and the maximum STD impact was evaluated through a comparison between the simulation results with and without the STDs, which revealed that the interception effect of the STDs contributed to the decrease of the streamflow by approximately 39%. This paper also analysed the relationship between the spatial distribution of the STDs and rainfall in the Huangfuchuan River basin and revealed that future soil and water conservation measures should focus on areas with a higher average annual rainfall and higher number of rainstorm hours. © 2015 The Authors Hydrological Processes Published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

In this study, the spatial and temporal variability of summer (June-July-August, JJA) streamflow over Romania, as recorded at 46 hydrological stations over the period 1935-2010 is analysed. An empirical orthogonal function analysis and a canonical correlation analysis (CCA) were used to characterize the spatial and temporal variability of summer streamflow and its relationship with large-scale atmospheric factors. The dominant summer mode captures in-phase variability of river flow anomalies over the entire country, while the second mode of variability is characterized by a northwest-southeast dipole, emphasizing the influence of topography over the streamflow variability. Based on a CCA analysis, more than 50% of the summer streamflow variability is shown to be influenced by cloud cover and summer temperatures, via the modulation of precipitation and potential evapotranspiration. In general, positive (negative) streamflow anomalies, at country level, are associated with cyclonic (anticyclonic) circulation, the advection ofmoist (warm and dry) air, enhanced (reduced) precipitation and positive (negative) cloud cover anomalies. [ABSTRACT FROM AUTHOR]

Many studies have analysed the nonstationarity in single hydrological variables due to changing environments. Yet, few researches have been done to investigate how the dependence structure between different individual hydrological variables is affected by changing environments. To investigate how the reservoirs have altered the dependence structure between river flows at different locations on the Hanjiang River, a time-varying copula model, which takes the nonstationarity in the marginal distribution and/or the time variation in dependence structure between different hydrological series into consideration, is presented in this paper to perform a bivariate frequency analysis for the low-flow series from two neighbouring hydrological gauges. The time-varying moments model with either time or reservoir index as explanatory variables is applied to build the time-varying marginal distributions of the two low-flow series. It's found that both marginal distributions are nonstationary, and the reservoir index yields better performance than the time index in describing the nonstationarities in the marginal distributions. Then, the copula with the dependence parameter expressed as a function of either time or reservoir index is applied to model the variable dependence between the two low-flow series. The copula with reservoir index as the explanatory variable of the dependence parameter has a better fitting performance than the copula with the constant or the time-trend dependence parameter. Finally, the effect of the time variation in the joint distribution on three different types of joint return periods (i.e. AND, OR and Kendall) of low flows at two neighbouring hydrological gauges is presented. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Using a nonstationary flood frequency model, this study investigates the impact of trends on the estimation of flood frequencies and flood magnification factors. Analysis of annual peak streamflow data from 28 hydrological stations across the Pearl River basin, China, shows that: (1) northeast parts of the West and the North River basins are dominated by increasing annual peak streamflow, whereas decreasing trends of annual peak streamflow are prevailing in other regions of the Pearl River basin; (2) trends significantly impact the estimation of flood frequencies. The changing frequency of the same flood magnitude is related to the changing magnitude or significance/insignificance of trends, larger increasing frequency can be detected for stations with significant increasing trends of annual peak streamflow and vice versa, and smaller increasing magnitude for stations with not significant increasing annual peak streamflow, pointing to the critical impact of trends on estimation of flood frequencies; (3) larger-than-1 flood magnification factors are observed mainly in the northeast parts of the West River basin and in the North River basin, implying magnifying flood processes in these regions and a higher flood risk in comparison with design flood-control standards; and (4) changes in hydrological extremes result from the integrated influence of human activities and climate change. Generally, magnifying flood regimes in the northeast Pearl River basin and in the North River basin are mainly the result of intensifying precipitation regime; smaller-than-1 flood magnification factors along the mainstream of the West River basin and also in the East River basin are the result of hydrological regulations of water reservoirs. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Although ensemble prediction systems (EPS) are increasingly promoted as the scientific state-of-the-art for operational flood forecasting, the communication, perception, and use of the resulting alerts have received much less attention. Using a variety of qualitative research methods, including direct user feedback at training workshops, participant observation during site visits to 25 forecasting centres across Europe, and in-depth interviews with 69 forecasters, civil protection officials, and policy makers involved in operational flood risk management in 17 European countries, this article discusses the perception, communication, and use of European Flood Alert System (EFAS) alerts in operational flood management. In particular, this article describes how the design of EFAS alerts has evolved in response to user feedback and desires for a hydrographic-like way of visualizing EFAS outputs. It also documents a variety of forecaster perceptions about the value and skill of EFAS forecasts and the best way of using them to inform operational decision making. EFAS flood alerts were generally welcomed by flood forecasters as a sort of 'pre-alert' to spur greater internal vigilance. In most cases, however, they did not lead, by themselves, to further preparatory action or to earlier warnings to the public or emergency services. Their hesitancy to act in response to medium-term, probabilistic alerts highlights some wider institutional obstacles to the hopes in the research community that EPS will be readily embraced by operational forecasters and lead to immediate improvements in flood incident management. The EFAS experience offers lessons for other hydrological services seeking to implement EPS operationally for flood forecasting and warning. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Flash floods represent one of the deadliest and costliest natural disasters worldwide. The hydrological analysis of a flash flood event contributes in the understanding of the runoff creation process. This study presents the analysis of some flash flood events that took place in a complex geomorphological Mediterranean River basin. The objective of the present work is to develop the thresholds for a real-time flash flood forecasting model in a complex geomorphological watershed, based on high-frequency data from strategically located hydrological and meteorological telemetric stations. These stations provide hourly real-time data which were used to determine hydrological and meteorological parameters. The main characteristics of various hydrographs specified in this study were the runoff coefficients, lag time, time to peak, and the maximum potential retention. The estimation of these hydrometeorological parameters provides the necessary information in order to successfully manage flash floods events. Especially, the time to peak is the most significant hydrological parameter that affects the response time of an oncoming flash flood event. A study of the above parameters is essential for the specification of thresholds which are related to the geomorphological characteristics of the river basin, the rainfall accumulation of an event, the rainfall intensity, the threshold runoff through karstic area, the season during which the rainfall takes place and the time intervals between the rainstorms that affect the soil moisture conditions. All these factors are combined into a real-time-threshold flash flood prediction model. Historical flash flood events at the downstream are also used for the validation of the model. An application of the proposed model is presented for the Koiliaris River basin in Crete, Greece. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The abrupt changes in the streamflow and sediment load at nine hydrological stations of the Pearl River basin were systematically analysed by using the simple two-phase linear regression scheme and the coherency analysis technique. Possible underlying causes were also discussed. Our study results indicated that abrupt changes in the streamflow occurred mainly in the early 1990s. The change points were followed by significant decreasing streamflow. Multiscale abrupt behaviour of the sediment load classified the hydrological stations into two groups: (1) Xiaolongtan, Nanning and Liuzhou; and (2) Qianjiang, Dahuangjiangkou, Wuzhou, Gaoyao, Shijiao and Boluo. The grouped categories implied obvious influences of water reservoirs on the hydrological processes of the Pearl River. On the basis of analysis of the locations and the construction time of the water reservoirs, and also the time when the change points occurred, we figured out different ways the water reservoirs impacted the hydrological processes within the Pearl River basin. As for the hydrological variation along the mainstream of the Pearl River, the water reservoirs have considerable influences on both the streamflow and sediment load variations; however, more influences seemed to be exerted on the sediment load transport. In the North River, the hydrological processes seemed to be influenced mainly by climate changes. In the East River, the hydrological variations tended to be impacted by the water reservoirs. The study results also indicated no fixed modes when we address the influences of water reservoirs on hydrological processes. Drainage area and regulation behaviour of the water reservoirs should be taken into account. The results of this study will be of considerable importance for the effective water resources management of the Pearl River basin under the changing environment. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Measurement of the stable isotopes oxygen-18 and deuterium in water is an important tool to characterize aquifer recharge sources. In the driest areas of the Mediterranean, this application is of special interest due to the scarcity of water and the resulting common incidence of human influence on natural hydrological systems. The Motril-Salobreña detrital aquifer (southern Spain) is a clear example of such an impact as inhabitants have designed irrigation systems and a dam was recently built across the course of the Guadalfeo River, which feeds the aquifer. The sampling of (river or ground) water has allowed the determination of stable isotope contents (oxygen-18 and deuterium), both temporally and spatially, and the relative importance of the main recharge sources in certain sectors. In addition, we were able to infer seasonal trends and to improve existing knowledge of the main flow paths and the position of a seasonal groundwater divide. Data analysis shows evaporation plays a minor role (despite the high temperatures in the zone), scarce rainwater influence, and the overwhelming contribution of recharge from the Guadalfeo River and from the carbonate aquifer (Escalate aquifer) in contact with the Motril-Salobreña aquifer. Irrigation return flow during the summer months comprises the main recharge due to the significant volumes of water that infiltrate. The construction of the dam will almost certainly entail great changes in the current dynamics of the hydrogeology of the Motril-Salobreña aquifer; therefore, knowledge of its behaviour is crucial in order to carry out sustainable use of its groundwater resources. [ABSTRACT FROM AUTHOR]

