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Recent droughts have severely threatened water security in many regions worldwide. Reservoirs, designed to combat droughts and secure water supply partially, are reported failing to fill up to the total capacity due to severe droughts. How bad is climate affecting reservoir filling up on a global scale? This issue has not been studied. We present a big picture of reservoirs in crisis using satellite altimetry. Thanks to the unique characteristics of CryoSat‐2, 525 reservoirs worldwide were investigated during 2010–2022. Results show that most reservoirs (93%) are found not fully filled up at least once. About 21% of reservoirs, which are mainly located in the Southern Hemisphere, show a significant decline in water levels. Moreover, about 20% of reservoirs with larger level fluctuations (>3 m) are located in less developed economies, indicating informed operation rules are needed. Further analyses indicate reservoirs are largely affected by extreme climate events, such as ENSO. Plain Language Summary: A reservoir is an artificial lake where water is collected and stored for various purposes, such as flood control, irrigation, hydropower generation, industrial use, etc. In a changing climate, drought events can cause a decline in the natural flow of streams and rivers to the reservoirs. Consequently, many of the functions provided by the reservoir might be halted if the drought continues, just like the cases of Lake Powell and Lake Mead. The past decade saw several record‐breaking global annual temperatures. How have global reservoirs been affected in terms of the filling up? Leveraging more than a decade of CryoSat‐2 altimetry observations, we provided a global picture of this issue. We found that 93% of studied reservoirs have not been fully filled up at least once during 2010–2022. Our analyses revealed that droughts are the most probable culprits. About 86% of the 398 reservoirs with accessible SPEI data exhibited significant susceptibility to drought, while 43% of the 525 reservoirs demonstrated notable sensitivity to ENSO events. These findings have important implications for future reservoir operations to cope with more intensive drought events. It also means the benefits and costs of both existing and planned reservoirs need to be re‐assessed to take adaptation strategies. Key Points: Water levels of reservoirs in the southern hemisphere show a declining trendAbout 93% of the 525 studied reservoirs have not been fully filled up at least once in the past 12 yearsLess developed economies need to develop informed reservoir operation rules to cope with climate change [ABSTRACT FROM AUTHOR]

River stage fluctuation (RSF) is one of the most important factors influencing the physical, chemical, and ecological aspects of rivers. Despite widespread interest in river stage variations, there is currently no global benchmark of RSF and their spatial patterns. Our understanding of these characteristics remains limited. We used Sentinel‐3 altimetry data to establish a benchmark data set for RSF in wide rivers (width >1 km). We conducted an initial investigation of the spatial patterns and inter‐annual variability associated with RSF. The results show a wide range of fluctuation amplitudes spanning from a mere 1 to 18 m. Notably, rivers in semi‐arid regions exhibit more pronounced fluctuations. Further analyses indicate that human activities play a significant role in RSF. The results are of substantial interest to the scientific community, as they are closely linked to critical hydrological processes, including floods, river‐floodplain dynamics, river‐groundwater interaction, greenhouse gas emissions, and river restoration. Plain Language Summary: Rivers show a seasonal rhythm over time due to multiple processes. A critical aspect of the rhythm is the river stage, which resembles the pulse of a river as it rises and falls. Traditionally, river stages have been monitored using gauging stations. However, these local monitoring networks fall short in providing a comprehensive global perspective on river stage fluctuations, which are directly linked to significant events like floods and droughts. Advanced Earth Observation techniques now offer a means to better understand the pulse of rivers on broader scales. Specifically, satellite radar altimetry serves as a valuable tool for river stage records by measuring water surface elevation, thereby providing insights into the normality or abnormality of river conditions. This study represents one of the first global‐scale investigations into the patterns of river stage fluctuations and inter‐annual variability spanning from 2016 to 2022. Moreover, this new data set holds practical value for related studies, such as the validation of the average depth of the channel when the river is full, the assessment of river channel storage variation, the facilitation of river navigation, stepwise ecological restoration, and more. Key Points: Stage fluctuations of large rivers were estimated globally for the first time using satellite radar altimetryRivers in semi‐arid regions have larger fluctuations than those in other climate regionsThe top five river basins with the highest stage fluctuations (>7 m) are the Orinoco, Mississippi, Yangtze, Irrawaddy, and Amazon basins [ABSTRACT FROM AUTHOR]

With the booming big data techniques, large-sample hydrological analysis on streamflow regime is becoming feasible, which could derive robust conclusions on hydrological processes from a big-picture perspective. However, there is a lack of a comprehensive global large-sample dataset for components of the streamflow regime yet. This paper presents a new time series dataset on global streamflow indices calculated from daily streamflow records after data quality control. The dataset contains 79 indices over seven major components of streamflow regime (i.e., magnitude, frequency, duration, changing rate, timing, variability, and recession) of 41 263 river reaches globally on yearly and multiyear scales. Streamflow indices values until 2022 are covered in the dataset. Time span of the time series dataset is from 1806 to 2022 with an average length of 36 years. Compared to existing global datasets, this global dataset covers more stations and more indices, especially those characterizing the frequency, duration, changing rate, and recession of streamflow regime. With the dataset, research on streamflow regime will become easier without spending time handling raw streamflow records. This comprehensive dataset will be a valuable resource to the hydrology community to facilitate a wide range of studies, such as studies of hydrological behaviour of a catchment, streamflow regime prediction in data-scarce regions, as well as variations in streamflow regime from a global perspective. The dataset can be accessed at 10.57760/sciencedb.07227 (Chen et al., 2023a). [ABSTRACT FROM AUTHOR]

