Search

Sentinel-3 is the first satellite altimetry mission to operate both in synthetic aperture radar (SAR) mode and in open-loop tracking mode nearly globally. Both features are expected to improve the ability of the altimeters to observe inland water bodies. Additionally, the two-satellite constellation offers a unique compromise between spatial and temporal resolution with over 65 000 potential water targets sensed globally. In this study, we evaluate the possibility of extracting river water surface elevation (WSE) at catchment level from Sentinel-3A and Sentinel-3B radar altimetry using Level-1b and Level-2 data from two public platforms: the Copernicus Open Access Hub (SciHub) and Grid Processing on Demand (GPOD). The objectives of the study are to demonstrate that by using publicly available processing platforms, such databases can be created to suit specific study areas for any catchment and with a wide range of applications in hydrology. We select the Zambezi River as a study area. In the Zambezi basin, 156 virtual stations (VSs) contain useful WSE information in both datasets. The root-mean-square deviation (RMSD) is between 2.9 and 31.3 cm at six VSs, where in situ data are available, and all VSs reflect the observed WSE climatology throughout the basin. Some VSs are exclusive to either the SciHub or GPOD datasets, highlighting the value of considering multiple processing options beyond global altimetry-based WSE databases. In particular, we show that the processing options available on GPOD affect the number of useful VSs; specifically, extending the size of the receiving window considerably improved data at 13 Sentinel-3 VSs. This was largely related to the implementation of GPOD parameters. While correct on-board elevation information is crucial, the postprocessing options must be adapted to handle the steep changes in the receiving window position. Finally, we extract Sentinel-3 observations over key wetlands in the Zambezi basin. We show that clear seas

Hydrodynamic modeling has been increasingly used to simulate water surface elevation which is important for flood prediction and risk assessment. Scarcity and inaccessibility of in situ bathymetric information have hindered hydrodynamic model development at continental-to-global scales. Therefore, river cross-section geometry is commonly approximated by highly simplified generic shapes. Hydrodynamic river models require both bed geometry and roughness as input parameters. Simultaneous calibration of shape parameters and roughness is difficult, because often there are trade-offs between them. Instead of parameterizing cross-section geometry and hydraulic roughness separately, this study introduces a parameterization of 1D hydrodynamic models by combining cross-section geometry and roughness into one conveyance parameter. Flow area and conveyance are expressed as power laws of flow depth, and they are found to be linearly related in log-log space at reach scale. Data from a wide range of river systems show that the linearity approximation is globally applicable. Because the two are expressed as power laws of flow depth, no further assumptions about channel geometry are needed. Therefore, the hydraulic inversion approach allows for calibrating flow area and conveyance curves in the absence of direct observations of bathymetry and hydraulic roughness. The feasibility and performance of the hydraulic inversion workflow are illustrated using satellite observations of river width and water surface elevation in the Songhua river, China. Results show that this approach is able to reproduce water level dynamics with root-mean-square error values of 0.44 and 0.50m at two gauging stations, which is comparable to that achieved using a standard calibration approach. In summary, this study puts forward an alternative method to parameterize and calibrate river models using satellite observations of river width and water surface elevation.

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 reg

Secular polar drift underwent a directional change in the 1990s, but the underlying mechanism remains unclear. In this study, polar motion observations are compared with geophysical excitations from the atmosphere, oceans, solid Earth, and terrestrial water storage (TWS) during the period of 1981–2020 to determine major drivers. When contributions from the atmosphere, oceans, and solid Earth are removed, the residual dominates the change in the 1990s. The contribution of TWS to the residual is quantified by comparing the hydrological excitations from modeled TWS changes in two different scenarios. One scenario assumes that the TWS change is stationary over the entire study period, and another scenario corrects the stationary result with actual glacier mass change. The accelerated ice melting over major glacial areas drives the polar drift toward 26°E for 3.28 mas/yr after the 1990s. The findings offer a clue for studying past climate‐driven polar motion.

