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GRACE Facing the Challenge of Extreme Spatial and Temporal Scales

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (31 December 2018) | Viewed by 56481

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Dr. Laurent Longuevergne

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Geosciences Rennes, CNRS, Campus Beaulieu, 35042 Rennes, CEDEX, France
Interests: hydrogeodesy; hydrology; hydrogeology; heterogeneity; data fusion

Prof. Dr. Annette Eicker

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Guest Editor

HafenCity University Hamburg
Interests: satellite gravity missions; hydrology; climate research; data assimilation
Special Issues, Collections and Topics in MDPI journals

Dr. Wei Feng

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Institute of Geodesy and Geophysics, Chinese Academy of Sciences, 340 XuDong Rd, Wuhan 430077, Hubei, China
Interests: satellite gravity; satellite altimetry; hydrology; oceanography

Special Issue Information

Dear Colleagues,

Launched in 2002, the GRACE gravity satellite mission has revolutionized the way large mass changes can be detected on Earth. By monitoring the temporal variations of the Earth's gravity field with an unprecedented temporal and spatial resolution, GRACE has provided compelling scientific results on mass redistribution processes in the atmosphere, ocean, hydrosphere, cryosphere and lithosphere. As GRACE is the first satellite of its generation, data quality has significantly improved over the last 15 years, with a deeper understanding of the satellite dynamics and range rate data information content. However, there is still great potential to further exploit the mission’s scientific wealth by pushing the limits of the spatial and temporal scales observable by GRACE in order to resolve future scientific and societal challenges, e.g., identifying hot spots (glacier flow, aquifer storage changes) and hot moments (extreme events) and the investigation of the impact of climate variability and climate change. Wide potential to improve GRACE data is still possible. As example, the link between GRACE space-time integration (monthly, 200,000 km²) and its actual achievable resolution is still an open question. Further, the accurate estimation of low degree coefficients would drive to better constrain seasonal to long-term mass changes at global scale.

In this special issue, we invite geodesists and researchers in Earth Sciences to think together how such extreme—small and large—spatial and temporal scales could be further understood and captured, either by evolving GRACE data analysis techniques or by combining GRACE with other observation tools (whether geodetic: GNSS, InSAR, ground gravity—or alternate information, such as remote sensing or surface observations), models (land surface models, hydrological models) and/or mathematical methods (down and up-scaling, etc.). The objective is a better understanding of the potential and current limitations of gravity-based mission, such as GRACE, and how the design of future satellite missions could bring critical new insights into fluid and solid mass transport at the surface of the Earth.

Dr. Laurent Longuevergne
Dr. Annette Eicker
Dr. Wei Feng
Guest Editors

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Keywords

GRACE and GRACE-Follow on
GNSS–InSAR
Ground gravity
Extreme events
Climate change and climate variability
Regional scale
Water resources
Glacier mass changes
Atmosphere
Oceanic circulation

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Published Papers (10 papers)

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Research

22 pages, 4390 KiB

Open AccessArticle

Gravity Recovery and Climate Experiment (GRACE) Storage Change Characteristics (2003–2016) over Major Surface Basins and Principal Aquifers in the Conterminous United States

by Naga Manohar Velpuri, Gabriel B. Senay, Jessica M. Driscoll, Samuel Saxe, Lauren Hay, William Farmer and Julie Kiang

Remote Sens. 2019, 11(8), 936; https://doi.org/10.3390/rs11080936 - 18 Apr 2019

Cited by 11 | Viewed by 4609

Abstract

In this research, we characterized the changes in the Gravity Recovery and Climate Experiment (GRACE) monthly total water storage anomaly (TWSA) in 18 surface basins and 12 principal aquifers in the conterminous United States during 2003–2016. Regions with high variability in storage were identified. Ten basins and four aquifers showed significant changes in storage. Eight surface basins and eight aquifers were found to show decadal stability in storage. A pixel-based analysis of storage showed that the New England basin and North Atlantic Coastal Plain aquifer showed the largest area under positive storage change. By contrast, the Lower Colorado and California basins showed the largest area under negative change. This study found that historically wetter regions (with more storage) are becoming wetter, and drier regions (with less storage) are becoming drier. Fourier analysis of the GRACE data showed that while all basins exhibited prominent annual periodicities, significant sub-annual and multi-annual cycles also exist in some basins. The storage turnover period was estimated to range between 6 and 12 months. The primary explanatory variable (PEV) of TWSA was identified for each region. This study provides new insights on several aspects of basin or aquifer storage that are important for understanding basin and aquifer hydrology. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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17 pages, 10119 KiB