Satellite radar altimetry has become an important data source supplementing in situ water level. For practical reasons, a radar altimeter can only record reflected echoes within its range window. Therefore, water surface elevation must fall within the range window. To this end, the Sentinel‐3 radar altimetry mission is configured with a new tracking function (i.e., open loop) to position its range window based on an onboard a priori elevation of ground targets. We found that Sentinel‐3 is unable to observe recently built reservoirs due to the incorrect onboard elevations. To overcome this issue, four approaches are proposed to improve the a priori elevation for inland water bodies, particularly reservoirs. These approaches can significantly increase data availability of Sentinel‐3 over reservoirs and can be used to prepare the onboard elevations of reservoirs and lakes for future missions such as Sentinel‐6, Sentinel‐3C/‐3D, and the Surface Water and Ocean Topography (SWOT) mission. Plain Language Summary: Satellite radar altimetry is increasingly being used for hydrological studies. However, it is still challenging to deliver high‐quality data over inland water bodies, that is, lakes, rivers, and reservoirs. One of the reasons is that the altimeter cannot easily identify the water surface elevation due to highly variable terrain elevation along the satellite flight path. In other words, the data delivered may not contain valid information for water bodies. To address this issue, Sentinel‐3 is configured with a new function, which informs the altimeter about the expected elevation of the water surface. However, this function demands a priori knowledge of the altitude of the ground targets. We present four approaches to improve the a priori information to increase data availability over inland water bodies, specifically reservoirs. Key Points: The Sentinel‐3A altimeter cannot deliver useful data over many reservoirs (constructed after 2005) in open‐loop tracking mode with OLTC V5Defining correct a priori elevation information is the key to increasing data availability over reservoirsFour approaches are proposed to define the most accurate onboard a priori elevation [ABSTRACT FROM AUTHOR]

• IMERG early and final are comprehensively evaluated across Mainland China. • All evaluated products perform better in humid areas than in arid areas. • Hydrological simulations are carried out over 300 catchments across Mainland China. • IMERG early provides comparable performance. • IMERG performs better than TRMM 3B42 as hydrological model forcing. Accurate precipitation estimates are essential for reliable hydrological simulations of fluxes and states. Satellite precipitation products have been widely used for hydrological applications, especially for ungauged regions. The Global Precipitation Measurement (GPM) product is starting to provide a new generation of precipitation estimates. This work first evaluates several GPM Integrated Multi-satellite Retrievals (IMERG) against gauge-based precipitation over Mainland China for a two-year period (2016–2017), and then explores the feasibility of using GPM to force a lumped hydrological model over 300 catchments of varying size and climate. The analysis indicates that IMERG Final run estimates (gauge-adjusted) agree well with gauge-based precipitation at daily scale, while IMERG Early run estimates (near-real time without gauge adjustments) are consistently lower than the rain gauge records. Nevertheless, both Final run and Early run estimates are slightly better than TRMM 3B42 estimates in terms of rainfall detection skill. Moreover, all three products show better skill over humid regions than over high elevation zones. When used as hydrological model forcing, IMERG Final and Early estimates provide comparable performances to gauge-based precipitation. However, TRMM 3B42 performs relatively poor in terms of hydrological simulation. Moreover, models generally perform better in humid than in arid areas for all three products. The evaluation sheds light on how IMERG-driven hydrological predictions perform in different regions across China. The findings also indicate the potential of IMERG Early run for flood forecasting and Final run for climatological/hydrological modeling in ungauged or poorly gauged basins. [ABSTRACT FROM AUTHOR]

Hydrodynamic modeling is an essential tool to simulate water level for flood forecasting and risk assessment. However, parameterization of hydrodynamic models is challenging due to poor knowledge of bathymetry and lack of gauge data. In this study, we present an approach for calibrating spatially distributed Strickler coefficient and river datum simultaneously by regularized inversion. Calibration was carried out using altimetry derived observations of water surface elevation in the Songhua River (China). Synthetic experiments show that spatial variability of model parameters can be well constrained by geodetic altimetry, e.g., CryoSat-2 and SARAL, and to a lesser extent by Envisat and Jason-1. However, Jason-2 can only recover some of the parameters. We also find that a higher accuracy of observations does not proportionally decrease parameter uncertainty for all cross sections. Instead, high spatial sampling density helps to identify the spatial variability of parameters. Real-world calibrations indicate that CryoSat-2 by far outperforms other altimeters in terms of parameter identification. We conclude that high spatial resolution is more important than temporal resolution and observation accuracy for calibrating parameters of large-scale river models. The findings demonstrate the added value of geodetic satellite altimetry for inversion of spatially resolved parameter fields. This study is timely because the upcoming Surface Water and Ocean Topography mission will significantly improve spatial and temporal resolution of spaceborne observations of water surface elevation, and hydraulic models need to be prepared for the uptake of these data. • Water surface elevation observations are used to calibrate a hydrodynamic model. • Spatially distributed model parameters (datum and roughness) can be constrained. • Geodetic altimeters are more skillful in constraining the variability of parameters. • Higher accuracy of WSE does not proportionally decrease parameter uncertainty. [ABSTRACT FROM AUTHOR]

Abstract Water surface elevation (WSE) is an essential quantity for water resource monitoring and hydrodynamic modeling. Satellite altimetry has provided data for inland water bodies. The height that is derived from altimetry measurement is ellipsoidal height. In order to convert the ellipsoidal height to orthometric height, which has physical meaning, accurate estimates of the geoid are needed. This paper evaluates the suitability of geodetic altimetric measurements for improvement of global geoid models over a large lake in the Tibetan Plateau. CryoSat-2 and SARAL/AltiKa are used to derive the high-frequency geoid correction. A validation of the local geoid correction is performed with data from in-situ observations, a laser altimetry satellite (ICESat), a Ka-band radar altimetry satellite (SARAL) and a SAR radar altimetry satellite (Sentinel-3). Results indicate that the geodetic altimetric dataset can capture the high-resolution geoid information. By applying local geoid correction, the precision of ICESat, SARAL and Sentinel-3 retrievals are significantly improved. We conclude that using geodetic altimetry to correct for local geoid residual over large lakes significantly decreases the uncertainty of WSE estimates. These results also indicate the potential of geodetic altimetry missions to determine local geoid residual with centimeter-level accuracy, which can be used to improve global and regional geopotential models. Highlights • CryoSat-2 has very noisy measurements over rapidly changing topography. • Geodetic CryoSat-2 & AltiKa are used to derive a short-wavelength geoid correction. • The precision of ICESat, AltiKa and Sentinel-3 retrievals are significantly improved. • Geodetic altimetry can be incorporated to improve geopotential models. [ABSTRACT FROM AUTHOR]

