Global analysis of approaches for deriving total water storage changes from GRACE satellites

Long, Di; Longuevergne, Laurent; Scanlon, Bridget R.

doi:10.1002/2014wr016853

Cited by 203 publications

(158 citation statements)

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“…The scaling factor for this region may vary when different LSMs or HMs are used. We compare the scaling factors for this region calculated by Landerer and Swenson [37], Long et al [35], and Long et al [36], respectively, and found that the factor scaling for Horqin Sandy Land derived from different HMs is also different, but the gap is relatively small. In this case, we just followed Landerer's work, in which the scaling factor is derived by least square fit between spatially averaged filtered and unfiltered modeled TWS anomaly (TWSA) time series from GLDAS-NOAH [37].…”

Section: Grace Datamentioning

confidence: 92%

“…Moreover, bias and leakage corrections are likely less accurate when reservoir storage is considered a major component of the water balance because GLDAS excludes reservoir storage [34]. On the other hand, scaling factors derived from different LSMs or HMs are similar over most humid, subhumid, and high-latitude regions, but can differ by up to 100% over arid and semiarid basins as well as areas with intensive irrigation [35]. Long et al [36] found that filtered GRACE TWS changes applied with PCR-GLOBWB scaling factors exhibit closer agreement with water budget estimates of TWS changes than those applied with scaling factors from other LSMs in the Yangtze River Basin.…”

Section: Grace Datamentioning

confidence: 99%

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Analysis of Water Resources in Horqin Sandy Land Using Multisource Data from 2003 to 2010

et al. 2016

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Over the past four decades, land use/land cover (LU/LC) change, coupled with persistent drought, has resulted in the decline of groundwater levels in Horqin Sandy Land. Accordingly, this study quantifies changes in LU/LC and groundwater storage (GWS). Furthermore, it investigates the effects of LU/LC changes on GWS. GWS changes are estimated using Gravity Recovery and Climate Experiment (GRACE) data and ground-based measurements obtained from July 2003 to December 2010. Soil moisture and snow water equivalent data derived from the Global Land Data Assimilation System (GLDAS) are used to isolate GWS changes from GRACE-derived terrestrial water storage changes. The result shows that the groundwater depletion rate in Horqin Sandy Land is 13.5˘1.9 mm¨year´1 in 2003-2010, which is consistent with the results of monitoring well stations. LU/LC changes are detected using bitemporal imageries (2003 and 2010) from Landsat Thematic Mapper through the post-classification comparison method. The result shows that LU/LC significantly changed during the aforementioned period. Bare soil and built-up land have increased by 76.6% and 82.2%, respectively, while cropland, vegetation, and water bodies have decreased by 14.1%, 74.5%, and 82.6%, respectively. The analysis of GWS and LU/LC changes shows that LU/LC changes and persistent drought are the main factors that affect groundwater resources.

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Section: Grace Datamentioning

confidence: 92%

Section: Grace Datamentioning

confidence: 99%

Analysis of Water Resources in Horqin Sandy Land Using Multisource Data from 2003 to 2010

et al. 2016

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“…To facilitate insight into the underlying processes, hydrological models are frequently used to separate the measured TWS into its different components such as groundwater, soil moisture, and snowpacks (Felfelani et al, 2017). However, as a consequence of uncertain model structure, forcing, and parametrization, model-based partitioning is ambiguous (Güntner, 2008) and may lead to diverging conclusions, especially on regional scale (Long et al, 2015;Schellekens et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…So far, only a few models used to assess hydrological processes on continental to global scales are constrained by observations, and if so, they are mainly calibrated against the observed discharge of large river basins (Long et al, 2015;Döll et al, 2015). Recently, several studies showed the benefits of additionally including GRACE TWS data in model calibration (Werth and Güntner, 2010;Xie et al, 2012;Chen et al, 2017) or by means of data assimilation Forman et al, 2012;Kumar et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Understanding terrestrial water storage variations in northern latitudes across scales

Trautmann

Koirala

Eicker

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual timescales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snowpacks, soil moisture, and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid-to high latitudes.To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological spatio-temporal patterns and was used to assess the relative contributions of solid (snowpack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales.Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across all spatial scales in the northern mid-to high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages at all spatial scales. The relative contribution of snow to inter-annual TWS variations, though, increases when the spatial domain over which the storages are averaged becomes larger. This is due to a stronger spatial coherence of snow dynamics that are mainly driven by temperature, as opposed to spatially more heterogeneous liquid water anomalies, that cancel out when averaged over a larger spatial domain. The findings first highlight the effectiveness of our model-data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale-dependent. In particular, they seem to be not merely driven by snow variability, but rather are determined by liquid water storages on interannual timescales. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short-and long-term variability of water resources.

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“…GRACE has also been used for comparisons, validation and calibration of hydrological models [28][29][30]. The ∆TWS from GRACE was compared with in-situ observations [31][32][33], altimetry observations [32,[34][35][36] and hydrological models [36][37][38].…”

Section: Grace-derived ∆Twsmentioning

confidence: 99%

Water Budget Analysis within the Surrounding of Prominent Lakes and Reservoirs from Multi-Sensor Earth Observation Data and Hydrological Models: Case Studies of the Aral Sea and Lake Mead

et al. 2016

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Abstract:The hydrological budget of a region is determined based on the horizontal and vertical water fluxes acting in both inward and outward directions. These integrated water fluxes vary, altering the total water storage and consequently the gravitational force of the region. The time-dependent gravitational field can be observed through the Gravity Recovery and Climate Experiment (GRACE) gravimetric satellite mission, provided that the mass variation is above the sensitivity of GRACE. This study evaluates mass changes in prominent reservoir regions through three independent approaches viz. fluxes, storages, and gravity, by combining remote sensing products, in-situ data and hydrological model outputs using WaterGAP Global Hydrological Model (WGHM) and Global Land Data Assimilation System (GLDAS). The results show that the dynamics revealed by the GRACE signal can be better explored by a hybrid method, which combines remote sensing-based reservoir volume estimates with hydrological model outputs, than by exclusive model-based storage estimates. For the given arid/semi-arid regions, GLDAS based storage estimations perform better than WGHM.

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Global analysis of approaches for deriving total water storage changes from GRACE satellites

Cited by 203 publications

References 50 publications

Analysis of Water Resources in Horqin Sandy Land Using Multisource Data from 2003 to 2010

Analysis of Water Resources in Horqin Sandy Land Using Multisource Data from 2003 to 2010

Understanding terrestrial water storage variations in northern latitudes across scales

Water Budget Analysis within the Surrounding of Prominent Lakes and Reservoirs from Multi-Sensor Earth Observation Data and Hydrological Models: Case Studies of the Aral Sea and Lake Mead

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