Open AccessArticle

Separation and Recovery of Geophysical Signals Based on the Kalman Filter with GRACE Gravity Data

by Xiaolong Wang, Zhicai Luo, Bo Zhong, Yihao Wu, Zhengkai Huang, Hao Zhou and Qiong Li

Remote Sens. 2019, 11(4), 393; https://doi.org/10.3390/rs11040393 - 15 Feb 2019

Cited by 10 | Viewed by 3779

Abstract

Monthly gravitational field solutions as spherical harmonic coefficients produced by the GRACE satellite mission require post-processing to reduce the effects of shortwave-length noises and north–south stripe errors. However, the spatial smoothing and de-striping filter commonly used in the post-processing step will either reduce spatial resolution or remove short-wavelength features of geophysical signals, mainly at high latitudes. Here, by using prior covariance information that reflects the spatial and temporal features of the geophysical signals and the correlated errors derived from the synthetic model, together with the covariance matrix of the formal errors for the monthly gravity spherical harmonic coefficients, we apply the Kalman filter to separate the geophysical signal from GRACE Level-2 data and simultaneously to estimate the correlated errors. By increasing the number of observations, the iterative process is applied to update the state vector and covariance in the Kalman filter because the prior information is not accurate. Due to the inevitable truncation error, multiple gridded-gain factors method considering different temporal frequencies has been developed to recover the geophysical signal. The results show that the Kalman filter can reduce the high-frequency noises and correlated errors remarkably. When compared with the commonly used filter, no spatial filter (such as Gaussian filter) is used in the Kalman filter. Therefore, the estimated signal preserves its natural resolution, and more detailed information is retained. It shows good consistency when compared with mascon solutions in both secular trend and annual amplitude. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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22 pages, 2898 KiB

Open AccessArticle

Determining Regional-Scale Groundwater Recharge with GRACE and GLDAS

by Qifan Wu, Bingcheng Si, Hailong He and Pute Wu

Remote Sens. 2019, 11(2), 154; https://doi.org/10.3390/rs11020154 - 15 Jan 2019

Cited by 67 | Viewed by 7308

Abstract

Groundwater recharge (GR) is a key component of regional and global water cycles and is a critical flux for water resource management. However, recharge estimates are difficult to obtain at regional scales due to the lack of an accurate measurement method. Here, we estimate GR using Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data. The regional-scale GR rate is calculated based on the groundwater storage fluctuation, which is, in turn, calculated from the difference between GRACE and root zone soil water storage from GLDAS data. We estimated GR in the Ordos Basin of the Chinese Loess Plateau from 2002 to 2012. There was no obvious long-term trend in GR, but the annual recharge varies greatly from 30.8 to 66.5 mm year⁻¹, 42% of which can be explained by the variability in the annual precipitation. The average GR rate over the 11-year period from GRACE data was 48.3 mm year⁻¹, which did not differ significantly from the long-term average recharge estimate of 39.9 mm year⁻¹ from the environmental tracer methods and one-dimensional models. Moreover, the standard deviation of the 11-year average GR is 16.0 mm year⁻¹, with a coefficient of variation (CV) of 33.1%, which is, in most cases, comparable to or smaller than estimates from other GR methods. The improved method could provide critically needed, regional-scale GR estimates for groundwater management and may eventually lead to a sustainable use of groundwater resources. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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25 pages, 33837 KiB