Satellite altimetry has been widely used for inland water monitoring and modeling in the present decade. In this paper, the availability, data quality, and quantity of a number of spaceborne radar altimetry missions (including Topex/Poseidon (TP), ERS-2, Envisat, Jason-1/−2/−3, CryoSat-2, Saral, and Sentinel-3) are investigated. This is, to the best of our knowledge, the first paper to investigate the influences of onboard trackers, satellite flying directions, and land contamination on Level-1 waveforms and Level-2 measurements over large mountainous lakes. The analyses were conducted over eight Tibetan lakes, which are of varying sizes from ca. 93 to 1046 km2 and are sampled by multiple altimeters. From the results presented in this paper, it is demonstrated that the previous generation of altimeters, such as TP, Jason-1, ERS-2, and Envisat, shows a higher percentage of data unavailability and lower valid observation rates. Investigations of Level-1 waveforms show onboard tracker failing in locking on the lake surface, resulting in data loss or invalid measurements. In addition, the onboard tracking systems are sometimes unstable, resulting in larger along-track standard deviations (SD) (SD > 15 cm). In contrast, the recent generation of altimeters, i.e., Jason-3 and Sentinel-3 with open-loop tracking mode, significantly increases the data availability (> 90% passes and > 60% individual observations) and delivers higher precision measurements (SD around 10 cm). Moreover, the waveform leading edge is very consistent, indicating more stable onboard tracking. Higher quality Jason-3 and Sentinel-3 data allow monitoring of sub- and quasi-monthly lake variations, which are not revealed by e.g., TP and ERS-2 data due to poorer signal-to-noise ratios. Exceptionally, Saral Ka-band altimeter, operated in closed-loop tracking mode, is less affected by flying directions and land contamination (topography and landscapes), delivering high quality measurements (SD around 7 cm for 40 Hz). This study provides a comprehensive comparison of multiple altimeters in monitoring lakes in mountainous areas, and demonstrates the substantial improvements achieved in the past decades. However, care has to be taken when merging data from old generation altimetry missions over mountainous lakes. The lessons learned from these Tibetan lakes can be taken across to other mountain lakes. • Comprehensive assessment of multiple altimeters performance over Tibetan lakes. • Investigation of influences of onboard trackers on Level-1 waveforms and Level-2 measurements. • Onboard tracking failure is largely responsible for erroneous measurements contained in the GDR. • Distinctive improvements (∼ 100% data availability & < 10 cm precision) achieved during 1992–2021. [ABSTRACT FROM AUTHOR]

Surface water bodies (lakes, reservoirs, and rivers) are key components of the water cycle and are important water resources. Water level and storage vary greatly under the impacts of climate change and human activities. Due to sparse in-situ monitoring networks, a comprehensive national-scale monitoring dataset of surface water bodies in China is not available. Over the last two decades, satellite altimetry has been used successfully for inland water monitoring. Here, we use CryoSat-2 radar altimetry to monitor water level variations of large lakes, reservoirs and rivers across China and demonstrate its potential to complement available in-situ monitoring datasets for the country. In this study, over 1000 lakes and reservoirs, and 6 large rivers are investigated. The results show that surface water varied greatly over the past 6 years, e.g. in the Tibetan Plateau, the Junggar Basin, the Northeast China Plain, and the central Yangtze River basin. Estimated changes in volume indicate that surface water variation contributes significantly to terrestrial storage variation, especially in the Qaidam Basin and the Tibetan Plateau. CryoSat-2 is capable of measuring regional-scale river level at high spatial resolution and competitive accuracy as demonstrated by comparison with available in-situ gauging data. The results are encouraging with RMSE values ranging from 0.24 to 0.35 m for the Heilongjiang-Amur River, 0.22 to 0.6 m for the Yellow River and 0.22 to 0.5 m for the Songhua River. Comparatively, accuracy is much lower over the Yangtze and Pearl Rivers (RMSE ~ 2.6 m and ~ 3.3 m), probably due to intensive inland waterway navigation. CryoSat-2 shows great potential for monitoring surface water at national scale in China. [ABSTRACT FROM AUTHOR]

Lakes on the Tibetan Plateau (TP) are of great interest due to their value as water resources but also as an important indicator of climate change. However, in situ data in this region are extremely scarce and only a few lakes have gauge measurements. Satellite altimetry has been used successfully to monitor lake levels. In this study, Cryosat-2 SARIn mode data over the period 2010–2015 are used to investigate recent lake level variations. The estimated water levels of the 70 largest lakes (> 100 km 2 ) on the TP show that 48 lakes reveal a rising trend (avg. 0.28 ± 0.06 m/yr) while the other 22 show a slightly decreasing trend (avg. −0.10 ± 0.04 m/yr). To compare with the change rates during 2003–2009, ICESat data which cover 42 of the 70 lakes are also used. When combining the data, the results show that during the period of 2003–2015, 28 lakes maintained a rising trend and the change rates are comparable. Lakes in the northern part of the TP experienced pronounced rising (avg. 0.37 ± 0.10 m/yr), while lakes in southern part were steady or decreasing even in glaciated basins with high precipitation. Factor analysis indicates that driving factors for lake change are variable due to high spatial heterogeneity. However, autumn/winter temperature plays an important role in lake level change. These results demonstrate that lakes on the TP are still rapidly changing under climate change, especially in northern part of the TP, but the driving factors are variable and more research is needed to understand the mechanisms behind observed changes. [ABSTRACT FROM AUTHOR]

• Three hybridizations that combine HBV simulations with LSTM are used. • The hybrid models outperformed both the standalone LSTM and HBV models. • The tight hybridized model considering the feedback between LSTM and HBV performs the best. • LSTM and HBV can be successfully calibrated with representative short-length data. Accurate and efficient streamflow simulations are crucial in arid and semi-arid regions for water resources management. Process-based hydrological models generally perform inferior in arid and semi-arid catchments. Data-driven machine learning methods show very promising results in terms of prediction accuracy. In this study, we explore the synergies between process-based hydrological model and machine learning model to improve the predictive capability for semi-arid basins. We developed three hybridization approaches that combine the simulations of the Hydrologiska Byråns Vattenbalansavdelning (HBV) model with Long Short-Term Memory (LSTM) neural networks. In particular, one tight hybridization model is developed to consider the feedback between the LSTM model and the HBV model. Further, we investigated the predictive capability of both standalone HBV and LSTM models with short-length data for training, i.e., one-year data in the context of poorly gauged basins. The results show distinct improvements in the three types of hybrid models when compared with the HBV model and standalone LSTM model in terms of both NSE (12.3 % ∼ 25.6 %) and KGE (6 % ∼ 67.9 %). The model performance of the tight hybridization is the best among all the hybrid models, not only in terms of metrics but also hydrological signatures and the simulation of extreme flows. When calibrated with short-length data records, the LSTM was more robust than HBV, producing acceptable NSE and KGE values. Moreover, there is a strong correlation (0.92) between LSTM model performance and the similarity of flow duration curves (FDCs) between streamflow series in the calibration and validation periods. The results suggest that the hybridization of LSTM and HBV may provide an enhanced simulation capacity for semi-arid regions. Besides, the LSTM model can be successfully calibrated with representative short-length data and the characteristics of the representative short-length data are found. This study provides new insights into the potential use of hybridized machine learning in hydrological simulations. [ABSTRACT FROM AUTHOR]

