A framework for deriving drought indicators from the Gravity Recovery and Climate Experiment (GRACE)

Abstract. Identifying and quantifying drought in retrospective is a necessity for better understanding drought conditions and the propagation of drought through the hydrological cycle and eventually for developing forecast systems. Hydrological droughts refer to water deficits in surface and subsurface storage, and since these are difficult to monitor at larger scales, several studies have suggested exploiting total water storage data from the GRACE (Gravity Recovery and Climate Experiment) satellite gravity mission to analyze them. This has led to the development of GRACE-based drought indicators. However, it is unclear how the ubiquitous presence of climate-related or anthropogenic water storage trends found within GRACE analyses masks drought signals. Thus, this study aims to better understand how drought signals propagate through GRACE drought indicators in the presence of linear trends, constant accelerations, and GRACE-specific spatial noise. Synthetic data are constructed and existing indicators are modified to possibly improve drought detection. Our results indicate that while the choice of the indicator should be application-dependent, large differences in robustness can be observed. We found a modified, temporally accumulated version of the Zhao et al. (2017) indicator particularly robust under realistic simulations. We show that linear trends and constant accelerations seen in GRACE data tend to mask drought signals in indicators and that different spatial averaging methods required to suppress the spatially correlated GRACE noise affect the outcome. Finally, we identify and analyze two droughts in South Africa using real GRACE data and the modified indicators.

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A framework for deriving drought indicators from GRACE

10.5194/hess-2019-268 ◽

2019 ◽

Author(s):

Helena Gerdener ◽

Olga Engels ◽

Jürgen Kusche

Keyword(s):

Hydrological Cycle ◽

Water Storage ◽

Synthetic Data ◽

Satellite Gravity ◽

Spatially Correlated ◽

Grace Data ◽

Spatial Noise ◽

Drought Indicators ◽

Gravity Recovery ◽

Hydrological Droughts

Abstract. Identifying and quantifying drought in retrospective is a necessity for better understanding drought conditions and the propagation of drought through the hydrological cycle, and eventually for developing forecast systems. Hydrological droughts refer to water deficits in surface and subsurface storage, and since these are difficult to monitor at larger scales, several studies have suggested to exploit total water storage data from the GRACE (Gravity Recovery and Climate Experiment) satellite gravity mission to analyse them. This has led to the development of GRACE-based drought indicators. However, it is unclear how the ubiquitous presence of climate-related or anthropogenic water storage trends, which has been found from GRACE analyses, masks drought signals. Thus, this study aims at a better understanding of how drought signals, in the presence of trends and GRACE-specific spatial noise, propagate through GRACE drought indicators. Synthetic data are constructed and existing indicators are modified to possibly improve drought detection. Our results indicate that while the choice of the indicator should be application dependent, larger differences in robustness can be observed. We found a modified, temporally accumulated version of the Zhao et al. (2017) indicator in particular robust under realistic simulations. We show that trends and accelerations seen in GRACE data tend to mask drought signals in indicators, and that different spatial averaging methods required to suppress the spatially correlated GRACE noise affect the outcome. Finally, we identify and analyse two droughts in South Africa using real GRACE data and the modified indicators.

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Data Assimilation of Terrestrial Water Storage Observations to Estimate Precipitation Fluxes: A Synthetic Experiment

Remote Sensing ◽

10.3390/rs13061223 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1223

Author(s):

Manuela Girotto ◽

Rolf Reichle ◽

Matthew Rodell ◽

Viviana Maggioni

Keyword(s):