Open AccessArticle

Recent Surface Deformation in the Tianjin Area Revealed by Sentinel-1A Data

by Tengxu Zhang, Wen-Bin Shen, Wenhao Wu, Bao Zhang and Yuanjin Pan

Remote Sens. 2019, 11(2), 130; https://doi.org/10.3390/rs11020130 - 11 Jan 2019

Cited by 33 | Viewed by 5552

Abstract

In this study, we employed multitemporal InSAR (Interferometric Synthetic Aperture Radar) (MT-InSAR) to detect spatial and temporal ground deformations over the whole Tianjin region in the North China Plain area. Twenty-five ascending Sentinel-1A terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR) scenes covering this area, acquired from 9 January 2016 to 8 June 2017, were processed using InSAR time series analysis. The deformation results derived from Sentinel-1A MT-InSAR were validated with continuously operating reference stations (CORS) at four sites and four stations of the Crustal Movement Observation Network of China (CMONOC). The overall results show good agreement, demonstrating the suitability of applying Doris with Sentinel-1A data to high-resolution monitoring of surface deformation. Significant deformation variations have been observed in different parts of Tianjin. These gradually increased from the central part of the metropolitan area to the nearby suburbs. The deformation rate of the main urban area is well-balanced and it is also relatively linear, with uplifting rates ranging from 0 to 20 mm/yr. However, due to the diversity of the geological conditions and anthropogenic activities, remarkable signs of subsidence were found in several parts of Tianjin. In particular, the south-western part of Wuqing District and western part of Beichen District showed subsidence rates of up to −136 mm/yr. We also found that, in addition to groundwater over-exploitation and lithological characteristics, additional factors also influence ground subsidence, including dynamic loads (e.g., railways), static loads (e.g., urban construction), and groundwater recharging. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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19 pages, 16427 KiB

Open AccessArticle

The Challenge of Spatial Resolutions for GRACE-Based Estimates Volume Changes of Larger Man-Made Lake: The Case of China’s Three Gorges Reservoir in the Yangtze River

by Linsong Wang, Mikhail K. Kaban, Maik Thomas, Chao Chen and Xian Ma

Remote Sens. 2019, 11(1), 99; https://doi.org/10.3390/rs11010099 - 8 Jan 2019

Cited by 19 | Viewed by 5792

Abstract

The Three Gorges Reservoir (TGR) in China, with the largest dam in the world, stores a large volume of water and may influence the Earth’s gravity field on sub-seasonal to interannual timescales. Significant changes of the total water storage (TWS) might be detectable by satellite-based data provided by the Gravity Recovery and Climate Experiment (GRACE) mission. To detect these store water changes, effects of other factors are to be removed first from these data due to band-limited representation of near-surface mass changes from GRACE. Here, we evaluated three current popular land surface models (LSMs) basing on in situ measurements and found that the WaterGAP Global Hydrology Model (WGHM) demonstrates higher correlation than other analyzed models with the in-situ rainfall measurement. Then we used the WGHM outputs to remove climate-induced TWS changes, such as surface water storage, soil, canopy, snow, and groundwater storage. The residual results (GRACE minus WGHM) indicated a strong trend (3.85 ± 2 km³/yr) that is significantly higher than the TGR analysis and hindcast experiments (2.29 ± 1 km³/yr) based on in-situ water level measurements. We also estimated the seepage response to the TGR filling, contributions from other anthropogenic dams, and used in-situ gravity and GPS observations to evaluate dominant factors responsible for the GRACE-based overestimate of the TGR volume change. We found that the modeled seepage variability through coarse-grained materials explained most of the difference between the GRACE based estimate of TGR volume changes and in situ measurements, but the agreement with in-situ gravity observations is considerably lower. In contrast, the leakage contribution from 13 adjacent reservoirs explained ~74% of the TGR volume change derived from GRACE and WGHM. Our results demonstrate that GRACE-based overestimate TGR mass change mainly from the contribution of surrounding artificial reservoirs and underestimated TWS variations in WGHM simulations due to the large uncertainty of WGHM in groundwater component. In additional, this study also indicates that reservoir or lake volume changes can be reliably derived from GRACE data when they are used in combination with relevant complementary observations. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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20 pages, 3972 KiB

Open AccessArticle

Validation of the EGSIEM GRACE Gravity Fields Using GNSS Coordinate Timeseries and In-Situ Ocean Bottom Pressure Records

by Qiang Chen, Lea Poropat, Liangjing Zhang, Henryk Dobslaw, Matthias Weigelt and Tonie Van Dam