This study focuses on the chemical composition, and the factors controlling it, of the high mountain-rivers in the source region of the Yangtze River on the Tibetan Plateau. By comprehensive and systematic analysis, the chemical signatures, spatial variations of water quality, as well as the factors controlling them are studied. The value of the average total dissolved solids (TDS) is 778 mg/l, ranging from 117 to 5496 mg/l. In order of decreasing concentration, the main cations are Na + , Ca 2 + , Mg 2 + , and K + , while the main anions are Cl − , HCO 3 − , SO 4 2 − , and NO 3 − . Na + and Cl − are the dominant ions, accounting for 74.2% and 63.7% of the total cations and anions, respectively, followed by Ca 2 + and HCO 3 − , which account for 14.3% and 25%, respectively. The Piper diagram shows the main water type to be a Cl − ·HCO 3 − –Na + ·Ca 2 + type. From the Gibbs boomerang model, we conclude that the chemistry of the river water is controlled by lithogenic weathering processes. The Na-normalized ratio end-member diagram indicates that the weathering of silicates and carbonates is relatively significant, on the whole. There exists pronounced regional heterogeneity in the water chemistry and the factors affecting it. The northern rivers, including Chumaer He, Beilu He, and Ranchiqu, are mainly affected by evaporation and crystallization processes, while the southern rivers (Tuotuo He, Gaerqu, and Buqu) show effects from the weathering of carbonates and silicates. [ABSTRACT FROM AUTHOR]

• An efficient and effective steady-state hydraulic model was used for water level simulation; • Simultaneous use of gauging and Unmanned Aerial Vehicles (UAV) observed water level datasets; • Special-temporally varying Manning roughness was calibrated for a 23-km Danish river. Hydraulic roughness (e.g., expressed in terms of Manning's or Strickler's coefficient) is an essential input to numerical hydrodynamic models. One way to estimate roughness parameters is by hydraulic inversion, using observed water surface elevation (WSE) collected from gauging stations, satellite platforms, or Unmanned Aerial System (UAS) altimeters. Specifically, UAS altimetry provides close to instantaneous observations of longitudinal profiles and seasonal variations of WSE for various river types, which are helpful for calibrating roughness parameters. However, it is computationally expensive to run high-resolution hydrodynamic models thousands to millions of times as required for the global optimization of distributed parameter sets (e.g., spatio-temporally varying river roughness). This study presents an efficient calibration approach for hydrodynamic models using a simplified steady-state hydraulic solver, UAS altimetry datasets, and in-situ observations. The calibration approach minimized the weighted sum of a misfit term, spatial smoothness penalty, and an a-priori sinusoidal temporal variation constraint. The approach was first demonstrated for several synthetic calibration experiments, and the results indicated that the global search algorithm accurately recovered the variations of Strickler coefficient (K s) for short river reaches in temporal (due to the seasonal growth cycle of the aquatic vegetation) and spatial (e.g., due to spatially variable density of submerged vegetation) scales. Subsequently, the calibration approach was demonstrated for a real WSE dataset collected at a Danish test site (Vejle Å). In this river, friction is dominated by submerged vegetation growing in the stream and shows strong seasonal and longitudinal variations due to the plant growth cycle and variable vegetation density and species composition. Results indicated that spatio-temporal variation of K s was required to fit in-situ observations and UAS altimetry accurately. This study illustrates how UAS altimetry and hydrodynamic modeling can be combined to achieve an improved understanding and better parameterization of small and medium-sized rivers, where river channel conveyance is controlled by vegetation growth and other spatio-temporally variable factors. [ABSTRACT FROM AUTHOR]

• Multiple satellite missions are used to monitor water storage components in the NCP. • Sentinel-3 altimetry and spectral/SAR imagery are used to monitor surface water storage. • South-to-North Water Diversion project has a significant impact on regional water storage dynamics. Natural conditions of surface water bodies and groundwater aquifers in the North China Plain (NCP) have been altered to meet the ever-growing human water demands. Several water resources management measures have been implemented in recent decades to alleviate groundwater depletion, maintain ecological resilience, and sustain agricultural production. This study aims to investigate their impacts on land water storage, and thus obtain a picture of the spatio-temporal variation of water resources over the NCP. Based on multi-mission earth observation datasets, i.e., altimetry (Sentinel-3), synthetic aperture radar (SAR) and spectral imagery (Sentinel-1/2), gravimetry (GRACE/-FO), and microwave sensors (IMERG), as well as reanalysis datasets, we investigate surface water storage (SWS), soil moisture water storage (SMS), and total water storage (TWS) changes. Groundwater storage (GWS) change is subsequently estimated as the residual of the total storage equation. Results show that TWS declined significantly over the past decades (−1.04 ± 0.05 cm/yr in 2004 to 2020), while SMS rebounded after a decreasing trend from 2004 to 2014. The spatial pattern of TWS variations depicts a particularly severe depletion along provincial boundaries. The SWS dynamics reveal that the volumes of three major NCP reservoirs (Guanting, Miyun, and Danjiangkou) increased significantly since around 2014 when the operation of the South-to-North Water Diversion Middle Route project (SNWDP-MR) started. Moreover, GWS maintained a depletion rate of −1.05 ± 0.08 cm/yr during 2004–2014 over the whole NCP, while the depletion rate accelerated during 2015–2020 (−1.88 ± 0.38 cm/yr). We also found that the GWS depletion in Beijing (−1.20 ± 0.10 cm/yr during 2004–2014 and −0.79 ± 0.44 cm/yr during 2015–2020) and its surrounding areas has been lowered possibly because of the SNWDP-MR. This study shows how multi-mission satellite earth observation products can be combined to monitor water resources at a regional scale and provide spatio-temporally resolved estimates of the impacts of human-induced changes in the inland water cycle. [ABSTRACT FROM AUTHOR]

