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Terrestrial Hydrology Using GRACE and GRACE-FO

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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 (1 May 2021) | Viewed by 25340

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Special Issue Editor

Prof. Ki-Weon Seo

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Department of Earth Science Education, College of Education, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
Interests: satellite geodesy; polar motion; terrestrial water storage change; sea-level rise

Special Issue Information

Dear Colleagues,

The Gravity Recovery and Climate Experiment (GRACE) satellite, launched on March 17, 2002, observed global gravity fields from April 2002 to June 2017. Fifteen years of GRACE measurements have provided unprecedented insights to global mass redistribution that are fundamental to understanding dynamic Earth systems including solid Earth, atmosphere, cryosphere, and hydrosphere. Contributions from GRACE are particularly important to hydrology because total water storage (TWS) had not been monitored globally before GRACE: There is no alternative remote sensing to monitor groundwater and deeper layer soil moisture. Using GRACE data, TWS anomalies from regional to global scale have been revealed, and components of hydrological cycles such as groundwater storage, river discharge, and evapotranspiration have been estimated. To continue GRACE observation, GRACE Follow-On (GRACE FO) was launched on May 22, 2018. GRACE FO global gravity fields have been available since June 2018. With GRACE and GRACE FO, multi-decadal global gravity variations will be understood, and this is a significant opportunity to understand long-term changes of hydrological cycles driven by climate warming or anthropogenic effect.

This Special Issue solicits GRACE and GRACE FO contributions to terrestrial hydrology. We welcome contributions using GRACE to examine abrupt or long-term hydrological changes during the past 15 years. Gravity solutions from GRACE FO will include different noise and north–south stripe errors, and thus new data processing strategies to recover TWS from GRACE FO are also invited. We particularly solicit integrated studies using both GRACE and GRACE FO to examine terrestrial hydrology beyond the past 15 years.

Prof. Ki-Weon Seo
Guest Editor

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Keywords

GRACE
GRACE-FO
terrestrial hydrology
hydrological cycle
climate change
anthropogenic effect

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Published Papers (7 papers)

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12 pages, 2150 KiB

Open AccessCommunication

GRACE Satellites Enable Long-Lead Forecasts of Mountain Contributions to Streamflow in the Low-Flow Season

by Xingcai Liu, Qiuhong Tang, Seyed-Mohammad Hosseini-Moghari, Xiaogang Shi, Min-Hui Lo and Bridget Scanlon

Remote Sens. 2021, 13(10), 1993; https://doi.org/10.3390/rs13101993 - 19 May 2021

Cited by 2 | Viewed by 2706

Abstract

Terrestrial water storage (TWS) in high mountain areas contributes large runoff volumes to nearby lowlands during the low-flow season when streamflow is critical to downstream water supplies. The potential for TWS from GRACE (Gravity Recovery and Climate Experiment) satellites to provide long-lead streamflow forecasting in adjacent lowlands during the low-flow season was assessed using the upper Yellow River as a case study. Two linear models were trained for forecasting monthly streamflow with and without TWS anomaly (TWSA) from 2002 to 2016. Results show that the model based on streamflow and TWSA is superior to the model based on streamflow alone at up to a five-month lead-time. The inclusion of TWSA reduced errors in streamflow forecasts by 25% to 50%, with 3–5-month lead-times, which represents the role of terrestrial hydrologic memory in streamflow changes during the low-flow season. This study underscores the high potential of streamflow forecasting using GRACE data with long lead-times that should improve water management in mountainous water towers and downstream areas. Full article

(This article belongs to the Special Issue Terrestrial Hydrology Using GRACE and GRACE-FO)

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19 pages, 2747 KiB

Open AccessArticle

Monitoring Terrestrial Water Storage Changes with the Tongji-Grace2018 Model in the Nine Major River Basins of the Chinese Mainland

by Zhiwei Chen, Xingfu Zhang and Jianhua Chen

Remote Sens. 2021, 13(9), 1851; https://doi.org/10.3390/rs13091851 - 10 May 2021

Cited by 14 | Viewed by 3167

Abstract

Data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission can be used to monitor changes in terrestrial water storage (TWS). In this study, we exploit the TWS observations from a new temporal gravity field model, Tongji-Grace2018, which was developed using an optimized short-arc approach at Tongji University. We analyzed the changes in the TWS and groundwater storage (GWS) in each of the nine major river basins of the Chinese mainland from April 2002 to August 2016, using Tongji-Grace2018, the Global Land Data Assimilation System (GLDAS) hydrological model, in situ observations, and additional auxiliary data (such as precipitation and temperature). Our results indicate that the TWS of the Songliao, Yangtze, Pearl, and Southeastern River Basins are all increasing, with the most drastic TWS growth occurring in the Southeastern River Basin. The TWS of the Yellow, Haihe, Huaihe, and Southwestern River Basins are all decreasing, with the most drastic TWS loss occurring in the Haihe River Basin. The Continental River Basin TWS has remained largely unchanged over time. With the exception of the Songliao and Pearl River Basins, the GWS results produced by the Tongji-Grace2018 model are consistent with the in situ observations of these basins. The correlation coefficients for the Tongji-Grace2018 model results and the in situ observations for the Yellow, Huaihe, Yangtze, Southwestern, and Continental River Basins are higher than 0.710. Overall, the GWS results for the Songliao, Yellow, Haihe, Huaihe, Southwestern, and Continental River Basins all exhibit a downward trend, with the most severe groundwater loss occurring in the Haihe and Huaihe River Basins. However, the Yangtze and Southeastern River Basins both have upward-trending modeled and measured GWS values. This study demonstrates the effectiveness of the Tongji-Grace2018 model for the reliable estimation of TWS and GWS changes on the Chinese mainland, and may contribute to the management of available water resources. Full article

