scholarly journals Using GRACE in a streamflow recession to determine drainable water storage in the Mississippi River basin

2019 ◽  
Vol 23 (8) ◽  
pp. 3269-3277 ◽  
Author(s):  
Heloisa Ehalt Macedo ◽  
Ralph Edward Beighley ◽  
Cédric H. David ◽  
John T. Reager
Keyword(s):  
River Basin ◽  
Mississippi River ◽  
Water Storage ◽  
Mississippi River Basin ◽  
Runoff Generation ◽  
Grace Data ◽  
Basin Scale ◽  
Terrestrial Water ◽  
Gravity Recovery ◽  
Grace Mission

Abstract. The study of the relationship between water storage and runoff generation has long been a focus of the hydrological sciences. NASA's Gravity Recovery and Climate Experiment (GRACE) mission provides monthly depth-integrated information on terrestrial water storage anomalies derived from time-variable gravity observations. As the first basin-scale storage measurement technique, these data offer potentially novel insight into the storage–discharge relationship. Here, we apply GRACE data in a streamflow recession analysis with river discharge measurements across several subdomains of the Mississippi River basin. Nonlinear regression analysis was used for 12 watersheds to determine that the fraction of baseflow in streams during non-winter months varies from 52 % to 75 % regionally. Additionally, the first quantitative estimate of absolute drainable water storage was estimated. For the 2002–2014 period, the drainable storage in the Mississippi River basin ranged from 2900±400 to 3600±400 km3.

scholarly journals Using GRACE in a streamflow recession to determine drainable water storage in the Mississippi River Basin

2019 ◽  
Author(s):  
Heloisa Ehalt Macedo ◽  
Ralph Edward Beighley ◽  
Cedric H. David ◽  
John T. Reager
Keyword(s):  
River Basin ◽  
Mississippi River ◽  
Linear Regression Analysis ◽  
Water Storage ◽  
Mississippi River Basin ◽  
Runoff Generation ◽  
Grace Data ◽  
Basin Scale ◽  
Terrestrial Water ◽  
Gravity Recovery

Abstract. The study of the relationship between water storage and runoff generation has long been a focus of the hydrological sciences. NASA’s Gravity Recovery and Climate Experiment (GRACE) mission provides monthly depth-integrated information on terrestrial water storage anomalies derived from time-variable gravity observations. As the first basin-scale storage measurement technique, these data offer potentially novel insight into the storage-discharge relationship. Here, we apply GRACE data in a streamflow recession analysis with river discharge measurements across several subdomains of the Mississippi River Basin. Non-linear regression analysis was used for 12 watersheds to determine that the fraction of baseflow in streams during non-winter months varies from 52 to 75 % regionally. Additionally, the first quantitative estimate of absolute drainable water storage was estimated. For the 2002–2014 period, the drainable storage in the Mississippi River Basin ranged from 2,900 ± 400 km3 to 3,600 ± 400 km3.

scholarly journals Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin

2008 ◽  
Vol 9 (3) ◽  
pp. 535-548 ◽  
Author(s):  
Benjamin F. Zaitchik ◽  
Matthew Rodell ◽  
Rolf H. Reichle
Keyword(s):  
River Basin ◽  
Mississippi River ◽  
Land Surface ◽  
River Flow ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Mississippi River Basin ◽  
Terrestrial Water Storage ◽  
Terrestrial Water

Abstract Assimilation of data from the Gravity Recovery and Climate Experiment (GRACE) system of satellites yielded improved simulation of water storage and fluxes in the Mississippi River basin, as evaluated against independent measurements. The authors assimilated GRACE-derived monthly terrestrial water storage (TWS) anomalies for each of the four major subbasins of the Mississippi into the Catchment Land Surface Model (CLSM) using an ensemble Kalman smoother from January 2003 to May 2006. Compared with the open-loop CLSM simulation, assimilation estimates of groundwater variability exhibited enhanced skill with respect to measured groundwater in all four subbasins. Assimilation also significantly increased the correlation between simulated TWS and gauged river flow for all four subbasins and for the Mississippi River itself. In addition, model performance was evaluated for eight smaller watersheds within the Mississippi basin, all of which are smaller than the scale of GRACE observations. In seven of eight cases, GRACE assimilation led to increased correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications.

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

2015 ◽  
Vol 19 (4) ◽  
pp. 2079-2100 ◽  
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.

The uncertainty of storage-based drought indices from GRACE

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

<p>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.</p><p>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.</p><p>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.</p>

Nitrate stable isotopes: tools for determining nitrate sources among different land uses in the Mississippi River Basin

2002 ◽  
Vol 59 (12) ◽  
pp. 1874-1885 ◽  
Author(s):  
Cecily C.Y Chang ◽  
Carol Kendall ◽  
Steven R Silva ◽  
William A Battaglin ◽  
Donald H Campbell
Keyword(s):  
Land Use ◽  
Stable Isotopes ◽  
River Basin ◽  
Mississippi River ◽  
Large River ◽  
Mississippi River Basin ◽  
Land Uses ◽  
Nitrate Sources ◽  
Isotopic Signatures ◽  
Basin Scale

A study was conducted to determine whether NO3– stable isotopes (δ15N and δ18O), at natural abundance levels, could discriminate among NO3– sources from sites with different land uses at the basin scale. Water samples were collected from 24 sites in the Mississippi River Basin from five land-use categories: (1) large river basins (>34 590 km2) draining multiple land uses and smaller basins in which the predominant land use was (2) urban, (3) undeveloped, (4) crops, or (5) crops and livestock. Our data suggest that riverine nitrates from different land uses have overlapping but moderately distinct isotopic signatures. δ18O data were critical in showing abrupt changes in NO3– source with discharge. The isotopic values of large rivers resembled crop sites, sites with livestock tended to have δ15N values characteristic of manure, and urban sites tended to have high δ18O values characteristic of atmospheric nitrate.

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

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.

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

2010 ◽  
Vol 11 (1) ◽  
pp. 156-170 ◽  
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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