Data Assimilation ◽

Snow Water Equivalent ◽

Water Storage ◽

Synthetic Data ◽

Terrestrial Water Storage ◽

Grace Data ◽

Precipitation Estimates ◽

Terrestrial Water ◽

Snow Water ◽

Gravity Recovery

The Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On (GRACE-FO) mission provide unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. Established GRACE data assimilation techniques directly adjust the simulated water storage components to improve the estimation of groundwater, streamflow, and snow water equivalent. Such techniques artificially add/subtract water to/from prognostic variables, thus upsetting the simulated water balance. To overcome this limitation, we propose and test an alternative assimilation scheme in which precipitation fluxes are adjusted to achieve the desired changes in simulated TWS. Using a synthetic data assimilation experiment, we show that the scheme improves performance skill in precipitation estimates in general, but that it is more robust for snowfall than for rainfall, and it fails in certain regions with strong horizontal gradients in precipitation. The results demonstrate that assimilation of TWS observations can help correct (adjust) the model’s precipitation forcing and, in turn, enhance model estimates of TWS, snow mass, soil moisture, runoff, and evaporation. A key limitation of the approach is the assumption that all errors in TWS originate from errors in precipitation. Nevertheless, the proposed approach produces more consistent improvements in simulated runoff than the established GRACE data assimilation techniques.

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Study of water storage variations at the Pantanal wetlands area from GRACE monthly mass grids

Journal of Geodetic Science ◽

10.1515/jogs-2019-0013 ◽

2019 ◽

Vol 9 (1) ◽

pp. 133-143

Author(s):

Ayelen Pereira ◽

Cecilia Cornero ◽

Ana C. O. C. Matos ◽

M. Cristina Pacino ◽

Denizar Blitzkow

Keyword(s):

Water Mass ◽

Spatial Scales ◽

Water Storage ◽

Transport Processes ◽

Satellite Gravity ◽

The North ◽

Paraguay River ◽

Gravity Recovery ◽

Grace Mission ◽

Phase Differences

Abstract The continental water storage is significantly in-fluenced by wetlands, which are highly affected by climate change and anthropogenic influences. The Pantanal, located in the Paraguay river basin, is one of the world’s largest and most important wetlands because of the environmental biodiversity that represents. The satellite gravity mission GRACE (Gravity Recovery And Climate Experiment) provided until 2017 time-variable Earth’s gravity field models that reflected the variations due to mass transport processes-like continental water storage changes-which allowed to study environments such as wetlands, at large spatial scales. The water storage variations for the period 2002-2016, by using monthly land water mass grids of Total Water Storage (TWS) derived from GRACE solutions, were evaluated in the Pantanal area. The capability of the GRACE mission for monitoring this particular environment is analyzed, and the comparison of the water mass changes with rainfall and hydrometric heights data at different stations distributed over the Pantanal region was carried out. Additionally, the correlation between the TWS and river gauge measurements, and the phase differences for these variables, were also evaluated. Results show two distinct zones: high correlations and low phase shifts at the north, and smaller correlation values and consequently significant phase differences towards the south. This situation is mainly related to the hydrogeological domains of the area.

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Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River basin

Hydrology and Earth System Sciences ◽

10.5194/hess-19-2079-2015 ◽

2015 ◽

Vol 19 (4) ◽

pp. 2079-2100 ◽

Cited By ~ 52

Author(s):

N. Tangdamrongsub ◽

S. C. Steele-Dunne ◽

B. C. Gunter ◽

P. G. Ditmar ◽

A. H. Weerts

Keyword(s):