Sentinel-3 is the first satellite altimetry mission to operate both in synthetic aperture radar (SAR) mode and in open-loop tracking mode nearly globally. Both features are expected to improve the ability of the altimeters to observe inland water bodies. Additionally, the two-satellite constellation offers a unique compromise between spatial and temporal resolution with over 65 000 potential water targets sensed globally. In this study, we evaluate the possibility of extracting river water surface elevation (WSE) at catchment level from Sentinel-3A and Sentinel-3B radar altimetry using Level-1b and Level-2 data from two public platforms: the Copernicus Open Access Hub (SciHub) and Grid Processing on Demand (GPOD). The objectives of the study are to demonstrate that by using publicly available processing platforms, such databases can be created to suit specific study areas for any catchment and with a wide range of applications in hydrology. We select the Zambezi River as a study area. In the Zambezi basin, 156 virtual stations (VSs) contain useful WSE information in both datasets. The root-mean-square deviation (RMSD) is between 2.9 and 31.3 cm at six VSs, where in situ data are available, and all VSs reflect the observed WSE climatology throughout the basin. Some VSs are exclusive to either the SciHub or GPOD datasets, highlighting the value of considering multiple processing options beyond global altimetry-based WSE databases. In particular, we show that the processing options available on GPOD affect the number of useful VSs; specifically, extending the size of the receiving window considerably improved data at 13 Sentinel-3 VSs. This was largely related to the implementation of GPOD parameters. While correct on-board elevation information is crucial, the postprocessing options must be adapted to handle the steep changes in the receiving window position. Finally, we extract Sentinel-3 observations over key wetlands in the Zambezi basin. We show that clear seasona

Tibetan lakes are an effective indicator of climate change as they are highly sensitive to and directly affected by climate change. The past decade has seen the seven warmest years on record globally. Such observations have prompted questions about lake changes over the Tibetan Plateau. The dense coverage of the CryoSat-2 altimeter reveals large-scale patterns in this climate change signal. We investigate lake level variations of more than 200 lakes using altimetry observations from CryoSat-2 during the period 2010 to 2019. Combined with GRACE/GRACE-FO, we evaluate the water storage change of lakes and terrestrial water storage (TWS). We find that most studied lakes generally went through three phases of change, that is, rising-hiatus/decline-rising, albeit lakes in the north Tibetan Plateau, show higher rising rates. Results also show that lake levels are widely affected by the 2015/16 El Niño event across the entire Inner Plateau via reduced precipitation. Above normal precipitation during 2016–2018, resulted in a sharp rise of ~1.22 m on average, accounting for 56% of the decadal lake level rise (mean/median: 2.19/1.85 m). TWS in the Inner Tibetan Plateau accumulated a net gain of 70.5 km3, which is dominated by the net gain of lake water storage (ca. 63.3 km3). The interannual TWS variation is found to be associated mainly with precipitation. In particular, extreme conditions such as the 2015/16 El Niño, had a profound negative impact on the TWS. The findings in this study shed new light on the response of Tibetan lakes to recent decadal environmental changes.

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.

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.

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.

Tibetan lakes are an effective indicator of climate change as they are highly sensitive to and directly affected by climate change. The past decade has seen the 7 warmest years on record globally. Such observations have prompted questions about lake changes over the Tibetan Plateau. The dense coverage of the CryoSat‐2 altimeter reveals large‐scale patterns in this climate change signal. We investigate lake level variations of more than 200 lakes using altimetry observations from CryoSat‐2 during the period 2010 to 2019. Combined with GRACE/GRACE‐FO, we evaluate the water storage change of lakes and terrestrial water storage (TWS). We find that most studied lakes generally went through three phases of change, i.e. rising‐hiatus/decline‐rising, albeit lakes in the north Tibetan Plateau show higher rising rates. Results also show that lake levels are widely affected by the 2015/16 El Niño event across the entire inner plateau via reduced precipitation. Above normal precipitation during 2016‐2018, resulted in a sharp rise of ~1.22 m on average, accounting for 56% of the decadal lake level rise (mean/median: 2.19/1.85 m). TWS in the Inner Tibetan Plateau accumulated a net gain of 70.5 km3, which is dominated by the net gain of lake water storage (ca. 63.3 km3). The interannual TWS variation is found to be associated mainly with precipitation. In particular, extreme conditions such as the 2015/16 El Niño, had a profound negative impact on the TWS. The findings in this study shed new light on the response of Tibetan lakes to recent decadal environmental changes.

