Assimilation of Ground‐based GPS Observations of Vertical Displacement into a Land Surface Model to Improve Terrestrial Water Storage Estimates

2020 ◽  
Author(s):  
Gaohong Yin ◽  
Barton A. Forman ◽  
Jing Wang
Keyword(s):  
Land Surface ◽  
Water Storage ◽  
Land Surface Model ◽  
Vertical Displacement ◽  
Surface Model ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Gps Observations

Exploration of Terrestrial Water Storage Characterization via Assimilation of Ground-based GPS Observations of Vertical Displacement and GRACE TWS Retrievals

2020 ◽  
Author(s):  
Gaohong Yin ◽  
Barton Forman ◽  
Jing Wang
Keyword(s):  
Great Basin ◽  
Land Surface ◽  
Water Storage ◽  
Vertical Displacement ◽  
Estimation Accuracy ◽  
Terrestrial Water Storage ◽  
Drought Period ◽  
Terrestrial Water ◽  
Gps Observations

<p>Accurate estimation of terrestrial water storage (TWS) is crucial in the characterization of the terrestrial hydrologic cycle. The launch of GRACE and GRACE Follow-On (GRACE-FO) missions provide an unprecedented opportunity to monitor the change in TWS across the globe. However, the spatial and temporal resolutions provided by GRACE/GRACE-FO are often too coarse for many hydrologic applications. Land surface models (LSMs) provide estimates of TWS at a finer spatio-temporal resolution, but most LSMs lack complete, all-encompassing physical representations of the hydrological system such as deep groundwater storage or anthropogenic influences (e.g., groundwater pumping and surface water regulation). In recent years, geodetic measurements from the ground-based Global Positioning System (GPS) network have been increasingly used in hydrologic studies based on the elastic response of the Earth’s surface to mass redistribution. This study explores the potential of improving our knowledge in TWS change via merging the information provided by ground-based GPS, GRACE, and the NASA Catchment Land Surface Model (Catchment), especially for the TWS change during an extended drought period.</p> <p> </p> <p>Ground-based GPS observations of vertical displacement and GRACE TWS retrievals were assimilated into the Catchment LSM, respectively, using an ensemble Kalman filter (EnKF) in order to improve the estimation accuracy of TWS change. The data assimilation (DA) framework effectively downscaled TWS into its constituent components (e.g., snow and soil moisture) as well as improved estimates of hydrologic fluxes (e.g., runoff). Estimated TWS change from the open loop (OL; without assimilation) and GPS DA (i.e., using GPS-based vertical displacement during assimilation) simulations were evaluated against GRACE TWS retrievals. Results show that GPS DA improved estimation accuracy of TWS change relative to the OL, especially during an extended drought period post-2011 in the western United States (e.g., the correlation coefficient R<sub>OL</sub> = 0.46 and R<sub>GPSDA</sub> = 0.82 in the Great Basin). The performance of GPS DA and GRACE DA in estimating TWS constituent components and hydrologic fluxes were evaluated against in situ measurements. Results show that GPS DA improves snow water equivalent (SWE) estimates with improved R values found over 76% of all pixels that are collocated with in situ stations in the Great Basin. The findings in this study indicate the potential use of GPS DA and GRACE DA for TWS characterization. Both GRACE and ground-based GPS provide complementary TWS change information, which helps correct for missing physics in the LSM. Additionally, this study provides motivation for a multi-variate assimilation approach to simultaneously merge both GRACE and ground-based GPS into an LSM to further improve modeled TWS and its constituent components.</p>

scholarly journals Development and evaluation of 0.05° terrestrial water storage estimates using CABLE land surface model and GRACE data assimilation

2021 ◽  
Author(s):  
Natthachet Tangdamrongsub ◽  
Michael F. Jasinski ◽  
Peter Shellito
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Land Surface ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Parameters ◽  
Terrestrial Water Storage ◽  
Grace Data ◽  
Terrestrial Water

Abstract. Accurate estimation of terrestrial water storage (TWS) at a meaningful spatiotemporal resolution is important for reliable assessments of regional water resources and climate variability. Individual components of TWS include soil moisture, snow, groundwater, and canopy storage and can be estimated from the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. The spatial resolution of CABLE is currently limited to 0.5° by the resolution of soil and vegetation datasets that underlie model parameterizations, posing a challenge to using CABLE for hydrological applications at a local scale. This study aims to improve the spatial detail (from 0.5° to 0.05°) and timespan (1981–2012) of CABLE TWS estimates using rederived model parameters and high-resolution meteorological forcing. In addition, TWS observations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are assimilated into CABLE to improve TWS accuracy. The success of the approach is demonstrated in Australia, where multiple ground observation networks are available for validation. The evaluation process is conducted using four different case studies that employ different model spatial resolutions and include or omit GRACE data assimilation (DA). We find that the CABLE 0.05° developed here improves TWS estimates in terms of accuracy, spatial resolution, and long-term water resource assessment reliability. The inclusion of GRACE DA increases the accuracy of groundwater storage (GWS) estimates and has little impact on surface soil moisture or evapotranspiration. The use of improved model parameters and improved state estimations (via GRACE DA) together is recommended to achieve the best GWS accuracy. The workflow elaborated in this paper relies only on publicly accessible global datasets, allowing reproduction of the 0.05° TWS estimates in any study region.