Correlation Coefficient ◽

River Basin ◽

Hydrological Cycle ◽

Water Storage ◽

Model Parameters ◽

Hydrological Models ◽

Rhine River ◽

Terrestrial Water Storage ◽

Grace Data ◽

Terrestrial Water

Abstract. The ability to estimate terrestrial water storage (TWS) realistically is essential for understanding past hydrological events and predicting future changes in the hydrological cycle. Inadequacies in model physics, uncertainty in model land parameters, and uncertainties in meteorological data commonly limit the accuracy of hydrological models in simulating TWS. In an effort to improve model performance, this study investigated the benefits of assimilating TWS estimates derived from the Gravity Recovery and Climate Experiment (GRACE) data into the OpenStreams wflow_hbv model using an ensemble Kalman filter (EnKF) approach. The study area chosen was the Rhine River basin, which has both well-calibrated model parameters and high-quality forcing data that were used for experimentation and comparison. Four different case studies were examined which were designed to evaluate different levels of forcing data quality and resolution including those typical of other less well-monitored river basins. The results were validated using in situ groundwater (GW) and stream gauge data. The analysis showed a noticeable improvement in GW estimates when GRACE data were assimilated, with a best-case improvement of correlation coefficient from 0.31 to 0.53 and root mean square error (RMSE) from 8.4 to 5.4 cm compared to the reference (ensemble open-loop) case. For the data-sparse case, the best-case GW estimates increased the correlation coefficient from 0.46 to 0.61 and decreased the RMSE by 35%. For the average improvement of GW estimates (for all four cases), the correlation coefficient increases from 0.6 to 0.7 and the RMSE was reduced by 15%. Only a slight overall improvement was observed in streamflow estimates when GRACE data were assimilated. Further analysis suggested that this is likely due to sporadic short-term, but sizeable, errors in the forcing data and the lack of sufficient constraints on the soil moisture component. Overall, the results highlight the benefit of assimilating GRACE data into hydrological models, particularly in data-sparse regions, while also providing insight on future refinements of the methodology.

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The uncertainty of storage-based drought indices from GRACE

10.5194/egusphere-egu2020-3604 ◽

2020 ◽

Author(s):

Peyman Saemian ◽

Mohammad Javad Tourian ◽

Nico Sneeuw

Keyword(s):

Land Surface ◽

Water Storage ◽

Extended Period ◽

Drought Indices ◽

Terrestrial Water Storage ◽

Earth’S Gravity Field ◽

Grace Data ◽

Temporal And Spatial Variability ◽

Terrestrial Water ◽

Gravity Recovery

Climate change and the growing demand for freshwater have raised the frequency and intensity of extreme events like drought. Satellite observations have improved our understanding of the temporal and spatial variability of droughts. Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-On (GRACE-FO) have been observing variations in Earth's gravity field yielding valuable information about changes in terrestrial water storage anomaly (TWSA). The terrestrial water storage vertically integrates all forms of water on and beneath land surface including snow, surface water, soil moisture, and groundwater storage.Drought indices help to monitor drought by characterizing it in terms of their severity, location, duration and timing. Several drought indices have been developed based on GRACE water storage anomaly from a GRACE-based climatology, most of which suffer from the short record of GRACE, about 15 years, for their climatology. The limited duration of the GRACE observations necessitates the use of external datasets of TWSA with a more extended period for climatology. Drought characterization comes with its own uncertainties due to the inherent uncertainty in the GRACE data, the various post-processing approaches of GRACE data, and different options for external datasets on the other hand.This study offers a method to quantify uncertainties for the storage-based drought index. Moreover, we assess the sensitivity of major global river basins to the duration of the observations. The outcome of the study is invaluable in the sense that it allows for a more informative storage based drought, including uncertainty, thus enabling a more realistic risk assessment.

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Evaluating short-term hydro-meteorological fluxes in global atmospheric reanalyses using daily GRACE data

10.5194/egusphere-egu2020-4502 ◽

2020 ◽

Author(s):

Viviana Wöhnke ◽

Annette Eicker ◽

Laura Jensen ◽

Andreas Kvas ◽

Torsten Mayer-Gürr ◽

...

Keyword(s):

Water Storage ◽

Numerical Differentiation ◽

Evaluation Tool ◽

Satellite Gravity ◽

Data Set ◽

Weather Forecasts ◽

Grace Data ◽

Terrestrial Water ◽

Band Pass ◽

Net Flux

Changes in terrestrial water storage as observed by the satellite gravity mission GRACE represent a new and completely independent data set for constraining the net flux deficit of precipitation (P), evapotranspiration (E), and lateral runoff (R) in atmospheric reanalyses.In this study we use daily GRACE gravity field changes to investigate high-frequency hydro-meteorological fluxes over the continents. Band-pass filtered water fluxes are derived from GRACE water storage time series by first applying a numerical differentiation filter and subsequent high-pass filtering to isolate fluxes at periods between 5 and 30 days.We can show that on these time scales GRACE is able to identify quality differences between different reanalyses, e.g. the improvements in the latest reanalysis ERA5 of the European Centre for Medium-Range Weather Forecasts (ECWMF) over its direct predecessor ERA-Interim. We will therefore use GRACE as an evaluation tool to compare hydro-meteorological fluxes in various global atmospheric reanalyses, such as ERA5(-Land), ERA-Interim, Merra2, JRA-55, or NCEP.