Reservoirs and dams are essential infrastructure in water management; thus, information of their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) is crucial for understanding their properties and interactions in hydrological and biogeochemical cycles. However, knowledge of these reservoir characteristics is scarce or inconsistent at the national scale. Here, we introduce comprehensive reservoir datasets of 338 reservoirs in China, with a total of 470.6 km 3 storage capacity (50 % Chinese reservoir storage capacity). Given the scarcity of publicly available gauged observations and operational applications of satellites for hydrological cycles, we utilize multiple satellite altimetry missions (SARAL/AltiKa, Sentinel-3A and Sentinel-3B, CroySat-2, Jason-3, and ICESat-2) and imagery data from Landsat and Sentinel-2 to produce a comprehensive reservoir dataset on the WSE, SWA, and RWSC during 2010–2021. Validation against gauged measurements of 93 reservoirs demonstrates the relatively high accuracy and reliability of our remotely sensed datasets. (1) Across gauge comparisons of RWSC, the median statistics of the Pearson correlation coefficient (CC), normalized root mean square error (NRMSE), and root mean square error (RMSE) are 0.89, 11 %, and 0.021 km 3 , with a total of 91 % validated reservoirs (83 of 91) having good RMSE from 0.002 to 0.31 km 3 and NRMSE values smaller than 20 %. (2) Comparisons of WSE retracked by six satellite altimeters and gauges show good agreement. Specifically, the percentages of reservoirs having good and moderate RMSE values smaller than 1.0 m for CryoSat-2 (validated in 30 reservoirs), SARAL/AltiKa (9), Sentinel-3A (34), Sentinel-3B (25), Jason-3 (11), and ICESat-2 (26) are 77 %, 75 %, 79 %, 87 %, 81 %, and 82 %, respectively. By taking advantages of six satellite altimeters, we are able to densify WSE observations across spatiotemporal scales. Statistically, around 96 % of validated reservoirs (71 of 74) have RMSE values below 1.0 m, while 57 % of reservoirs (42 of 74) have good data quality with RMSE values below 0.6 m. Overall, our study fills such a data gap with regard to comprehensive reservoir information in China and provides strong support for many aspects such as hydrological processes, water resources, and other studies. The dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.7251283 (Shen et al., 2021). [ABSTRACT FROM AUTHOR]

Water level or water surface elevation (WSE) is an important state variable of rivers, lakes, and wetlands. Hydrodynamic models of rivers and streams simulate WSE and can benefit from spatially distributed WSE observations, to increase model reliability and predictive skill. This has been partially addressed by satellite radar altimetry, but satellite altimetry is unable to deliver useful data for small rivers. To overcome such limitations, we deployed a radar altimetry system on an unmanned aerial vehicle (UAV), to map spatially distributed WSE. We showed that UAV altimetry can provide observations of WSE with a very high spatial resolution (ca. 0.5 m) and accuracy (ca. 3 cm), in a time-saving and cost-effective way. Furthermore, we investigated the value of this dataset for the calibration and validation of hydrodynamic models. Specifically, we introduced spatially distributed roughness parameters in a hydrodynamic model and estimated these parameters, using the observed WSE profiles along the stream as input. A case study was conducted in the Åmose stream, Denmark. The results showed that UAV-borne WSE can identify significant variations of the Manning–Strickler coefficients, along this small and highly vegetated stream and over time. Moreover, the model performed extremely well using distributed roughness coefficients, but it could not reproduce WSE satisfactorily using uniform roughness. We concluded that distributed roughness coefficients should be considered, especially for small vegetated rivers, to improve model performance, both locally and globally. Spatially distributed parameterizations of the effective channel roughness could be constrained with UAV-borne WSE. This study demonstrated for the first time that UAV-borne WSE can help to understand the variations of hydraulic roughness, and can support efficient river management and maintenance. [ABSTRACT FROM AUTHOR]

Satellite radar altimetry observations of water surface elevation (WSE) have become an important data source to supplement river gauge records. Sentinel-3 is the first radar altimetry mission operating with a synthetic aperture radar (SAR) altimeter at global scale and with a new on-board tracking system (i.e. open-loop), which has great potential in terms of delivering reliable observations of inland water bodies for the next two decades (several future missions include an open-loop tracking mode). In this context, it is very important to investigate the data quality at an early stage. In this study, a comprehensive evaluation of Sentinel-3A (S3A) is conducted at 50 virtual stations (VS) located on a wide range of rivers in China. The evaluation of Level 1 data shows that, over mountain rivers, a good prior surface elevation estimate on-board is vital to deliver useful datasets using the S3A open-loop tracking system. The Open-Loop Tracking Command version 5 (OLTC V5) has significantly improved the placement of the range window, which was misplaced and resulted in lack of data over many mountain rivers prior to OLTC V5 (March 2019). However, application of S3A over mountain rivers still requires careful evaluation, especially before March 2019. Four retrackers are evaluated including a physical SAR Altimetry Mode Studies and Applications retracker (SAMOSA+), a traditional Offset Center Of Gravity (OCOG), a Primary Peak Center Of Gravity (PPCOG), and a modified Multiple Waveform Persistent Peak (MWaPP+) retracker. For 26 VSs in plain areas, retracked WSE data achieved a root mean square error (RMSE) ranging from 0.12 m to 0.9 m. The comparison of retracking methods reveals that SAMOSA+, OCOG, and PPCOG are unable to handle multi-peak waveforms. But the MWaPP+ can significantly improve the accuracy of the estimated WSE over large rivers, especially when the waveforms are contaminated. Moreover, our result shows no considerable difference between medium (ca. 300 m wide) and large (wider than 500 m) rivers. Instead, surrounding topography and homogeneity of surroundings are very important factors influencing the shape of a waveform. For rivers surrounded by lakes, man-made channels etc., special care must be taken when processing altimetry data. Dedicated retracking methods, such as MWaPP+, and sophisticated methods for outlier detection are needed to improve precision over such rivers, as demonstrated here for the Yangtze River. • Exhaustive evaluation of Sentinel-3 water surface elevation over 50 virtual stations across diverse river systems in China • The Open-Loop Tracking Command version 5 (OLTC v5) has significantly improved the data quality over mountain rivers. • A new retracker is proposed to retrack multi-peak waveforms. [ABSTRACT FROM AUTHOR]

