scholarly journals Interpretation of GRACE data of the Nile Basin using a groundwater recharge model

2010 ◽  
Vol 7 (4) ◽  
pp. 4501-4533 ◽  
Author(s):  
H. C. Bonsor ◽  
M. M. Mansour ◽  
A. M. MacDonald ◽  
A. G. Hughes ◽  
R. G. Hipkin ◽  
...  
Keyword(s):  
Groundwater Recharge ◽  
Water Mass ◽  
Regional Scale ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Nile Basin ◽  
Groundwater Storage ◽  
Grace Data ◽  
Terrestrial Water ◽  
Annual Water

Abstract. Assessing and quantifying natural water storage is becoming increasingly important as nations develop strategies for economic growth and adaptations measures for climate change. The Gravity Recovery and Climate Experiment (GRACE) data provide a new opportunity to gain a direct and independent measure of water mass variations on a regional scale. Hydrological models are required to interpret these mass variations and partition them between different parts of the hydrological cycle, but groundwater storage has generally been poorly constrained by such models. This study focused on the Nile basin, and used a groundwater recharge model ZOODRM (Zoomable Object Oriented Distributed Recharge Model) to help interpret the seasonal variation in terrestrial water storage indicated by GRACE. The recharge model was constructed using almost entirely remotely sensed input data and calibrated to observed hydrological data from the Nile. GRACE data for the Nile Basin indicates an annual terrestrial water storage of approximately 200 km3: water input is from rainfall, and much of this water is evaporated within the basin since average annual outflow of the Nile is less than 30 km3. Total annual recharge simulated by ZOODRM is 400 km3/yr; 0–50 mm/yr within the semi arid lower catchments, and a mean of 250 mm/yr in the sub-tropical upper catchments. These results are comparable to the few site specific studies of recharge in the basin. Accounting for year-round discharge of groundwater, the seasonal groundwater storage is 100–150 km3/yr and seasonal change in soil moisture, 30 km3/yr. Together, they account for between 50 and 90% of the annual water storage in the catchment. The annual water mass variation (200 km3/yr) is an order of magnitude smaller than the rainfall input into the catchment (2000 km3/yr), which could be consistent with a high degree of moisture recycling within the basin. Future work is required to advance the calibration of the ZOODRM model, particularly improving the timing of runoff routing.

scholarly journals Recent changes in terrestrial water storage in the Upper Nile Basin: an evaluation of commonly used gridded GRACE products

2017 ◽  
Vol 21 (9) ◽  
pp. 4533-4549 ◽  
Author(s):  
Mohammad Shamsudduha ◽  
Richard G. Taylor ◽  
Darren Jones ◽  
Laurent Longuevergne ◽  
Michael Owor ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Lake Victoria ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Nile Basin ◽  
Lake Victoria Basin ◽  
Groundwater Storage ◽  
Terrestrial Water ◽  
Substantial Uncertainty

Abstract. GRACE (Gravity Recovery and Climate Experiment) satellite data monitor large-scale changes in total terrestrial water storage (ΔTWS), providing an invaluable tool where in situ observations are limited. Substantial uncertainty remains, however, in the amplitude of GRACE gravity signals and the disaggregation of TWS into individual terrestrial water stores (e.g. groundwater storage). Here, we test the phase and amplitude of three GRACE ΔTWS signals from five commonly used gridded products (i.e. NASA's GRCTellus: CSR, JPL, GFZ; JPL-Mascons; GRGS GRACE) using in situ data and modelled soil moisture from the Global Land Data Assimilation System (GLDAS) in two sub-basins (LVB: Lake Victoria Basin; LKB: Lake Kyoga Basin) of the Upper Nile Basin. The analysis extends from January 2003 to December 2012, but focuses on a large and accurately observed reduction in ΔTWS of 83 km3 from 2003 to 2006 in the Lake Victoria Basin. We reveal substantial variability in current GRACE products to quantify the reduction of ΔTWS in Lake Victoria that ranges from 80 km3 (JPL-Mascons) to 69 and 31 km3 for GRGS and GRCTellus respectively. Representation of the phase in TWS in the Upper Nile Basin by GRACE products varies but is generally robust with GRGS, JPL-Mascons, and GRCTellus (ensemble mean of CSR, JPL, and GFZ time-series data), explaining 90, 84, and 75 % of the variance respectively in "in situ" or "bottom-up" ΔTWS in the LVB. Resolution of changes in groundwater storage (ΔGWS) from GRACE ΔTWS is greatly constrained by both uncertainty in changes in soil-moisture storage (ΔSMS) modelled by GLDAS LSMs (CLM, NOAH, VIC) and the low annual amplitudes in ΔGWS (e.g. 1.8–4.9 cm) observed in deeply weathered crystalline rocks underlying the Upper Nile Basin. Our study highlights the substantial uncertainty in the amplitude of ΔTWS that can result from different data-processing strategies in commonly used, gridded GRACE products; this uncertainty is disregarded in analyses of ΔTWS and individual stores applying a single GRACE product.

