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Twenty-Year Spatiotemporal Variations of TWS over Mainland China Observed by GRACE and GRACE Follow-On Satellites
by
Chen, Wei
, Shum, C. K.
, Liang, Lei
, Li, Wenhao
, Yang, Zihan
, Li, Quanguo
, Zhong, Min
, Xiong, Yuhao
in
Agricultural production
/ Agriculture
/ Algorithms
/ Anomalies
/ China
/ Climate change
/ Continuity (mathematics)
/ Correlation coefficient
/ Correlation coefficients
/ Data assimilation
/ Data collection
/ Datasets
/ Depletion
/ Drought
/ Drought conditions
/ Droughts
/ El Nino
/ El Nino events
/ El Nino phenomena
/ GRACE (experiment)
/ GRACE/GRACE-FO
/ Gravity data
/ Groundwater
/ Groundwater storage
/ Hydrologic cycle
/ Hydrological cycle
/ Hydrology
/ La Nina
/ La Nina events
/ Machine learning
/ Management
/ Missing data
/ Precipitation
/ Principal components analysis
/ Resource management
/ River basins
/ Rivers
/ Satellites
/ Soil moisture
/ soil moisture water storage (SMS)
/ Soil water storage
/ Spectrum analysis
/ SSA-PCA
/ Surface water
/ terrestrial water storage (TWS)
/ Variation
/ Water
/ Water resources
/ Water resources management
/ Water storage
2023
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Twenty-Year Spatiotemporal Variations of TWS over Mainland China Observed by GRACE and GRACE Follow-On Satellites
by
Chen, Wei
, Shum, C. K.
, Liang, Lei
, Li, Wenhao
, Yang, Zihan
, Li, Quanguo
, Zhong, Min
, Xiong, Yuhao
in
Agricultural production
/ Agriculture
/ Algorithms
/ Anomalies
/ China
/ Climate change
/ Continuity (mathematics)
/ Correlation coefficient
/ Correlation coefficients
/ Data assimilation
/ Data collection
/ Datasets
/ Depletion
/ Drought
/ Drought conditions
/ Droughts
/ El Nino
/ El Nino events
/ El Nino phenomena
/ GRACE (experiment)
/ GRACE/GRACE-FO
/ Gravity data
/ Groundwater
/ Groundwater storage
/ Hydrologic cycle
/ Hydrological cycle
/ Hydrology
/ La Nina
/ La Nina events
/ Machine learning
/ Management
/ Missing data
/ Precipitation
/ Principal components analysis
/ Resource management
/ River basins
/ Rivers
/ Satellites
/ Soil moisture
/ soil moisture water storage (SMS)
/ Soil water storage
/ Spectrum analysis
/ SSA-PCA
/ Surface water
/ terrestrial water storage (TWS)
/ Variation
/ Water
/ Water resources
/ Water resources management
/ Water storage
2023
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Twenty-Year Spatiotemporal Variations of TWS over Mainland China Observed by GRACE and GRACE Follow-On Satellites
by
Chen, Wei
, Shum, C. K.
, Liang, Lei
, Li, Wenhao
, Yang, Zihan
, Li, Quanguo
, Zhong, Min
, Xiong, Yuhao
in
Agricultural production
/ Agriculture
/ Algorithms
/ Anomalies
/ China
/ Climate change
/ Continuity (mathematics)
/ Correlation coefficient
/ Correlation coefficients
/ Data assimilation
/ Data collection
/ Datasets
/ Depletion
/ Drought
/ Drought conditions
/ Droughts
/ El Nino
/ El Nino events
/ El Nino phenomena
/ GRACE (experiment)
/ GRACE/GRACE-FO
/ Gravity data
/ Groundwater
/ Groundwater storage
/ Hydrologic cycle
/ Hydrological cycle
/ Hydrology
/ La Nina
/ La Nina events
/ Machine learning
/ Management
/ Missing data
/ Precipitation
/ Principal components analysis
/ Resource management
/ River basins
/ Rivers
/ Satellites
/ Soil moisture
/ soil moisture water storage (SMS)
/ Soil water storage
/ Spectrum analysis
/ SSA-PCA
/ Surface water
/ terrestrial water storage (TWS)
/ Variation
/ Water
/ Water resources
/ Water resources management
/ Water storage
2023
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Twenty-Year Spatiotemporal Variations of TWS over Mainland China Observed by GRACE and GRACE Follow-On Satellites
Journal Article
Twenty-Year Spatiotemporal Variations of TWS over Mainland China Observed by GRACE and GRACE Follow-On Satellites
2023
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Overview
Terrestrial water storage (TWS) is a pivotal component of the global water cycle, profoundly impacting water resource management, hazard monitoring, and agriculture production. The Gravity Recovery and Climate Experiment (GRACE) and its successor, the GRACE Follow-On (GFO), have furnished comprehensive monthly TWS data since April 2002. However, there are 35 months of missing data over the entire GRACE/GFO observational period. To address this gap, we developed an operational approach utilizing singular spectrum analysis and principal component analysis (SSA-PCA) to fill these missing data over mainland China. The algorithm was demonstrated with good performance in the Southwestern River Basin (SWB, correlation coefficient, CC: 0.71, RMSE: 6.27 cm), Yangtze River Basin (YTB, CC: 0.67, RMSE: 3.52 cm), and Songhua River Basin (SRB, CC: 0.66, RMSE: 7.63 cm). Leveraging two decades of continuous time-variable gravity data, we investigated the spatiotemporal variations in TWS across ten major Chinese basins. According to the results of GRACE/GFO, mainland China experienced an average annual TWS decline of 0.32 ± 0.06 cm, with the groundwater storage (GWS) decreasing by 0.54 ± 0.10 cm/yr. The most significant GWS depletion occurred in the Haihe River Basin (HRB) at −2.07 ± 0.10 cm/yr, significantly substantial (~1 cm/yr) depletions occurred in the Yellow River Basin (YRB), SRB, Huaihe River Basin (HHB), Liao-Luan River Basin (LRB), and Southwest River Basin (SWB), and moderate losses were recorded in the Northwest Basin (NWB, −0.34 ± 0.03 cm/yr) and Southeast River Basin (SEB, −0.24 ± 0.10 cm/yr). Furthermore, we identified that interannual TWS variations in ten basins of China were primarily driven by soil moisture water storage (SMS) anomalies, exhibiting consistently and relatively high correlations (CC > 0.60) and low root-mean-square errors (RMSE < 5 cm). Lastly, through the integration of GRACE/GFO and Global Land Data Assimilation System (GLDAS) data, we unraveled the contrasting water storage patterns between northern and southern China. Southern China experienced drought conditions, while northern China faced flooding during the 2020–2023 La Niña event, with the inverse pattern observed during the 2014–2016 El Niño event. This study fills in the missing data and quantifies water storage variations within mainland China, contributing to a deeper insight into climate change and its consequences on water resource management.
Publisher
MDPI AG
Subject
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