Modelling of river flow is an essential tool in water resources management and flood forecasting. Computation of flow in open-channel requires determination of flow resistance, which determines the water surface elevation (WSE) and the flow velocity. Such resistance is typically represented by a roughness parameter, i.e. Manning's coefficient. Currently, uniform coefficient is routinely used in hydrodynamic modelling. A key problem is that uniform value degrades the calculation of WSE. Despite the importance, its variation is not well accounted for due to the lack of high spatial observations of discharge/WSE data.In this context, more efficient methods are needed to deliver high-resolution spatial WSE datasets with a higher resolution than presently available from satellite altimetry missions. Unmanned aerial vehicle (UAV) can provide observations of WSE with very high spatial resolution and data accuracy, in a time-saving and cost-effective way. Here we investigate the potential for identifying spatial-temporal variation of Manning's roughness coefficient via inverse modelling using UAV-borne WSE data in the Åmose river, Denmark. The survey results show that UAV-borne WSE observations have shown an accuracy of ca. 3 cm when compared with in-situ Real Time Kinematic (RTK) GPS observations and a high spatial resolution of ca. 0.5 m. Hydrodynamic modelling shows that UAV-borne WSE data is able to identify the variation of Manning's coefficients; a significant variation exists for such a small and vegetated stream. Moreover, simulation shows overwhelmingly better performance using distributed Manning's coefficient than using spatially uniform value. We conclude that variation of Manning's coefficient for vegetated rivers should be considered in hydrodynamic modelling. As a consequence, application of UAV-borne WSE to determine Manning's coefficient for small rivers is suggested. [ABSTRACT FROM AUTHOR]

With increasing coverage, density, and accuracy of the global inland water altimetry record, remote sensing observations of water surface elevation (WSE) and water surface slope (WSS) are becoming available for the world's rivers. In steady, uniform flows, WSS is invariable, while there is a unique one‐to‐one relationship between WSE and discharge, the rating curve. While the assumptions of steady uniform flow are appropriate for many rivers, they are violated upstream of river confluences. We present a simple analytical hydraulic model of river confluences using the theory of steady, gradually varied flow. We apply the model to four river confluences in the Mississippi‐Missouri river system. We determine the spatial extent of the backwater‐affected zones and map WSE‐discharge and WSS‐discharge relationships. We show that coincident measurements of WSE and WSS from new satellite altimetry missions effectively constrain discharge estimates from space in the backwater‐affected zones upstream of river confluences. Plain Language Summary: New satellite altimetry missions monitor water levels in global rivers at unprecedented spatio‐temporal resolution and accuracy. One principal objective of this monitoring effort is to map river flow in space and time, understand the impacts of climatic change on river flows, and provide river flow estimates for practical water resources applications. In many locations and situations, there is a one‐to‐one relationship between river flow and river water level. This so‐called rating curve can be used to directly translate water level observations into river flow estimates. However, the concept of the rating curve breaks down whenever the flow in the river is significantly different from steady uniform flow, which is the flow occurring in a long and uniform river reach with constant boundary inflow. Upstream of river confluences, conditions are often non‐uniform, because high flow in one tributary can coincide with low flow in the other, leading to significant backwater effects in both tributaries. This study models water level and water surface slope dynamics upstream of river junctions and highlights the value that data sets from new satellite missions provide for understanding the hydraulics around river confluences and for estimating flow upstream of river confluences from space. Key Points: The classic stage‐discharge rating curve concept fails upstream of river confluences because of backwater effectsHydraulic modeling confirms that unique stage‐slope‐discharge relationships exist upstream of river confluencesNew satellite altimetry observations of river stage and slope reveal stage‐slope‐discharge relationships for selected river confluences [ABSTRACT FROM AUTHOR]

Accurate predictions of water surface elevation (WSE) in rivers at high spatial and temporal resolution are important for flood/drought risk assessment and flood/drought forecasting and management. WSE in a river is controlled by three main factors: discharge, riverbed geometry, and hydraulic roughness. In remote and poorly instrumented rivers, discharge and riverbed geometry are highly uncertain and WSE is therefore hard to predict. ICESat-2 laser altimetry provides accurate elevation transects across the river at very high spatial resolution (70 cm along track). This paper demonstrates how ICESat-2 elevation transects can be used to parameterize a basin-scale hydraulic model of a continental-scale river. The workflow is demonstrated for the transboundary Amur River in North-East Asia. Simulated WSE is subsequently validated against a large dataset of in situ and satellite altimetry observations, and we demonstrate that the model can reproduce available WSE observations throughout the basin with an accuracy of 1–2 m. [ABSTRACT FROM AUTHOR]

The geochemistry of natural waters in the Changtang Nature Reserve, northern Tibet, can help us understand the geology of catchments, and provide additional insight in surface processes that influence water chemistry such as rock weathering on the Qinghai–Tibet Plateau. However, severe natural conditions are responsible for a lack of scientific data for this area. This study represents the first investigation of the chemical composition of surface waters and weathering effects in two lake basins in the reserve (Lake Dogaicoring Qiangco and Lake Longwei Co). The results indicate that total dissolved solids (TDS) in the two lakes are significantly higher than in other gauged lakes on the Qinghai–Tibet Plateau, reaching 20–40 g/L, and that TDS of the tectonic lake (Lake Dogaicoring Qiangco) is significantly higher than that of the barrier lake (Lake Longwei Co). Na + and Cl − are the dominant ions in the lake waters as well as in the glacier-fed lake inflows, with chemical compositions mainly affected by halite weathering. In contrast, ion contents of inflowing rivers fed by nearby runoff are lower and concentrations of dominant ions are not significant. Evaporite, silicate, and carbonate weathering has relatively equal effects on these rivers. Due to their limited scope, small streams near the lakes are less affected by carbonate than by silicate weathering. [ABSTRACT FROM AUTHOR]