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Dynamics of Terrestrial Water Storage Change from Satellite and Surface Observations and Modeling

Journal of Hydrometeorology ◽

10.1175/2009jhm1152.1 ◽

2010 ◽

Vol 11 (1) ◽

pp. 156-170 ◽

Cited By ~ 48

Author(s):

Qiuhong Tang ◽

Huilin Gao ◽

Pat Yeh ◽

Taikan Oki ◽

Fengge Su ◽

...

Keyword(s):

Water Cycle ◽

Regional Scale ◽

Water Storage ◽

Terrestrial Water Storage ◽

Surface Observation ◽

Grace Data ◽

Terrestrial Water ◽

Gravity Recovery ◽

Storage Change ◽

Surface Observations

Abstract Terrestrial water storage (TWS) is a fundamental component of the water cycle. On a regional scale, measurements of terrestrial water storage change (TWSC) are extremely scarce at any time scale. This study investigates the feasibility of estimating monthly-to-seasonal variations of regional TWSC from modeling and a combination of satellite and in situ surface observations based on water balance computations that use ground-based precipitation observations in both cases. The study area is the Klamath and Sacramento River drainage basins in the western United States (total area of about 110 000 km2). The TWSC from the satellite/surface observation–based estimates is compared with model results and land water storage from the Gravity Recovery and Climate Experiment (GRACE) data. The results show that long-term evapotranspiration estimates and runoff measurements generally balance with observed precipitation, suggesting that the evapotranspiration estimates have relatively small bias for long averaging times. Observations show that storage change in water management reservoirs is about 12% of the seasonal amplitude of the TWSC cycle, but it can be up to 30% at the subbasin scale. Comparing with predevelopment conditions, the satellite/surface observation–based estimates show larger evapotranspiration and smaller runoff than do modeling estimates, suggesting extensive anthropogenic alteration of TWSC in the study area. Comparison of satellite/surface observation–based and GRACE TWSC shows that the seasonal cycle of terrestrial water storage is substantially underestimated by GRACE.

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Downscaling GRACE total water storage change using partial least squares regression

Scientific Data ◽

10.1038/s41597-021-00862-6 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Bramha Dutt Vishwakarma ◽

Jinwei Zhang ◽

Nico Sneeuw

Keyword(s):

Water Mass ◽

Spatial Scales ◽

Water Storage ◽

Temporal Variations ◽

Least Squares Regression ◽

Total Water ◽

Satellite Mission ◽

Grace Data ◽

Gravity Recovery ◽

Storage Change

AbstractThe Gravity Recovery And Climate Experiment (GRACE) satellite mission recorded temporal variations in the Earth’s gravity field, which are then converted to Total Water Storage Change (TWSC) fields representing an anomaly in the water mass stored in all three physical states, on and below the surface of the Earth. GRACE provided a first global observational record of water mass redistribution at spatial scales greater than 63000 km2. This limits their usability in regional hydrological applications. In this study, we implement a statistical downscaling approach that assimilates 0.5° × 0.5° water storage fields from the WaterGAP hydrology model (WGHM), precipitation fields from 3 models, evapotranspiration and runoff from 2 models, with GRACE data to obtain TWSC at a 0.5° × 0.5° grid. The downscaled product exploits dominant common statistical modes between all the hydrological datasets to improve the spatial resolution of GRACE. We also provide open access to scripts that researchers can use to produce downscaled TWSC fields with input observations and models of their own choice.

