GRACE-Derived Terrestrial Water Storage Changes in the Inter-Basin Region and Its Possible Influencing Factors: A Case Study of the Sichuan Basin, China

Yao, Chaolong; Luo, Zhicai; Wang, Haihong; Li, Qiong; Zhou, Hao

doi:10.3390/rs8060444

Cited by 27 publications

(12 citation statements)

References 66 publications

(55 reference statements)

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“…GRACE has provided, for the first time, observations on TWS variations from large river basin to continental scales (e.g., Syed et al, ). Nevertheless, a clear picture of the quantitative attribution of spatial TWS variation from hydroclimatic regimes, vegetation change, and human water use is still less well documented (Huang et al, ; Ndehedehe et al, ; Yao et al, ; Zhang, Wang, et al, ). For instance, several studies have analyzed GRACE‐derived TWS, precipitation, evapotranspiration, and runoff, but they only plotted these variables together lacking quantitative discussions (Syed et al, ; Yirdaw et al, ).…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Terrestrial Water Storage Changes Under the Grain for Green Program in the Yellow River Basin

et al. 2019

JGR Atmospheres

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Afforestation‐induced changes in water resources have attracted worldwide attention. However, a clear picture of quantitative attribution of terrestrial water storage (TWS) variation from hydroclimatic and anthropogenic factors is still lacking. In this study, a quantitative analysis of TWS variation was conducted in the Yellow River basin of China under the Grain for Green project with consideration of irrigation. The results showed that the TWS has decreased (increased) more and more quickly (slowly) in the Loess Plateau (headwater region). The TWS increase corresponded to increased runoff and soil moisture in the headwaters, and the TWS depletion corresponded to decreased runoff and groundwater in the Loess Plateau and downstream regions. Regarding the TWS change (TWSC), it exhibited a negative trend across the basin. The increase in evapotranspiration (ET) dominated the basin‐averaged TWSC reduction, while the increase in ET was highly related to the increases in vegetation cover and irrigation water use. For spatial TWSC variations, the value of precipitation minus ET could account for most changes in TWSC, except for those in the headwater region and a region near the internally drained area. The increased vegetation coverage, which can affect multiple hydrological processes, played an important role in these two excluded regions. Importantly, the irrigation‐induced TWSC was considerable and varied with different irrigation water sources (i.e., surface water and groundwater). Overall, the impacts of afforestation and irrigation on TWS are sufficiently important. The research in this study can provide guidance for the water resource management during revegetation efforts.

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Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Terrestrial Water Storage Changes Under the Grain for Green Program in the Yellow River Basin

et al. 2019

JGR Atmospheres

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“…responsible for the observed TWS variations [7,16,48,49], a cross-comparison was also implemented between GRACE-derived TWS, TRMM-derived precipitation and NCEP/NCAR-derived vertical velocity. As shown in Figure 11, the consistency between the non-seasonal values can also be seen during the 'universal' drought and flood events.…”

Section: Ncep/ncar Vertical Velocitymentioning

confidence: 99%

Characterizing Drought and Flood Events over the Yangtze River Basin Using the HUST-Grace2016 Solution and Ancillary Data

et al. 2017

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Accurate terrestrial water storage (TWS) estimation is important to evaluate the situation of the water resources over the Yangtze River Basin (YRB). This study exploits the TWS observation from the new temporal gravity field model, HUST-Grace2016 (Huazhong University of Science and Technology), which is developed by a new low-frequency noise processing strategy. A novel GRACE (Gravity Recovery and Climate Experiment) post-processing approach is proposed to enhance the quality of the TWS estimate, and the improved TWS is used to characterize the drought and flood events over the YRB. The HUST-Grace2016-derived TWS presents good agreement with the CSR (Center for Space Research) mascon solution as well as the PCR-GLOBWB (PCRaster Global Water Balance) hydrological model. Particularly, our solution provides remarkable performance in identifying the extreme climate events e.g., flood and drought over the YRB and its sub-basins. The comparison between GRACE-derived TWS variations and the MODIS-derived (Moderate Resolution Imaging Spectroradiometer) inundated area variations is then conducted. The analysis demonstrates that the terrestrial reflectance data can provide an alternative way of cross-comparing and validating TWS information in Poyang Lake and Dongting Lake, with a correlation coefficient of 0.77 and 0.70, respectively. In contrast, the correlation is only 0.10 for Tai Lake, indicating the limitation of cross-comparison between MODIS and GRACE data. In addition, for the first time, the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) vertical velocity data is incorporated with GRACE TWS in the exploration of the climate-induced hydrological activities. The good agreement between non-seasonal NCEP/NCAR vertical velocities and non-seasonal GRACE TWSs is found in flood years

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“…As for the drought events, the long-term negative anomalies are seen during the dry season in 2011, reflecting the severe drought event over the Poyang Lake basin. However, no drought event is observed over the Poyang Lake basin in 2006, when the upper Yangtze River basin suffers a severe drought [2,46].…”

Section: Comparison Between Forward-modeling Mascon Grids and Tellumentioning

confidence: 99%

Identifying Flood Events over the Poyang Lake Basin Using Multiple Satellite Remote Sensing Observations, Hydrological Models and In Situ Data

et al. 2018

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The Poyang Lake, the largest freshwater lake in China, is famous for its ecological and economic importance as well as frequent flood characteristics. In this study, multiple satellite remote sensing observations (e.g., GRACE, MODIS, Altimetry, and TRMM), hydrological models, and in situ data are used to characterize the flood phenomena over the Poyang Lake basin between 2003 and 2016. To improve the accuracy of the terrestrial water storage (TWS) estimates over the Poyang Lake basin, a modified forward-modeling method is introduced in the GRACE processing. The method is evaluated using the contaminated noise onboard observations for the first time. The results in both spectral and spatial domains infer a good performance of the method on the suppression of high-frequency noise while reducing the signal loss. After applying forward-modeling method, the TWS derived from the GRACE spherical harmonic coefficients presents a comparable performance with the solution derived from the newly released CSR Release05 mascon product over the Poyang Lake basin. The flood events in 2010 and 2016 are identified from the positive anomalies in non-seasonal TWSs derived by GRACE and hydrological models. The flood signatures also coincide with the largest inundated areas estimated from MODIS data, and the observed areas in 2010 and 2016 are 3370.3 km 2 (30% higher than the long-term mean) and 3445.0 km 2 (33% higher), respectively. The water levels in the Hukou station exceed the warning water level for 25 days in 2010 and 28 days in 2016. These continuous warning-exceeded water levels also imply the severe flood events, which are primarily driven by the local plenteous precipitation in the rainy season (1528 mm in 2010, 1522 mm in 2016).

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GRACE-Derived Terrestrial Water Storage Changes in the Inter-Basin Region and Its Possible Influencing Factors: A Case Study of the Sichuan Basin, China

Cited by 27 publications

References 66 publications

Quantitative Analysis of Terrestrial Water Storage Changes Under the Grain for Green Program in the Yellow River Basin

Quantitative Analysis of Terrestrial Water Storage Changes Under the Grain for Green Program in the Yellow River Basin

Characterizing Drought and Flood Events over the Yangtze River Basin Using the HUST-Grace2016 Solution and Ancillary Data

Identifying Flood Events over the Poyang Lake Basin Using Multiple Satellite Remote Sensing Observations, Hydrological Models and In Situ Data

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