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

Nigatu, Zemede M.; Fan, Dongming; You, Wei

doi:10.1016/j.asr.2020.12.042

Cited by 12 publications

(6 citation statements)

References 72 publications

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“…The NRB is the world's longest drainage basin, stretching over 6700 km and encompassing 11 nations (Figure 1) and over 400 million people. The basin is divided into four distinct regions based on the hydroclimatic conditions and previous studies [8]: the Blue Nile Region (BNR), the Lake Victoria Region (LVR), the Bahr-el-Ghazal Region (BER), and the Main Nile Region (MNR). The population of NRBs is expected to reach 700 million by 2030, prompting issues about fair resource usage [21] and the sustainable management of basin water resources.…”

Section: Methodology 21 Study Area Descriptionmentioning

confidence: 99%

See 1 more Smart Citation

Drought Dynamics in the Nile River Basin: Meteorological, Agricultural, and Groundwater Drought Propagation

Nigatu,

You,

Melesse

2024

Remote Sensing

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The Nile River Basin (NRB) has experienced a notable rise in drought episodes in recent decades. The propagation of meteorological, agricultural, and groundwater drought dynamics in the NRB was investigated in this study. The following drought indices examined the correlation and propagation among meteorological, agricultural, and groundwater droughts. These are the standardized precipitation evapotranspiration index (SPEI), soil moisture index, Gravity Recovery and Climate Experiment, and GRACE Follow-On (GRACE/GRACE-FO)-derived groundwater drought index (GGDI). These droughts were comprehensively evaluated in the NRB from 2003 to 2022. The cross-wavelet transform approach highlighted the links between droughts. The following are the key findings: (1) In the NRB, the cross-wavelet energy spectrum of wavelet coherence can indicate the internal connection between meteorological versus (vs.) agricultural and agricultural versus (vs.) groundwater drought. The time scale with the most significant correlation coefficient is the drought propagation time. (2) The El Niño–Southern Oscillation (ENSO) correlated with agricultural and groundwater drought much more than the Indian Ocean Dipole (IOD), demonstrating that ENSO has an important impact on drought advancement. (3) The R2 values were 0.68 for GGDI vs. standardized soil moisture index (SSI), 0.71 for Blue Nile Region (BNR) GGDI vs. SSI, and 0.55 for SSI vs. Standardized Precipitation Evapotranspiration Index (SPEI). Similarly, in the Lake Victoria Region (LVR), GGDI vs. SSI was 0.51 and SSI vs. SPEI was 0.55, but in the Bahr-el-Ghazal Region (BER), GGDI vs. SSI was 0.61 and SSI vs. SPEI was 0.27 during the whole research period with varied lag durations ranging from 1 to 6 months. Thus, the propagation of drought (i.e., meteorological, agricultural, and groundwater drought) dynamics has the potential to reshape our understanding of drought evolution, which could lead to early drought forecasting across the NRB and similar climatic regions.

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Section: Methodology 21 Study Area Descriptionmentioning

confidence: 99%

“…Ethiopia receives the most annual rainfall (RF) in the NRB [8], with 2292 mm/year, during its two rainy seasons. Egypt and Sudan have the greatest annual mean surface temperature (27)(28)(29)(30)(31) • C), while air temperatures vary both geographically and chronologically.…”

Section: Methodology 21 Study Area Descriptionmentioning

confidence: 99%

Drought Dynamics in the Nile River Basin: Meteorological, Agricultural, and Groundwater Drought Propagation

Nigatu,

You,

Melesse

2024

Remote Sensing

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“…Currently, the TC method has been used to estimate measurement errors of GRACE data [36]. Specifically, Khaki et al [37] and Nigatu et al [38] estimated the changes in key water-storage components by using the GRACE data and soil-moisture data based on the TC analysis method. Yin and Park [39] proposed a simple least-square merging approach using error characteristics quantified from the TC approach to estimate weight.…”

Section: Introductionmentioning

confidence: 99%

Improving the Accuracy of Groundwater Storage Estimates Based on Groundwater Weighted Fusion Model