Remote Sens. 2018, 10(12), 1976; https://doi.org/10.3390/rs10121976 - 7 Dec 2018

Cited by 7 | Viewed by 4007

Abstract

Over the 15 years of the Gravity Recovery and Climate Experiment (GRACE) mission, various data processing approaches were developed to derive time-series of global gravity fields based on sensor observations acquired from the two spacecrafts. In this paper, we compare GRACE-based mass anomalies provided by various processing groups against Global Navigation Satellite System (GNSS) station coordinate time-series and in-situ observations of ocean bottom pressure. In addition to the conventional GRACE-based global geopotential models from the main processing centers, we focus particularly on combined gravity field solutions generated within the Horizon2020 project European Gravity Service for Improved Emergency Management (EGSIEM). Although two validation techniques are fully independent from each other, it is demonstrated that they confirm each other to a large extent. Through the validation, we show that the EGSIEM combined long-term monthly solutions are comparable to CSR RL05 and ITSG2016, and better than the other three considered GRACE monthly solutions AIUB RL02, GFZ RL05a, and JPL RL05.1. Depending on the GNSS products, up to 25.6% mean Weighted Root-Mean-Square (WRMS) reduction is obtained when comparing GRACE to the ITRF2014 residuals over 236 GNSS stations. In addition, we also observe remarkable agreement at the annual period between GNSS and GRACE with up to 73% median WRMS reduction when comparing GRACE to the 312 EGSIEM-reprocessed GNSS time series. While the correspondence between GRACE and ocean bottom pressure data is overall much smaller due to lower signal to noise ratio over the oceans than over the continents, up to 50% agreement is found between them in some regions. The results fully confirm the conclusions found using GNSS. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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21 pages, 6359 KiB

Open AccessArticle

Drought and Flood Monitoring of the Liao River Basin in Northeast China Using Extended GRACE Data

by Xuhui Chen, Jinbao Jiang and Hui Li

Remote Sens. 2018, 10(8), 1168; https://doi.org/10.3390/rs10081168 - 24 Jul 2018

Cited by 52 | Viewed by 7282

Abstract

In recent years, alternating periods of floods and droughts, possibly related to climate change and/or human activity, have occurred in the Liao River Basin of China. To monitor and gain a deep understanding of the frequency and severity of the hydro-meteorological extreme events in the Liao River Basin in the past 30 years, the total storage deficit index (TSDI) is established by the Gravity Recovery and Climate Experiment (GRACE)-based terrestrial water storage anomalies (TWSAs) and the general regression neural network (GRNN)-predicted TWSA. Results indicate that the GRNN model trained with GRACE-based TWSA, model-simulated soil moisture, and precipitation observations was optimal, and the correlation coefficient and the root mean square error (RMSE) of the predicted TWSA and GRACE TWSA for the testing period equal 0.90 and 18 mm, respectively. The drought and flood conditions monitored by the TSDI were consistent with those of previous studies and records. The extreme climate events could indirectly reflect the status of the regional hydrological cycle. By monitoring the extreme climate events in the study area with TSDI, which was based on the TWSA of GRACE and GRNN, the decision of water resource management in the Liao River Basin could be made reasonably. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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24 pages, 15643 KiB

Open AccessArticle

Investigation of Short-Term Evolution of Soil Characteristics over the Lake Chad Basin Using GRACE Data

by Teodolina Lopez, Guillaume Ramillien, Raphaël Antoine, José Darrozes, Yu-Jun Cui and Yann Kerr

Remote Sens. 2018, 10(6), 924; https://doi.org/10.3390/rs10060924 - 12 Jun 2018

Cited by 2 | Viewed by 4033

Abstract

In the Sahelian region, the West African Monsoon (WAM) is an important phenomenon for land water storage evolution, as demonstrated by The Gravity Recovery and Climate Experiment (GRACE) estimations. The Monsoon leads to an annual increase of the water mass. However, GRACE data also displays the existence of a semi-annual cycle whose its origin is still uncertain. This cycle is characterized by a gain of water mass at the beginning of the dry season. In this study, 10-days GRACE data are used to understand the characteristics of this semi-annual cycle. Investigations of the rainfall events, rivers discharge peaks, and the Lake Chad water level variations suggest that they are not at the origin of this cycle. However, MODIS evapotranspiration data display an increase each 6 months, during the rainy season, and at the same time as the semi-annual cycle estimated by GRACE. This increase occurs in regions where the amount of clays at the surface exceeds 30%. The link between both signals and the proportion of clays at the surface leads us to the conclusion that the seasonal variation of the vertical permeability of clays controls the amount of water present in the unsaturated zone. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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21 pages, 8042 KiB