(This article belongs to the Special Issue Terrestrial Hydrology Using GRACE and GRACE-FO)

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22 pages, 19379 KiB

Open AccessArticle

Spatio-Temporal Patterns of Mass Changes in Himalayan Glaciated Region from EOF Analyses of GRACE Data

by Harika Munagapati and Virendra M. Tiwari

Remote Sens. 2021, 13(2), 265; https://doi.org/10.3390/rs13020265 - 14 Jan 2021

Cited by 7 | Viewed by 3833

Abstract

The nature of hydrological seasonality over the Himalayan Glaciated Region (HGR) is complex due to varied precipitation patterns. The present study attempts to exemplify the spatio-temporal variation of hydrological mass over the HGR using time-variable gravity from the Gravity Recovery and Climate Experiment (GRACE) satellite for the period of 2002–2016 on seasonal and interannual timescales. The mass signal derived from GRACE data is decomposed using empirical orthogonal functions (EOFs), allowing us to identify the three broad divisions of HGR, i.e., western, central, and eastern, based on the seasonal mass gain or loss that corresponds to prevailing climatic changes. Further, causative relationships between climatic variables and the EOF decomposed signals are explored using the Granger causality algorithm. It appears that a causal relationship exists between total precipitation and total water storage from GRACE. EOF modes also indicate certain regional anomalies such as the Karakoram mass gain, which represents ongoing snow accumulation. Our causality result suggests that the excessive snowfall in 2005–2008 has initiated this mass gain. However, as our results indicate, despite the dampening of snowfall rates after 2008, mass has been steadily increasing in the Karakorum, which is attributed to the flattening of the temperature anomaly curve and subsequent lower melting after 2008. Full article

(This article belongs to the Special Issue Terrestrial Hydrology Using GRACE and GRACE-FO)

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22 pages, 15681 KiB

Open AccessArticle

The Use of National CORS Networks for Determining Temporal Mass Variations within the Earth’s System and for Improving GRACE/GRACE-FO Solutions

by Walyeldeen Godah, Jagat Dwipendra Ray, Malgorzata Szelachowska and Jan Krynski

Remote Sens. 2020, 12(20), 3359; https://doi.org/10.3390/rs12203359 - 15 Oct 2020

Cited by 6 | Viewed by 3093

Abstract

Temporal mass variations within the Earth’s system can be detected on a regional/global scale using GRACE (Gravity Recovery and Climate Experiment) and GRACE Follow-On (GRACE-FO) satellite missions’ data, while GNSS (Global Navigation Satellite System) data can be used to detect those variations on a local scale. The aim of this study is to investigate the usefulness of national GNSS CORS (Continuously Operating Reference Stations) networks for the determination of those temporal mass variations and for improving GRACE/GRACE-FO solutions. The area of Poland was chosen as a study area. Temporal variations of equivalent water thickness ΔEWT and vertical deformations of the Earth’s surface Δh were determined at the sites of the ASG-EUPOS (Active Geodetic Network of the European Position Determination System) CORS network using GRACE/GRACE-FO-based GGMs and GNSS data. Moreover, combined solutions of ΔEWT were developed by combining ΔEWT obtained from GNSS data with the corresponding ones determined from GRACE satellite mission data. Strong correlations (correlation coefficients ranging from 0.6 to 0.9) between detrended Δh determined from GRACE/GRACE-FO satellite mission data and the corresponding ones from GNSS data were observed at 93% of the GNSS stations investigated. Furthermore, for the determination of temporal mass variations, GNSS data from CORS network stations provide valuable information complementary to GRACE satellite mission data. Full article

(This article belongs to the Special Issue Terrestrial Hydrology Using GRACE and GRACE-FO)