• Exogenous putrescine promoted the photosynthesis in grape seedlings under drought stress. • Exogenous putrescine activated VvRBOHb and VvRBOHc2 and stimulated H 2 O 2 synthesis. • Exogenous putrescine activated the endogenous polyamine synthetic pathway. • H 2 O 2 was critical for putrescine-mediated drought resistance in grape seedlings. Drought stress poses a significantly constraint on grape growth, development, and yield. Increasing drought resistance is a critical goal of viticulture, especially in the context of global warming. In this study, exogenous putrescine (Put) significantly improved the photosynthetic and antioxidant capacity of drought-stressed Cabernet Sauvignon seedlings, stimulated the biosynthesis of endogenous polyamines, and reinforced the protective impact on organelle structure. Hydrogen peroxide scavenging agent (DMTU) severely undermined the drought resistance conferred by Put. The elimination of H 2 O 2 using exogenous DMTU led to a dramatic reduction in the Fv/Fm value, antioxidant enzyme activity, and endogenous PAs content in the grape leaves. Our observations suggested that Put increased the expression of the nicotinamide adenine dinucleotide phosphate oxidase genes VvRBOHb and VvRBOHc2 , which stimulated the synthesis of H 2 O 2 in the cells. H 2 O 2 functioned as signal molecules and contributed to the regulatory role of Put in enhancing the drought resistance of Cabernet Sauvignon grape seedlings. [ABSTRACT FROM AUTHOR]

Reservoir release is an essential variable as it affects hydrological processes and water availability downstream. This study aims to estimate reservoir release using a satellite-based approach, specially focusing on the impacts of inflow simulations and reservoir water storage change (RWSC) on release estimates. Ten inflow simulations based on hydrological models and blending schemes are used in combination with three RWSC estimates based on two satellite-based approaches. A case study is performed at the Ankang reservoir, China. The results demonstrate that release estimates show high skill, with normalized root-mean-square error (NRMSE) less than 0.12 and Kling-Gupta Efficiency (KGE) over 0.65. The performance of release estimates is varying with and influenced by inflow simulations and RWSC estimates, with NRMSE ranging from 0.09–0.12 and KGE from 0.65–0.74. Based on time-varying Bayesian Model Averaging (BMA) approaches and synthetic aperture radar (SAR) satellite datasets, more accurate inflow and RWSC estimates can be obtained, thus facilitating substantially release estimates. With multi-source satellite datasets, temporal scale of reservoir estimates is increased (monthly and bi-weekly), acting as a key supplement to in situ records. Overall, this study explores the possibility to reconstruct and facilitate reservoir release estimates in poorly gauged dammed basins using hydrological modeling techniques and multi-source satellite datasets. [ABSTRACT FROM AUTHOR]

Satellite altimetry can fill the spatial gaps of in-situ gauging networks especially in poorly gauged regions. Although at a generally low temporal resolution, satellite altimetry has been successfully used for water surface elevation (WSE) estimation and hydrodynamic modeling. This study aims to investigate the contribution of WSE from both short-repeat and geodetic altimetry to hydrodynamic model calibration, and also explore the contribution of the new Sentinel-3 mission. Two types of data sources (i.e., in-situ and satellite altimetry) are investigated together with two roughness cases (i.e., spatially variable and uniform roughness) for calibration of a hydrodynamic model (DHI MIKE 11) with available bathymetry. A 150 km long reach of Han River in China with rich altimetry and in-situ gauging data is selected as a case study. Results show that the performances of the model calibrated by satellite altimetry-derived datasets are acceptable in terms of Root Mean Square Error (RMSE) of simulated WSE. Sentinel-3A can support hydrodynamic model calibration even though it has a relatively low temporal resolution (27-day repeat cycle). The CryoSat-2 data with a higher spatial resolution (7.5 km at the Equator) are proved to be more valuable than the Sentinel-3A altimetry data with a low spatial resolution (104 km at the Equator) for hydrodynamic model calibration in terms of RMSE values of 0.16 and 0.18 m, respectively. Moreover, the spatially variable roughness can also improve the model performance compared to the uniform roughness case, with decreasing RMSE values by 2–14%. Our finding shows the value of satellite altimetry-derived datasets for hydrodynamic model calibration and therefore supports flood risk assessment and water resources management. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) technology can help reduce carbon emissions significantly, but its benefits may be affected by climate change. Few studies have reported on the impact of climate change on the spatial and temporal distribution of solar energy in China based on the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) models, and few have explored the rooftop PV potential. In this study, 16 CMIP6 models are used for evaluation of the inter-annual and seasonal changes of solar irradiance and PV capacity factor under low (SSP1–2.6), medium (SSP2–4.5) and high (SSP5–8.5) greenhouse gas emission scenarios. The effects on the variation of solar irradiance of three factors are examined: clouds, aerosol optical thickness (AOT) and specific humidity. Furthermore, the future power generation potential of rooftop PV is investigated. It is found that the solar irradiance exhibits an upward trend on national level under all the future scenarios, especially for the SSP1–2.6 scenario, with an increasing rate of 1.4 W m−2 decade−1, mainly due to a reduction in AOT. Solar irradiance increases notably in southeast China while increases little in west China, and the level for 2051–2060 remains lower than that for 1960–2014. The PV capacity factor increases in southeast China with increasing solar irradiance, with a maximum increase of about 4% compared to the average PV CF for 1960–2014 and the highest increasing rate being 0.37% decade−1. In addition, to achieve the projected national distributed PV power generation level, >70% of the effective rooftop area needs to be utilized in 2050. This study hopes to enhance understanding of the impact of climate change on solar energy and provide recommendations for future PV planning to better achieve the long-term planetary temperature goal set by the Paris Agreement. • Solar irradiance exhibits an upward trend on national level for 2020–2060 under all future scenarios. • Comparing the solar irradiance for 2020–2060 with 1960–2014, east and west China exhibit opposite results. • PV capacity factor increases significantly in the southeast China, with the highest increasing rate being 0.37% decade−1. • >70% of the effective rooftop area needs to be utilized in 2050 for meeting the projected PV power generation level. [ABSTRACT FROM AUTHOR]