Open AccessArticle

Identifying Flood Events over the Poyang Lake Basin Using Multiple Satellite Remote Sensing Observations, Hydrological Models and In Situ Data

by Hao Zhou, Zhicai Luo, Natthachet Tangdamrongsub, Zebing Zhou, Lijie He, Chuang Xu, Qiong Li and Yunlong Wu

Remote Sens. 2018, 10(5), 713; https://doi.org/10.3390/rs10050713 - 5 May 2018

Cited by 22 | Viewed by 5215

Abstract

The Poyang Lake, the largest freshwater lake in China, is famous for its ecological and economic importance as well as frequent flood characteristics. In this study, multiple satellite remote sensing observations (e.g., GRACE, MODIS, Altimetry, and TRMM), hydrological models, and in situ data are used to characterize the flood phenomena over the Poyang Lake basin between 2003 and 2016. To improve the accuracy of the terrestrial water storage (TWS) estimates over the Poyang Lake basin, a modified forward-modeling method is introduced in the GRACE processing. The method is evaluated using the contaminated noise onboard observations for the first time. The results in both spectral and spatial domains infer a good performance of the method on the suppression of high-frequency noise while reducing the signal loss. After applying forward-modeling method, the TWS derived from the GRACE spherical harmonic coefficients presents a comparable performance with the solution derived from the newly released CSR Release05 mascon product over the Poyang Lake basin. The flood events in 2010 and 2016 are identified from the positive anomalies in non-seasonal TWSs derived by GRACE and hydrological models. The flood signatures also coincide with the largest inundated areas estimated from MODIS data, and the observed areas in 2010 and 2016 are 3370.3 km² (30% higher than the long-term mean) and 3445.0 km² (33% higher), respectively. The water levels in the Hukou station exceed the warning water level for 25 days in 2010 and 28 days in 2016. These continuous warning-exceeded water levels also imply the severe flood events, which are primarily driven by the local plenteous precipitation in the rainy season (1528 mm in 2010, 1522 mm in 2016). Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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18 pages, 2828 KiB

Open AccessArticle

Monitoring Groundwater Storage Changes in the Loess Plateau Using GRACE Satellite Gravity Data, Hydrological Models and Coal Mining Data

by Xiaowei Xie, Caijun Xu, Yangmao Wen and Wei Li

Remote Sens. 2018, 10(4), 605; https://doi.org/10.3390/rs10040605 - 13 Apr 2018

Cited by 54 | Viewed by 7204

Abstract

Monitoring the groundwater storage (GWS) changes is crucial to the rational utilization of groundwater and to ecological restoration in the Loess Plateau of China, which is one of the regions with the most extreme ecological environmental damage in the world. In this region, the mass loss caused by coal mining can reach the level of billions of tons per year. For this reason, in this work, in addition to Gravity Recovery and Climate Experiment (GRACE) satellite gravity data and hydrological models, coal mining data were also used to monitor GWS variation in the Loess Plateau during the period of 2005–2014. The GWS changes results from different GRACE solutions, that is, the spherical harmonics (SH) solutions, mascon solutions, and Slepian solutions (which are the Slepian localization of SH solutions), were compared with in situ GWS changes, obtained from 136 groundwater observation wells, and the aim was to acquire the most robust GWS changes. The results showed that the GWS changes from mascon solutions (mascon-GWS) match best with in situ GWS changes, showing the highest correlation coefficient, lowest root mean square error (RMSE) values and nearest annual trend. Therefore, the Mascon-GWS changes are used for the spatial-temporal analysis of GWS changes. Based on which, the groundwater depletion rate of the Loess Plateau was −0.65 ± 0.07 cm/year from 2005–2014, with a more severe consumption rate occurring in its eastern region, reaching about −1.5 cm/year, which is several times greater than those of the other regions. Furthermore, the precipitation and coal mining data were used for analyzing the causes of the groundwater depletion: the results showed that seasonal changes in groundwater storage are closely related to rainfall, but the groundwater consumption is mainly due to human activities; coal mining in particular plays a major role in the serious groundwater consumption in eastern region of the study area. Our results will help in groundwater resource management, ecological restoration, and policy planning for coal mining and economic development. Full article

(This article belongs to the Special Issue GRACE Facing the Challenge of Extreme Spatial and Temporal Scales)

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