Monitoring the variation of rivers and lakes is of great importance. Satellite radar altimetry is a promising technology to do this on a regional to global scale. Satellite radar altimetry data has been used successfully to observe water levels in lakes and (large) rivers, and has also been combined with hydrologic/hydrodynamic models. Except CryoSat-2, all radar altimetry missions have been operated in conventional low resolution mode with a short repeat orbit (35 days or less). CryoSat-2, carrying a Synthetic Aperture Radar (SAR) altimeter, has a 369-day repeat and a drifting ground track pattern and provides new opportunities for hydrologic research. The narrow inter-track distance (7.5 km at the equator) makes it possible to monitor many lakes and rivers and SAR mode provides a finer along-track resolution, higher return power and speckle reduction through multi-looks. However, CryoSat-2 challenges conventional ways of dealing with satellite inland water altimetry data because virtual station time series cannot be directly derived for rivers. We review the CryoSat-2 mission characteristics, data products, and its use and perspectives for inland water applications. We discuss all the important steps in the workflow for hydrologic analysis with CryoSat-2, and conclude with a discussion of promising future research directions.

Surface water bodies (lakes, reservoirs and rivers) are key components of the water cycle and are important water sources. Water level and storage vary greatly under the impacts of climate change and human activities. A national-scale surface water monitoring dataset for China is not available. The spatio-temporal pattern of surface water dynamics is poorly known due to insufficient in situ monitoring capabilities and restricted access to monitoring data. In comparison with other satellites, the 369 day repeat orbit enables Cryosat-2 to monitor smaller water bodies than other satellites and the SIRAL sensor has higher precise than conventional altimeters. We investigated water level variations for large lakes, reservoirs and rivers during the period of 2010 - 2015 using Cryosat-2 altimetry data. Water storage changes for 759 water bodies were estimated, and the contribution of surface water storage (SWS) changes to terrestrial water storage (TWS) was evaluated in combination with results from the Gravity Recovery and Climate Experiment (GRACE). Moreover, water level dynamics in the Yangtze and Yellow Rivers were mapped. Results show that 1) surface water levels change significantly at regional scale, i.e. declining in Junggar Basin, Huai River Basin and Hubei Province while rising in North Tibetan Plateau and Songnen Plain; 2) SWS change affects TWS variation greatly, especially in Tibetan Plateau ; 3) TWS in Songhua River basin has been fluctuating strongly over the past decade and the North China Plain maintained a consistently decreasing trend in TWS (- 20 mm/yr); 4) Change observed in Songnen Plain is also seen from SongLiao Water Resources Bulletin.

The spatiotemporal changes in 21 indices of extreme temperature and precipitation for the Mongolian Plateau from 1951 to 2012 were investigated on the basis of daily temperature and precipitation data from 70 meteorological stations. Changes in catastrophic events, such as droughts, floods, and snowstorms, were also investigated for the same period. The correlations between catastrophic events and the extreme indices were examined. The results show that the Mongolian Plateau experienced an asymmetric warming trend. Both the cold extremes and warm extremes showed greater warming at night than in the daytime. The spatial changes in significant trends showed a good homogeneity and consistency in Inner Mongolia. Changes in the precipitation extremes were not as obvious as those in the temperature extremes. The spatial distributions in changes of precipitation extremes were complex. Adecreasing trend was shown for total precipitation from west to east as based on the spatial distribution of decadal trends. Drought was the most serious extreme disaster, and prolonged drought for longer than 3 yr occurred about every 7-11 yr. An increasing trend in the disaster area was apparent for flood events from 1951 to 2012. A decreasing trend was observed for the maximum depth of snowfall from 1951 to 2012, with a decreased average maximum depth of 10 mm from the 1990s.