scholarly journals Recent changes in terrestrial water storage in the Upper Nile Basin: an evaluation of commonly used gridded GRACE products

2017 ◽  
Author(s):  
Mohammad Shamsudduha ◽  
Richard G. Taylor ◽  
Darren Jones ◽  
Laurent Longuevergne ◽  
Michael Owor ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Lake Victoria ◽  
Water Storage ◽  
Series Data ◽  
Terrestrial Water Storage ◽  
Nile Basin ◽  
Groundwater Storage ◽  
Terrestrial Water ◽  
Substantial Uncertainty

Abstract. GRACE (Gravity Recovery and Climate Experiment) satellite data monitor large-scale changes in total terrestrial water storage (ΔTWS) providing an invaluable tool where in situ observations are limited. Substantial uncertainty remains, however, in the amplitude of GRACE gravity signals and the disaggregation of ΔTWS into individual terrestrial water stores (e.g. groundwater storage). Here, we test the phase and amplitude of GRACE ΔTWS signals from 5 commonly-used gridded products (i.e., NASA's GRCTellus: CSR, JPL GFZ; JPL-Mascons; GRGS GRACE) using in situ data and modelled soil-moisture from the Global Land Data Assimilation System (GLDAS). The focus of this analysis is a large and accurately observed reduction in ΔTWS of 75 km3 from 2004 to 2006 in Lake Victoria in the Upper Nile Basin. We reveal substantial variability in current GRACE products to quantify the reduction of ΔTWS in Lake Victoria that ranges from 68 km3 (GRGS) to 50 km3 and 26 km3 for JPL-Mascons and GRCTellus, respectively. Representation of the phase in ΔTWS in the Upper Nile Basin by GRACE products varies but is generally robust with GRGS, JPL-Mascons and GRCTellus (ensemble mean of CSR, JPL and GFZ time-series data) explaining 91 %, 85 %, and 77 % of the variance, respectively, in in-situ ΔTWS. Resolution of changes in groundwater storage (ΔGWS) from GRACE ΔTWS is greatly constrained by both uncertainty in modelled changes in soil-moisture storage (ΔSMS) and the low annual amplitudes in ΔGWS (e.g., 3.5 to 4.4 cm) observed in deeply weathered crystalline rocks underlying the Upper Nile Basin. Our study highlights the substantial uncertainty in the amplitude of ΔTWS that can result from different data-processing strategies in commonly used, gridded GRACE products.

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.

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.

scholarly journals A Multi-Sourced Data Retrodiction of Remotely Sensed Terrestrial Water Storage Changes for West Africa

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 401 ◽  
Author(s):  
Vagner Ferreira ◽  
Samuel Andam-Akorful ◽  
Ramia Dannouf ◽  
Emmanuel Adu-Afari
Keyword(s):  
West Africa ◽  
Water Storage ◽  
Remotely Sensed ◽  
Climate Indices ◽  
Terrestrial Water Storage ◽  
Drought Assessment ◽  
Grace Data ◽  
Short Period ◽  
Terrestrial Water ◽  
Land Data Assimilation System

Remotely sensed terrestrial water storage changes (TWSC) from the past Gravity Recovery and Climate Experiment (GRACE) mission cover a relatively short period (≈15 years). This short span presents challenges for long-term studies (e.g., drought assessment) in data-poor regions like West Africa (WA). Thus, we developed a Nonlinear Autoregressive model with eXogenous input (NARX) neural network to backcast GRACE-derived TWSC series to 1979 over WA. We trained the network to simulate TWSC based on its relationship with rainfall, evaporation, surface temperature, net-precipitation, soil moisture, and climate indices. The reconstructed TWSC series, upon validation, indicate high skill performance with a root-mean-square error (RMSE) of 11.83 mm/month and coefficient correlation of 0.89. The validation was performed considering only 15% of the available TWSC data not used to train the network. More so, we used the total water content changes (TWCC) synthesized from Noah driven global land data assimilation system in a simulation under the same condition as the GRACE data. The results based on this simulation show the feasibility of the NARX networks in hindcasting TWCC with RMSE of 8.06 mm/month and correlation coefficient of 0.88. The NARX network proved robust to adequately reconstruct GRACE-derived TWSC estimates back to 1979.

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>

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