The article examines the detection of trends in extreme hydrological events for steam flow gauging stations in Canada. It notes that the application of the Mann-Kendall non-parametric test is involved in the trend analysis. It mentions that decreasing trends in flow magnitude and event timing are showed in annual and spring maximum flows.

The article presents a study on the ecological status of Ter Vell, an eutrophic Mediterranean coastal lagoon in Northeast Iberian Peninsula after being flooded by excessive water from the irrigation during the past decades, and other man-made changes of its hydrological regime. It analyzes whether the hydrological changes caused by management actions have affected the lagoon's status. The suitability of several physiochemical and biological indicators for the assessment of the ecological status of this kind of coastal ecosystem are also presented. Methods involved and the indicators used in the study are also discussed.

The article discusses the homogeneity of the precipitation data in Turkey. It says that outlier trimming and homogeneity checking were both performed on a monthly basis at various lengths using the Standard Normal Homogeneity Test in 267 hydrological stations. It likewise states that outlier values are usually found during dry summer months over the southern part of the country. Moreover, it claims that there are several stations that could either not be tested efficiently or could be classified as inhomogeneous.

The article discusses the calibration and verification of the estimates of stream power in a river channel with varying discharge at a given station. The authors use the split sampling approach to show that the change in stream power is not shared equally among hydraulic variables. They argue that the unevenness depends on the boundary conditions to be satisfied by the channel under consideration. They conclude that there is good agreement between the predicted hydraulic variables and the observed stream measurements.

The article discusses the estimate of stream power in a river channel with varying discharge at a given station. According to the authors, the temporal variation in channel form defined by flow depth and channel width is a function of hydraulic variables such as energy slope, friction, and flow velocity. They argue that the change in stream power is distributed among these hydraulic variables based on the boundary conditions which the stream channel satisfies. The theory of minimum energy dissipation when applied to the principle of maximum entropy leads to the simplified minimum stream power.