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21 pages, 5757 KiB

Open AccessArticle

Surface Mass Variations from GPS and GRACE/GFO: A Case Study in Southwest China

by Bo Zhong, Xianpao Li, Jianli Chen, Qiong Li and Tao Liu

Remote Sens. 2020, 12(11), 1835; https://doi.org/10.3390/rs12111835 - 5 Jun 2020

Cited by 28 | Viewed by 3586

Abstract

Surface mass variations inferred from the Global Positioning System (GPS), and observed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO) complement each other in terms of spatial and temporal coverage. This paper presents an analysis of regional surface mass variations inverted from GPS vertical displacements under different density distributions of GPS stations, and compares the GPS-derived mass variations with GRACE/GFO inversion results in spatial and temporal domains. To this end, GPS vertical displacement data from a total of 85 permanent GPS stations of the Crustal Movement Observation Network of China (CMONOC), the latest GRACE/GFO RL06 spherical harmonic (SH) solutions and GRACE RL06 mascon solutions are used to investigate surface mass variations in four regions or basins, including the Yunnan Province (YNP), Min River Basin (MRB), Jialing River Basin (JLRB), and Wu River Basin (WRB) in Southwest China. Our results showed that the spatial distributions and seasonal characteristics of GPS-derived mass change time series agree well with those from GRACE/GFO observations, especially in regions with relatively dense distributions of GPS stations (e.g., in the YNP and MRB), but there are still obvious discrepancies between the GPS and GRACE/GFO results. Scale factor methods (both basin-scaled and pixel-scaled) were employed to reduce the amplitude discrepancies between GPS and GRACE/GFO results. The results also showed that the one-year gap between the GRACE and GFO missions can be bridged by scaled GPS-derived mass change time series in the four studied regions, especially in the YNP and MRB regions (with relatively dense distributions of GPS stations). Full article

(This article belongs to the Special Issue Terrestrial Hydrology Using GRACE and GRACE-FO)

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20 pages, 5017 KiB

Open AccessArticle

Spatial Downscaling of GRACE TWSA Data to Identify Spatiotemporal Groundwater Level Trends in the Upper Floridan Aquifer, Georgia, USA

by Adam M. Milewski, Matthew B. Thomas, Wondwosen M. Seyoum and Todd C. Rasmussen

Remote Sens. 2019, 11(23), 2756; https://doi.org/10.3390/rs11232756 - 23 Nov 2019

Cited by 42 | Viewed by 4551

Abstract

Accurate assessments of groundwater resources in major aquifers across the globe are crucial for sustainable management of freshwater reservoirs. Observations from the Gravity Recovery and Climate Experiment (GRACE) satellite have become invaluable as a means to identify regions groundwater change. While there is a large body of research that focuses on downscaling coarse (1°) GRACE products, few studies have attempted to spatially downscale GRACE to produce fine resolution (5 km) maps that are more useful to resource managers. This study trained a boosted regression tree model to statistically downscale GRACE total water storage anomaly to monthly 5 km groundwater level anomaly maps in the karstic upper Floridan aquifer (UFA) using multiple hydrologic datasets. Evaluation of spatial predictions with existing groundwater wells indicated satisfactory performance (R = 0.79, NSE = 0.61). Results demonstrate that groundwater levels were stable between 2002–2016 but varied seasonally. The data also highlights areas where groundwater pumping is exacerbating UFA water-level declines. While results demonstrate the applicability of machine learning based methods for spatial downscaling of GRACE data, future studies should account for preferential flowpaths (i.e., conduits, lineaments) in karstic systems. Full article

(This article belongs to the Special Issue Terrestrial Hydrology Using GRACE and GRACE-FO)

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13 pages, 2756 KiB

Open AccessLetter

Constrained Linear Deconvolution of GRACE Anomalies to Correct Spatial Leakage

by Ki-Weon Seo, Seokhoon Oh, Jooyoung Eom, Jianli Chen and Clark R. Wilson

Remote Sens. 2020, 12(11), 1798; https://doi.org/10.3390/rs12111798 - 2 Jun 2020

Cited by 8 | Viewed by 3007

Abstract

Time-varying gravity observed by the Gravity Recovery and Climate Experiment (GRACE) satellites measures surface water and ice mass redistribution driven by weather and climate forcing and has emerged as one of the most important data types in measuring changes in Earth’s climate. However, spatial leakage of GRACE signals, especially in coastal areas, has been a recognized limitation in quantitatively assessing mass change. It is evident that larger terrestrial signals in coastal regions spread into the oceans and vice versa and various remedies have been developed to address this problem. An especially successful one has been Forward Modeling but it requires knowledge of geographical locations of mass change to be fully effective. In this study, we develop a new method to suppress leakage effects using a linear least squares operator applied to GRACE spherical harmonic data. The method is effectively a constrained deconvolution of smoothing inherent in GRACE data. It assumes that oceanic mass changes near the coast are negligible compared to terrestrial changes, with additional spatial regularization constraints. Some calibration of constraint weighting is required. We apply the method to estimate surface mass loads over Australia using both synthetic and real GRACE data. Leakage into the oceans is effectively suppressed and when compared with mascon solutions there is better performance over interior basins. Full article

(This article belongs to the Special Issue Terrestrial Hydrology Using GRACE and GRACE-FO)

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