GRACE products and land surface models for estimating the changes in key water storage components in the Nile River Basin

2021 ◽  
Vol 67 (6) ◽  
pp. 1896-1913 ◽  
Author(s):  
Zemede M. Nigatu ◽  
Dongming Fan ◽  
Wei You
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Water Storage ◽  
Nile River ◽  
Land Surface Models ◽  
Surface Models ◽  
Nile River Basin

scholarly journals Using GRACE/GRACE-FO, Data-Driven, and Modeling to Assess the Twentieth and Twenty-first Century Water Storage Changes in the Nile River Basin

2021 ◽  
Author(s):  
Emad Hasan ◽  
Aondover Tarhule ◽  
Pierre-Emmanuel Kirstetter
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Land Surface ◽  
Water Storage ◽  
Data Driven ◽  
Nile River ◽  
Surface Model ◽  
Distribution Fitting ◽  
Duration Magnitude ◽  
Nile River Basin

This research assesses the changes in the total water storage (TWS) during the twentieth century and their future projections in the Nile River Basin (NRB) via TWSA (TWS anomalies) records from GRACE (Gravity Recovery and Climate Experiment), GRACE-FO (Follow-On), data-driven-reanalysis TWSA and land surface model (LSM), in association with precipitation, temperature records, and standard drought indicators. The analytical approach incorporates the development of 100+ yearlong TWSA records using a probabilistic conditional distribution fitting approach by the GAMLSS (Generalized Additive Model for Location, Scale, and Shape) model. The drought and flooding severity, duration, magnitude, frequencies, and recurrence were assessed during the studied period. The results showed, 1- The NRB between 2002 to 2020 has transited to substantial wetter conditions. 2- The TWSA reanalysis records between 1901 to 2002 revealed that the NRB had experienced a positive increase in TWS during the wet and dry seasons. 3- The projected TWSA between 2021 to 2050 indicated slight positive changes in TWSA during the rainy seasons. The analysis of drought and flooding frequencies between 1901 to 2050 indicated the NRB has ~64 dry-years compared to ~86 wet-years. The 100+ yearlong TWSA records assured that the NRB transited to wetter conditions relative to few dry spells. These TWSA trajectories call for further water resources planning in the region especially during flood seasons. This research contributes to the ongoing efforts to improve the TWSA assessment and its associated dynamics for transboundary river basins. It also demonstrates how an extended TWSA record provides unique insights for water resources management in the NRB and similar regions.

scholarly journals Twentieth and Twenty-First Century Water Storage Changes in the Nile River Basin from GRACE/GRACE-FO and Modeling

2021 ◽  
Vol 13 (5) ◽  
pp. 953
Author(s):  
Emad Hasan ◽  
Aondover Tarhule ◽  
Pierre-Emmanuel Kirstetter
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Water Storage ◽  
Model Performance ◽  
Dry Season ◽  
Nile River ◽  
Surface Model ◽  
Wet Season ◽  
Distribution Fitting ◽  
Nile River Basin

This research assesses the changes in total water storage (TWS) during the twentieth century and future projections in the Nile River Basin (NRB) via TWSA (TWS anomalies) records from GRACE (Gravity Recovery and Climate Experiment), GRACE-FO (Follow-On), data-driven-reanalysis TWSA and a land surface model (LSM), in association with precipitation, temperature records, and standard drought indicators. The analytical approach incorporates the development of 100+ yearlong TWSA records using a probabilistic conditional distribution fitting approach by the GAMLSS (generalized additive model for location, scale, and shape) model. The model performance was tested using standard indicators including coevolution plots, the Nash–Sutcliffe coefficient, cumulative density function, standardized residuals, and uncertainty bounds. All model evaluation results are satisfactory to excellent. The drought and flooding severity/magnitude, duration, and recurrence frequencies were assessed during the studied period. The results showed, (1) The NRB between 2002 to 2020 has witnessed a substantial transition to wetter conditions. Specifically, during the wet season, the NRB received between ~50 Gt./yr. to ~300 Gt./yr. compared to ~30 Gt./yr. to ~70 Gt./yr. of water loss during the dry season. (2) The TWSA reanalysis records between 1901 to 2002 revealed that the NRB had experienced a positive increase in TWS of ~17% during the wet season. Moreover, the TWS storage had witnessed a recovery of ~28% during the dry season. (3) The projected TWSA between 2021 to 2050 unveiled a positive increase in the TWS during the rainy season. While during the dry season, the water storage showed insubstantial TWS changes. Despite these projections, the future storage suggested a reduction between 10 to 30% in TWS. The analysis of drought and flooding frequencies between 1901 to 2050 revealed that the NRB has ~64 dry-years compared to ~86 wet-years. The exceedance probabilities for the normal conditions are between 44 to 52%, relative to a 4% chance of extreme events. The recurrence interval of the normal to moderate wet or dry conditions is ~6 years. These TWSA trajectories call for further water resources planning in the region, especially during flood seasons. This research contributes to the ongoing efforts to improve the TWSA assessment and its associated dynamics for transboundary river basins.

