李夫鹏, 王正涛, 超能芳, 冯建迪, 张兵兵, 田坤俊, 韩亚坤. 利用Swarm星群探测亚马逊流域2015-2016年干旱事件[J]. 武汉大学学报 ( 信息科学版), 2020, 45(4): 595-603. DOI: 10.13203/j.whugis20180273
引用本文: 李夫鹏, 王正涛, 超能芳, 冯建迪, 张兵兵, 田坤俊, 韩亚坤. 利用Swarm星群探测亚马逊流域2015-2016年干旱事件[J]. 武汉大学学报 ( 信息科学版), 2020, 45(4): 595-603. DOI: 10.13203/j.whugis20180273
LI Fupeng, WANG Zhengtao, CHAO Nengfang, FENG Jiandi, ZHANG Bingbing, TIAN Kunjun, HAN Yakun. 2015-2016 Drought Event in the Amazon River Basin as Measured by Swarm Constellation[J]. Geomatics and Information Science of Wuhan University, 2020, 45(4): 595-603. DOI: 10.13203/j.whugis20180273
Citation: LI Fupeng, WANG Zhengtao, CHAO Nengfang, FENG Jiandi, ZHANG Bingbing, TIAN Kunjun, HAN Yakun. 2015-2016 Drought Event in the Amazon River Basin as Measured by Swarm Constellation[J]. Geomatics and Information Science of Wuhan University, 2020, 45(4): 595-603. DOI: 10.13203/j.whugis20180273

利用Swarm星群探测亚马逊流域2015-2016年干旱事件

2015-2016 Drought Event in the Amazon River Basin as Measured by Swarm Constellation

  • 摘要: 准确探测和预防干旱事件对人类社会和经济发展至关重要。重力场恢复和气候实验(Gravity Recovery and Climate Experiment,GRACE)卫星自发射以来被广泛用于探测包括陆地水储量变化在内的地球质量迁移情况,但两代GRACE卫星数据任务之间存在空白。Swarm卫星搭载了全球定位系统(Global Positioning System,GPS)接收机和加速度计等设备,可用于恢复地球时变重力场,具有填补两代GRACE卫星任务之间空白的潜力。基于此,首先采用2013-12—2016-12的Swarm时变重力场估计亚马逊流域的陆地水储量变化和2015-2016年干旱事件造成的陆地水储量不足;然后与GRACE卫星数据、3种水文模型和4个虚拟水文站数据估计的结果进行对比分析;最后采用降水和温度数据研究造成亚马逊流域干旱事件的原因。实验数据结果表明,Swarm同GRACE、水文模型和虚拟水文站估计的结果均符合较好;Swarm为探测陆地水储量变化和干旱事件提供了新的有效途径,具有替代GRACE卫星探测亚马逊流域极端干旱和洪水灾害的潜力,该结果对利用Swarm星群研究地球质量迁移有一定参考作用。

     

    Abstract: The Swarm satellite is equipped with the Global Positioning System (GPS) receiver and accelerometer, which can be used to restore Earth's temporal gravity field model. Firstly, the terrestrial water storage (TWS) variability and 2015—2016 drought induced TWS deficits in the Amazon basin are estimated from the Swarm time-variable gravity field model between December 2013 and December 2016. Then, the estimated results from Swarm data are compared to the results derived from Gravity Recovery and Climate Experiment (GRACE), three hydrological models (Global Land Data Assimilation System (GLDAS), Climate Predication Center (CPC), National Centers for Environmental Prediction (NCEP))and 4 virtual stations (AMZ_076, AMZ_152, AMZ_ 228 and AMZ_215). Finally, the precipitation and temperature data are employed to study the origination of the drought event in the Amazon basin. The results indicate that the TWS derived from Swarm, GRACE, hydrological models, and virtual stations are in high consistency in the space/time distribution; Swarm provided a new perspective in detecting TWS, which has a potential to substitute GRACE satellite in studying the extremely drought and flood in the Amazon basin. The results in this paper may provide a reference in understanding Earth's mass transformation by Swarm.

     

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