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Tracking inter-annual terrestrial water storage variations over Lake Baikal basin from GRACE and GRACE Follow-On missions
The Gravity Recovery and Climate Experiment (GRACE) mission and its follow-on mission (GRACE Follow-On) can accurately track the Earth’s mass variations, which have been successfully used in various geoscience researches related to global and regional hydrological process. In this study, satellite gravimetry (GRACE and GRACR Follow-On) and hydrological model (GLDAS) are used to estimate the TWS variations over LBB in 2003–2020. As the world’s largest freshwater lake by volume, the terrestrial water storage (TWS) variations in Lake Baikal basin (LBB) significantly affect the surrounding ecological environment. However, the spatial scale of LBB is relatively small when compared to approximately 300 km spatial resolution of GRACE and GRACE Follow-On mission. Therefore, the forward modeling method is used to alleviate the leakage errors during satellite gravimetry data processing. To assess the performance of forward modeling method, a close-loop simulation study is designed in noise-contaminated condition. The simulation results demonstrate the feasibility of forward modeling method in accurately estimating TWS variations over LBB. After appropriate leakage correction, the inter-annual TWS from satellite gravimetry agrees well with GLDAS. The TWS variations over LBB demonstrate that (1) there are drastic variations and periodic characteristics around 4–5 years, and the drought events are observed in 2003, 2007, 2011 and 2015 as relatively smaller TWSs. (2) The soil moisture and groundwater are the major contributors to TWS variations (with the correlation coefficient of 0.88 and 0.89), and the surface water is the main contributor to the seasonal variations over LBB. (3) The TWS presents about 6 moths delay to precipitation variations, while the precipitation is still the major driver to affect the hydrological processes over this region.
Tracking inter-annual terrestrial water storage variations over Lake Baikal basin from GRACE and GRACE Follow-On missions
The Gravity Recovery and Climate Experiment (GRACE) mission and its follow-on mission (GRACE Follow-On) can accurately track the Earth’s mass variations, which have been successfully used in various geoscience researches related to global and regional hydrological process. In this study, satellite gravimetry (GRACE and GRACR Follow-On) and hydrological model (GLDAS) are used to estimate the TWS variations over LBB in 2003–2020. As the world’s largest freshwater lake by volume, the terrestrial water storage (TWS) variations in Lake Baikal basin (LBB) significantly affect the surrounding ecological environment. However, the spatial scale of LBB is relatively small when compared to approximately 300 km spatial resolution of GRACE and GRACE Follow-On mission. Therefore, the forward modeling method is used to alleviate the leakage errors during satellite gravimetry data processing. To assess the performance of forward modeling method, a close-loop simulation study is designed in noise-contaminated condition. The simulation results demonstrate the feasibility of forward modeling method in accurately estimating TWS variations over LBB. After appropriate leakage correction, the inter-annual TWS from satellite gravimetry agrees well with GLDAS. The TWS variations over LBB demonstrate that (1) there are drastic variations and periodic characteristics around 4–5 years, and the drought events are observed in 2003, 2007, 2011 and 2015 as relatively smaller TWSs. (2) The soil moisture and groundwater are the major contributors to TWS variations (with the correlation coefficient of 0.88 and 0.89), and the surface water is the main contributor to the seasonal variations over LBB. (3) The TWS presents about 6 moths delay to precipitation variations, while the precipitation is still the major driver to affect the hydrological processes over this region.
Tracking inter-annual terrestrial water storage variations over Lake Baikal basin from GRACE and GRACE Follow-On missions
Min Wei (Autor:in) / Hao Zhou (Autor:in) / Zhicai Luo (Autor:in) / Min Dai (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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