scholarly journals Integrating GRACE products and land surface models to estimate changes in key components of terrestrial water storage in the Nile River Basin

2020 ◽  
Author(s):  
Zemede M. Nigatu ◽  
Dongming Fan ◽  
Wei You
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
River Basin ◽  
Land Surface ◽  
Signal To Noise Ratio ◽  
Water Storage ◽  
Nile River ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Nile River Basin

Abstract The Nile River Basin (NRB) is facing extreme pressure on its water resources due to an alarmingly increasing population that is extremely vulnerable in aspects of irrigation and hydropower. The NRB ascends itself to remotely sensed approaches with high resolution of spatial and temporal coverage as disparate to ground-based in-situ observations due to its size and limited access from basin countries. The Gravity Recovery and Climate Experiment (GRACE) allow a unique opportunity to investigate the changes in key components of Terrestrial Water Storage (TWS). Differences in tuning parameters and processing strategies result in GRACE TWS solutions with regionally specific variations and error patterns. We explored the spatiotemporal changes of the TWS time series, trend, uncertainties, and signal-to-noise ratio (SNR) among different GRACE TWS. We had also investigated the key terrestrial water storage components (surface water, soil moisture, and groundwater storage changes). The results show that the uncertainty of GRACE spherical harmonic (SH) solutions are higher than the mass concentration (mascon) over the NRB, and the Center for Space Research-mascons (CSR-M) noted the first best performance. Substantially, significant long-term (2003–2017) negative groundwater and soil moisture trend demonstrates a potential depletion over NRB. Despite an increase in precipitation and TWS time series, the rate of decline noted to increase rapidly from 2008, thus indicating the possibility of human-induced change ( e.g., for irrigation purposes). Thus, the result of this study provides a guiding principle for future studies in TWS change-related hydro-climatic change over NRB and similar basins.

scholarly journals Trend Dynamics of GRACE Terrestrial Water Storage in the Nile River Basin

2019 ◽  
Author(s):  
Emad Hasan ◽  
Aondover Tarhule
Keyword(s):  
Soil Moisture ◽  
Population Density ◽  
River Basin ◽  
Goodness Of Fit ◽  
Water Storage ◽  
Least Square ◽  
Nile River ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Nile River Basin

GRACE-derived Terrestrial Water Storage Anomalies (TWSA) continue to be used in an expanding array of studies to analyze numerous processes and phenomena related to terrestrial water storage dynamics, including groundwater depletions, lake storage variations, snow, and glacial mass changes, as well as floods, droughts, among others. So far, however, few studies have investigated how the factors that affect total water storage (e.g., precipitation, runoff, soil moisture, evapotranspiration) interact and combine over space and time to produce the mass variations that GRACE detects. This paper is an attempt to fill that gap and stimulate needed research in this area. Using the Nile River Basin as case study, it explicitly analyzes nine hydroclimatic and anthropogenic processes, as well as their relationship to TWS in different climatic zones in the Nile River Basin. The analytic method employed the trends in both the dependent and independent variables applying two geographically multiple regression (GMR) approaches: (i) an unweighted or ordinary least square regression (OLS) model in which the contributions of all variables to TWS variability are deemed equal at all locations; and (ii) a geographically weighted regression (GWR) which assigns a weight to each variable at different locations based on the occurrence of trend clusters, determined by Moran’s cluster index. In both cases, model efficacy was investigated using standard goodness of fit diagnostics. The OLS showed that trends in five variables (i.e., precipitation, runoff, surface water soil moisture, and population density) significantly (p<0.0001) explain the trends in TWSA for the basin at large. However, the models R2 value is only 0.14. In contrast, the GWR produced R2 values ranging between 0.40 and 0.89, with an average of 0.86 and normally distributed standard residuals. The models retained in the GWR differ by climatic zone. The results showed that all nine variables contribute significantly to the trend in TWS in the Tropical region; population density is an important contributor to TWSA variability in all zones; ET and Population density are the only significant variables in the semiarid zone. This type of information is critical for developing robust statistical models for reconstructing time series of proxy GRACE anomalies that predate the launch of the GRACE mission and for gap-filling between GRACE and GRACE-FO.

scholarly journals Comparison and Assessment of Three Advanced Land Surface Models in Simulating Terrestrial Water Storage Components over the United States

2017 ◽  
Vol 18 (3) ◽  
pp. 625-649 ◽  
Author(s):  
Youlong Xia ◽  
David Mocko ◽  
Maoyi Huang ◽  
Bailing Li ◽  
Matthew Rodell ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Land Surface ◽  
Water Storage ◽  
The United States ◽  
Major Contributor ◽  
Terrestrial Water Storage ◽  
Land Surface Models ◽  
Community Land Model ◽  
Surface Models ◽  
Terrestrial Water