scholarly journals Assimilation of gridded terrestrial water storage observations from GRACE into a land surface model

2016 ◽  
Vol 52 (5) ◽  
pp. 4164-4183 ◽  
Author(s):  
Manuela Girotto ◽  
Gabriëlle J. M. De Lannoy ◽  
Rolf H. Reichle ◽  
Matthew Rodell
Keyword(s):  
Land Surface ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Terrestrial Water Storage ◽  
Terrestrial Water

scholarly journals Assimilation of GRACE Terrestrial Water Storage Observations into a Land Surface Model for the Assessment of Regional Flood Potential

2015 ◽  
Vol 7 (11) ◽  
pp. 14663-14679 ◽  
Author(s):  
John Reager ◽  
Alys Thomas ◽  
Eric Sproles ◽  
Matthew Rodell ◽  
Hiroko Beaudoing ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Terrestrial Water Storage ◽  
Terrestrial Water

Data assimilation of satellite-based terrestrial water storage changes into a hydrology land-surface model

2020 ◽  
pp. 125744
Author(s):  
Ala Bahrami ◽  
Kalifa Goïta ◽  
Ramata Magagi ◽  
Bruce Davison ◽  
Saman Razavi ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Land Surface ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Terrestrial Water Storage ◽  
Terrestrial Water

scholarly journals Development and evaluation of 0.05° terrestrial water storage estimates using Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and assimilation of GRACE data

2021 ◽  
Vol 25 (7) ◽  
pp. 4185-4208
Author(s):  
Natthachet Tangdamrongsub ◽  
Michael F. Jasinski ◽  
Peter J. Shellito
Keyword(s):  
Land Surface ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Parameters ◽  
Data Sets ◽  
Terrestrial Water Storage ◽  
Grace Data ◽  
Terrestrial Water ◽  
Land Exchange

Abstract. Accurate estimation of terrestrial water storage (TWS) at a high spatiotemporal resolution is important for reliable assessments of regional water resources and climate variability. Individual components of TWS include soil moisture, snow, groundwater, and canopy storage and can be estimated from the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. The spatial resolution of CABLE is currently limited to 0.5∘ by the resolution of soil and vegetation data sets that underlie model parameterizations, posing a challenge to using CABLE for hydrological applications at a local scale. This study aims to improve the spatial detail (from 0.5 to 0.05∘) and time span (1981–2012) of CABLE TWS estimates using rederived model parameters and high-resolution meteorological forcing. In addition, TWS observations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are assimilated into CABLE to improve TWS accuracy. The success of the approach is demonstrated in Australia, where multiple ground observation networks are available for validation. The evaluation process is conducted using four different case studies that employ different model spatial resolutions and include or omit GRACE data assimilation (DA). We find that the CABLE 0.05∘ developed here improves TWS estimates in terms of accuracy, spatial resolution, and long-term water resource assessment reliability. The inclusion of GRACE DA increases the accuracy of groundwater storage (GWS) estimates and has little impact on surface soil moisture or evapotranspiration. Using improved model parameters and improved state estimations (via GRACE DA) together is recommended to achieve the best GWS accuracy. The workflow elaborated on in this paper relies only on publicly accessible global data sets, allowing the reproduction of the 0.05∘ TWS estimates in any study region.

scholarly journals Retrieving snow mass from GRACE terrestrial water storage change with a land surface model

2007 ◽  
Vol 34 (15) ◽  
Author(s):  
Guo-Yue Niu ◽  
Ki-Weon Seo ◽  
Zong-Liang Yang ◽  
Clark Wilson ◽  
Hua Su ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Storage Change ◽  
Snow Mass

scholarly journals Widespread decline in terrestrial water storage and its link to teleconnections across Asia and eastern Europe

2020 ◽  
Vol 24 (7) ◽  
pp. 3663-3676
Author(s):  
Xianfeng Liu ◽  
Xiaoming Feng ◽  
Philippe Ciais ◽  
Bojie Fu
Keyword(s):  
Land Surface ◽  
Southern Oscillation ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Global Changes ◽  
Eastern European ◽  
Terrestrial Water Storage ◽  
European Regions ◽  
Terrestrial Water

Abstract. Recent global changes in terrestrial water storage (TWS) and associated freshwater availability raise major concerns about the sustainability of global water resources. However, our knowledge regarding the long-term trends in TWS and its components is still not well documented. In this study, we characterize the spatiotemporal variations in TWS and its components over the Asian and eastern European regions from April 2002 to June 2017 based on Gravity Recovery and Climate Experiment (GRACE) satellite observations, land surface model simulations, and precipitation observations. The connections of TWS and global major teleconnections (TCs) are also discussed. The results indicate a widespread decline in TWS during 2002–2017, and five hotspots of TWS negative trends were identified with trends between −8.94 and −21.79 mm yr−1. TWS partitioning suggests that these negative trends are primarily attributed to the intensive over-extraction of groundwater and warmth-induced surface water loss, but the contributions of each hydrological component vary among hotspots. The results also indicate that the El Niño–Southern Oscillation, Arctic Oscillation and North Atlantic Oscillation are the three largest dominant factors controlling the variations in TWS through the covariability effect on climate variables. However, seasonal results suggest a divergent response of hydrological components to TCs among seasons and hotspots. Our findings provide insights into changes in TWS and its components over the Asian and eastern European regions, where there is a growing demand for food grains and water supplies.

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