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ANALYSIS OF WATER MASS VARIATIONS AT WETLANDS REGIONS FROM GRACE: THE PANTANAL CASE

Brazilian Journal of Geophysics ◽

10.22564/rbgf.v35i4.786 ◽

2018 ◽

Vol 35 (4) ◽

pp. 307

Author(s):

Cecilia Cornero ◽

AYELEN PEREIRA ◽

MARÍA CRISTINA PACINO

Keyword(s):

Water Mass ◽

Spatial Scales ◽

Water Storage ◽

Transport Processes ◽

Satellite Gravity ◽

The North ◽

Paraguay River ◽

Gravity Recovery ◽

Gravity Mission

ABSTRACT. The natural heritage of biodiversity of the Paraguay river basin is subject to potential impacts due to climate change. To monitor these environments at large spatial scales, the satellite gravity mission GRACE (Gravity Recovery and Climate Experiment) provides time-variable Earth’s gravity field models that reflect the variations due to mass transport processes, like continental water storage changes. The purpose of this work is to analyze the spatial and temporal water storage changes for period 2003-2014 using the Equivalent Water Height (EWH) derived from the GRACE solutions in the Pantanal region, one of the most biologically rich environments of the planet. The comparison with EWH and river gauge data at different stations distributed over the Pantanal area was carried out. In order to validate the satellite results, the correlation analysis between the water mass changes and river gauge measurements was obtained, and also the phase differences were analyzed. High correlations were detected at the north, and lower ones towards the south of the Pantanal. The EWH were also contrasted with soil moisture and rainfall data models. The results showed a good agreement between the signals for the area under study.Keywords: water storage, satellite gravity mission, river gauge, rainfall. RESUMO. O patrimônio natural de biodiversidade da bacia do rio Paraguai está sujeito a potenciais impactos das mudanças climáticas. Para monitorar esse ambiente em escala espacial, a missão satelital GRACE (Gravity Recovery and Climate Experiment) fornece modelos do campo de gravidade da Terra variáveis no tempo devido ao processo de transporte de massa, como as variações de armazenamento de água continentais. O objetivo deste artigo é analisar a variabilidade espacial e temporal de armazenamento de água para o período 2003-2014 através da altura equivalente d’água (EWH) derivada das soluções deGRACE na região do Pantanal, um dos ambientes biologicamente mais ricos do planeta. Comparações dos dados de EWH e alturas d’água in-situ foram feitas para diferentes estações distribuídas na região do Pantanal. Com a finalidade de validar os resultados de satélite, foi feita a análise de correlação entre as mudanças de massa d’água e as medições das réguas linimétricas fixadas nas margens dos rios. As diferenças de fase também foram analisadas. Ao Norte do Pantanal foram detectadas altas correlações entre as duas alturas (EWH versus in-situ), e baixas em direção ao sul. O EWH também foi validado com modelos de umidade do solo e precipitação. Os resultados mostraram uma boa concordância entre os sinais para a área em estudo. Palavras-chave: armazenamento de água, missão satelital, cotas do nível d’água, precipitação.

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Geophysical interpretation of GPS loading deformation over western Europe using GRACE measurements

Annals of Geophysics ◽

10.4401/ag-7058 ◽

2016 ◽

Vol 59 (5) ◽

Author(s):

Songyun Wang ◽

Jianli Chen ◽

Jin Li ◽

Xiaogong Hu ◽

Shengnan Ni

Keyword(s):

Western Europe ◽

International Gnss Service ◽

Satellite Gravity ◽

Surface Mass ◽

Grace Data ◽

Surface Displacements ◽

Residual Series ◽

Vertical Displacements ◽

Gravity Recovery ◽

Improved Accuracy

We analyze more than 10 years of Global Positioning System (GPS) height residuals and vertical displacements predicted from surface mass loading observed by the Gravity Recovery and Climate Experiment (GRACE) for 36 International GNSS Service (IGS) stations over Europe. Seasonal surface displacements, mostly due to atmospheric and hydrological loading, are significant in both GPS and GRACE measurements. With an extended time period, our new analysis based on release 05 GRACE data from Center for Space Research (CSR) shows considerably improved agreement between GPS and GRACE than that from previous studies, for not only annual but also interannual signals. The GPS height residual series at most stations exhibit reduced weighted root-mean-squares (WRMS) after removing GRACE-derived vertical displacements, which is attributed to improved accuracy of both GPS and GRACE data products. Furthermore, we demonstrate the necessity of reducing leakage bias in GRACE estimates for the study of surface loading deformation using GRACE satellite gravity observations.

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