Abstract To prepare for the next-generation North American Land Data Assimilation System (NLDAS), three advanced land surface models [LSMs; i.e., Community Land Model, version 4.0 (CLM4.0); Noah LSM with multiphysics options (Noah-MP); and Catchment LSM-Fortuna 2.5 (CLSM-F2.5)] were run for the 1979–2014 period within the NLDAS-based framework. Unlike the LSMs currently executing in the operational NLDAS, these three advanced LSMs each include a groundwater component. In this study, the model simulations of monthly terrestrial water storage anomaly (TWSA) and its individual water storage components are evaluated against satellite-based and in situ observations, as well as against reference reanalysis products, at basinwide and statewide scales. The quality of these TWSA simulations will contribute to determining the suitability of these models for the next phase of the NLDAS. Overall, it is found that all three models are able to reasonably capture the monthly and interannual variability and magnitudes of TWSA. However, the relative contributions of the individual water storage components to TWSA are very dependent on the model and basin. A major contributor to the TWSA is the anomaly of total column soil moisture content for CLM4.0 and Noah-MP, while the groundwater storage anomaly is the major contributor for CLSM-F2.5. Other water storage components such as the anomaly of snow water equivalent also play a role in all three models. For each individual water storage component, the models are able to capture broad features such as monthly and interannual variability. However, there are large intermodel differences and quantitative uncertainties, which are motivating follow-on investigations in the NLDAS Science Testbed developed by the NASA and NCEP NLDAS teams.

scholarly journals Global terrestrial water storage connectivity revealed using complex climate network analyses

2015 ◽  
Vol 22 (4) ◽  
pp. 433-446 ◽  
Author(s):  
A. Y. Sun ◽  
J. Chen ◽  
J. Donges
Keyword(s):  
Spatial Patterns ◽  
Land Surface ◽  
Water Storage ◽  
Data Sets ◽  
Terrestrial Water Storage ◽  
Land Surface Models ◽  
Data Set ◽  
Surface Models ◽  
Global Land ◽  
Terrestrial Water

Abstract. Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

Closing the water budget at the global scale using observations, remote sensing, and reanalyses

2021 ◽  
Author(s):  
Fanny Lehmann ◽  
Brahma Dutt Vishwakarma ◽  
Jonathan Bamber
Keyword(s):  
Land Surface ◽  
Water Budget ◽  
Water Storage ◽  
Global Scale ◽  
Terrestrial Water Storage ◽  
Land Surface Models ◽  
Cold Regions ◽  
Climate Zones ◽  
Surface Models ◽  
Terrestrial Water

<p>Despite the accuracy of GRACE terrestrial water storage estimates and the variety of global hydrological datasets providing precipitations, evapotranspiration, and runoff data, it remains challenging to find datasets satisfying the water budget equation at the global scale.</p><p>We select commonly used and widely-assessed datasets. We use several precipitations (CPC, CRU, GPCC, GPCP, GPM, MSWEP, TRMM, ERA5 Land, MERRA2), evapotranspiration (land surface models CLSM, Noah, VIC from GLDAS 2.0, 2.1, and 2.2; GLEAM, MOD16, SSEBop, ERA5 Land, MERRA2), and runoff (land surface models CLSM, Noah, VIC from GLDAS 2.0, 2.1, and 2.2; GRUN, ERA5 Land, MERRA2) datasets to assess the water storage change over more than 150 hydrological basins. Both mascons and spherical harmonics coefficients are used as the reference terrestrial water storage from different centres processing GRACE data. The analysis covers a wide range of climate zones over the globe and is conducted over 2003-2014.</p><p>The water budget closure is evaluated with Root Mean Square Deviation (RMSD), Nash-Sutcliffe Efficiency (NSE), and seasonal decomposition. Each dataset is assessed individually across all basins and dataset combinations are also ranked according to their performances. We obtain a total of 1080 combinations, among which several are suitable to close the water budget. Although none of the combinations performs consistently well over all basins, GPCP precipitations provide generally good results, together with GPCC and GPM. A better water budget closure is generally obtained when using evapotranspiration from Catchment Land Surface Models (GLDAS CLSM), while reanalyses ERA5 Land and MERRA2 are especially suitable in cold regions. Concerning runoff, the machine learning GRUN dataset performs remarkably well across climate zones, followed by ERA5 Land and MERRA2 in cold regions. We also highlight highly unrealistic values in evapotranspiration computed with version 2.2 of GLDAS (using data assimilation from GRACE) in most of the cold basins. Our results are robust as changing the GRACE product from one centre to the other does not affect our conclusions.</p>

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