Zheng

Yin

et al. 2022

Remote Sensing

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It is an effective measure to estimate groundwater storage anomalies (GWSA) by combining Gravity Recovery and Climate Experiment (GRACE) data and hydrological models. However, GWSA results based on a single hydrological model and GRACE data may have greater uncertainties, and it is difficult to verify in some regions where in situ groundwater-level measurements are limited. First, to solve this problem, a groundwater weighted fusion model (GWFM) is presented, based on the extended triple collocation (ETC) method. Second, the Shiyang River Basin (SYRB) is taken as an example, and in situ groundwater-level measurements are used to evaluate the performance of the GWFM. The comparison indicates that the correlation coefficient (CC) and Nash-Sutcliffe efficiency coefficient (NSE) are increased by 9–40% and 23–657%, respectively, relative to the original results. Moreover, the root mean squared error (RMSE) is reduced by 9–28%, which verifies the superiority of the GWFM. Third, the spatiotemporal distribution and influencing factors of GWSA in the Hexi Corridor (HC) are comprehensively analyzed during the period between 2003 and 2016. The results show that GWSA decline, with a trend of −2.37 ± 0.38 mm/yr from 2003 to 2010, and the downward trend after 2011 (−0.46 ± 1.35 mm/yr) slow down significantly compared to 2003–2010. The spatial distribution obtained by the GWFM is more reliable compared to the arithmetic average results, and GWFM-based GWSA fully retain the advantages of different models, especially in the southeastern part of the SYRB. Additionally, a simple index is used to evaluate the contributions of climatic factors and human factors to groundwater storage (GWS) in the HC and its different subregions. The index indicates that climate factors occupy a dominant position in the SLRB and SYRB, while human factors have a significant impact on GWS in the Heihe River Basin (HRB). This study can provide suggestions for the management and assessments of groundwater resources in some arid regions.

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“…An increasing number of studies have successfully applied GRACE to quantify variations in groundwater storage through space and time [22][23][24][25][26]. GRACE observations have been particularly useful for detecting variations in groundwater storage in semi-arid areas and to better understand the climate and human-driven factors that are responsible for this variation [18,[27][28][29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Assessing Changes in Terrestrial Water Storage Components over the Great Artesian Basin Using Satellite Observations

et al. 2021

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The influence of climate change and anthropogenic activities (e.g., water withdrawals) on groundwater basins has gained attention recently across the globe. However, the understanding of hydrological stores (e.g., groundwater storage) in one of the largest and deepest artesian basins, the Great Artesian Basin (GAB) is limited due to the poor distribution of groundwater monitoring bores. In this study, Gravity Recovery and Climate Experiment (GRACE) satellite and ancillary data from observations and models (soil moisture, rainfall, and evapotranspiration (ET)) were used to assess changes in terrestrial water storage and groundwater storage (GWS) variations across the GAB and its sub-basins (Carpentaria, Surat, Western Eromanga, and Central Eromanga). Results show that there is strong relationship of GWS variation with rainfall (r = 0.9) and ET (r = 0.9 to 1) in the Surat and some parts of the Carpentaria sub-basin in the GAB (2002–2017). Using multi-variate methods, we found that variation in GWS is primarily driven by rainfall in the Carpentaria sub-basin. While changes in rainfall account for much of the observed spatio-temporal distribution of water storage changes in Carpentaria and some parts of the Surat sub-basin (r = 0.90 at 0–2 months lag), the relationship of GWS with rainfall and ET in Central Eromanga sub-basin (r = 0.10–0.30 at more than 12 months lag) suggest the effects of human water extraction in the GAB.

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

Cited by 12 publications

References 72 publications

Drought Dynamics in the Nile River Basin: Meteorological, Agricultural, and Groundwater Drought Propagation

Drought Dynamics in the Nile River Basin: Meteorological, Agricultural, and Groundwater Drought Propagation

Improving the Accuracy of Groundwater Storage Estimates Based on Groundwater Weighted Fusion Model

Assessing Changes in Terrestrial Water Storage Components over the Great Artesian Basin Using Satellite Observations

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