[Display omitted] • Identified HMR's precipitationshed and found transport differences in wet/dry years. • Quantified climate indices' impacts on annual/seasonal moisture variation. • Explored anthropogenic factors' potential impacts on local moisture recycling. Climate change and anthropogenic factors have resulted in intense and frequent droughts and floods in the Hengduan Mountain Region (HMR). Exploring the source supply of evaporation and transportation processes for the precipitation in the HMR can help us understand regional precipitation characteristics and provide valuable insights regarding effective water resource management, disaster prevention, and mitigation. Based on the ERA5 reanalysis data, we identified the annual and seasonal precipitationsheds of the HMR, using the Water Accounting Model-2layer, to investigate the potential mechanisms that drive the changes in the precipitation in the HMR, in terms of external moisture contribution and local recycling. The identified precipitationshed in the HMR varied in response to different types of precipitation during the different seasons. The decrease in the annual precipitation was mainly attributed to the reduced moisture supply from the extended southwest (SW) and northwest (NW) regions, portraying a decreasing trend of −2.08 mm/yr/yr and −0.92 mm/yr/yr, respectively. The detected difference in the moisture sources and transport pathways, in terms of the response of wet and dry precipitation years, can improve our understanding of the moisture patterns of wet and dry years. We could conclude that the increase in moisture from the SW regions, due to El Niño, may have triggered the heavy precipitation in the HMR in 1998. Additionally, the reduction in moisture from the SW regions, due to La Niña, may have triggered an extreme drought in the HMR in 2011. Notably, woodland and water surface expansion tend to weaken local recycling (−0.07 %/yr) after 2000. In the future, the decreasing trend of local recycling will likely be intensified owing to large-scale artificial reservoir construction and the surface changes caused by underlying impoundment. [ABSTRACT FROM AUTHOR]

• A new satellite-based algorithm for detecting rice phenology is proposed. • Feature-based VH, EVI, and NDYI predict rice planting, heading, and harvest dates. • Robustness was confirmed for multiple scales and cropping systems in monsoon Asia. • Algorithm is promising in mapping large-scale high resolution rice phenology map. Knowledge of rice phenology is essential for understanding the agricultural practices and studying its impact on ecosystem services. However, so far, available global-scale rice phenology maps do not provide fine spatiotemporal details of rice phenology in a consistent framework because they rely on the compilation of statistical data. Thus, this paper proposes an algorithm that combines the complementary advantages of Sentinel-1 and Sentinel-2 satellite images to produce large-scale maps that depict rice phenology dynamics. The novelty of this algorithm lies in the correlation with rice phenology features, i.e., rice in water condition and rice color change. The time series of backscattering at Vertical-Horizontal (VH) polarization and Enhanced Vegetation Index (EVI) are proposed to recognize rice planting and heading dates, respectively. For the same time, the Normalized Difference Yellow Index (NDYI) is utilized to detect the rice harvest date for the first time. The proposed algorithm is applied to multiple spatial scales (prefecture, 0.5° gridcell, and site scales) and to multiple rice cropping systems (single, double, and triple croppings) in monsoon Asia. Results reveal that the algorithm is able to accurately detect the rice planting and harvest dates across two rice paddy field distribution maps with moderate-to-high spatial resolution, different validation data, and different rice cropping systems. The bias values of detected planting dates are 2, 0, and 4 days, while that of harvest dates are -2, -5, and -13 days at the prefecture, 0.5° gridcell, and site scales, respectively. These results highlight the potential of this algorithm to generate national, continental, or even global maps of rice phenology dynamics in an efficient manner, which can facilitate research on the impact of rice phenology on rice ecosystem services that echoes environmental and climate change. [ABSTRACT FROM AUTHOR]

The wide distribution of natural lakes over the Tibetan Plateau, the highest and largest plateau on Earth, have received extensive attention due to global warming. In this Review, we examine lake evolution, spatial patterns and driving mechanisms over the Tibetan Plateau. The changes in lake area, level and volume show a slight decrease from 1976 to the mid-1990s, followed by a continuous rapid increase. The spatial patterns show an overall lake growth in the north of the inner plateau against a reduction in the south, which are accompanied by most of the lakes cooling in the north against warming in the south, and longer ice cover duration in the north compared with the south. The changes in lake temperature are negatively correlated with water level variations and lake ice duration. Enhanced precipitation is the dominant contributor to increased lake water storage, followed by glacier mass loss and permafrost thawing. The decadal or longer lake expansion since the mid-1990s could have been driven by the positive phase of Atlantic Multidecadal Oscillation, and clear inflection points of lake area/level identified in 1997/1998 and 2015/2016 are attributed to strong El Niño events. In the near-term, the lakes will continue to expand. Future interdisciplinary lake studies are urgently required to improve understanding of climate-cryosphere-hydrosphere interactions and water resources management. • The TP lakes are experiencing a drastic increase in extents, level and volume with variable spatial-temporal patterns. • The spatial concurrent patterns between lake hydrological variations and physical variables are revealed. • Enhanced precipitation is dominant contributor to lake water gain, followed by glacier mass loss and permafrost thawing. • Decadal lake expansion is driven by positive phase of AMO, and inflection points are attributed to strong El Niño events. [ABSTRACT FROM AUTHOR]

Terrestrial water storage (TWS) is one of the major contributors (along with the solid earth, atmosphere, and the oceans) to excite polar motion. Previous studies on hydrological excitation of polar motion mainly concentrated on the global scale. We started to analyze how regional TWS, e.g. the Amazon River basin, affects polar motion and found it has significant effect on polar motion (Liu et. al., 2018). Given the uneven distribution of terrestrial water storage, the effect of regional water mass change on polar motion remains unclear and needs to be further explored.The aim of this work is to investigate the effect of terrestrial water storage change on polar motion excitation at regional scale. First, we test how polar motion response to TWS changes in different regions. Synthetic experiments show that the excitation from regional water mass change varies with latitude, and the regions around 35°N and 35°S have the most significant effect on polar motion while the regions close to Equator and Poles have a relatively small effect. Second, we investigate the hydrological excitations of about twenty large river basins at different latitudes using GRACE data. Among selected basins, Amur, Lena, Nile, and Parana river basins have significant contribution to polar motion χ1 component (along prime meridian) while Mississippi and Ob river basins have significant contribution to polar motion χ2 component (along 90°W and 90°E). Then, a reconstructed long-term terrestrial water storage change derived from Reanalysis and GRACE data are applied to compute hydrological excitation with different basins to show the true polar motion driven by regional water storage change over decades. Moreover, combined with altimetry, we also investigate the excitation from TWS changes in large lakes. This work is expected to improve the understanding of the relative importance of regional TWSC for polar motion excitation.Reference:Liu S, Deng S, Xingguo M O,Yan H. 2018. Indexing the relationship between polar motion and water mass change in a giant river basin. Science China Earth Sciences: 1065-1077 [ABSTRACT FROM AUTHOR]