Tao Tingye, Dai Ju, Song Zichen, Li Shuiping, Qu Xiaochuan, Zhu Yongchao, Li Zhenxuan, Zhu Mingming
College of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
Sensors (Basel). 2024 Feb 12;24(4):1198. doi: 10.3390/s24041198.
The frequent occurrence of extreme climate events has a significant impact on people's lives. Heavy rainfall can lead to an increase of regional Terrestrial Water Storage (TWS), which will cause land subsidence due to the influence of hydrological load. At present, regional TWS is mostly obtained from Gravity Recovery and Climate Experiment (GRACE) data, but the method has limitations for small areas. This paper used water level and flow data as hydrological signals to study the land subsidence caused by heavy rainfall in the Chaohu Lake area of East China (June 2016-August 2016). Pearson's correlation coefficient was used to study the interconnection between water resource changes and Global Navigation Satellites System (GNSS) vertical displacement. Meanwhile, to address the reliability of the research results, combined with the Coefficient of determination method, the research findings were validated by using different institutional models. The results showed that: (1) During heavy rainfall, the vertical displacement caused by atmospheric load was larger than non-tidal oceanic load, and the influence trends of the two were opposite. (2) The rapidly increasing hydrologic load in the Chaohu Lake area resulted in greater subsidence displacement at the closer CORS station (CHCH station) than the more distant CORS station (LALA station). The Pearson correlation coefficients between the vertical displacement and water level were as high as -0.80 and -0.64, respectively. The phenomenon confirmed the elastic deformation principle of disc load. (3) Although there was a systematic bias between the different environmental load deformation models, the deformation trends were generally consistent with the GNSS monitoring results. The average Coefficients of determination between the different models and the GNSS results were 0.63 and 0.77, respectively. The results demonstrated the effectiveness of GNSS in monitoring short-term hydrological load. This study reveals the spatial-temporal evolution of land deformation during heavy rainfall around Chaohu Lake, which is of reference significance for water resource management and infrastructure maintenance in this area.
极端气候事件的频繁发生对人们的生活产生了重大影响。强降雨会导致区域陆地水储量(TWS)增加,受水文负荷影响,这将引发地面沉降。目前,区域TWS大多通过重力恢复与气候实验(GRACE)数据获取,但该方法在小区域存在局限性。本文利用水位和流量数据作为水文信号,研究了中国东部巢湖地区(2016年6月至2016年8月)强降雨引发的地面沉降。采用皮尔逊相关系数研究水资源变化与全球导航卫星系统(GNSS)垂直位移之间的相互联系。同时,为解决研究结果的可靠性问题,结合决定系数法,利用不同的机构模型对研究结果进行验证。结果表明:(1)强降雨期间,大气负荷引起的垂直位移大于非潮汐海洋负荷,且二者影响趋势相反。(2)巢湖地区迅速增加的水文负荷导致距离较近的连续运行参考站(CHCH站)的沉降位移大于距离较远的连续运行参考站(LALA站)。垂直位移与水位之间的皮尔逊相关系数分别高达-0.80和-0.64。该现象证实了圆盘荷载的弹性变形原理。(3)尽管不同环境负荷变形模型之间存在系统偏差,但变形趋势总体上与GNSS监测结果一致。不同模型与GNSS结果之间的平均决定系数分别为0.63和0.77。结果证明了GNSS在监测短期水文负荷方面的有效性。本研究揭示了巢湖周边强降雨期间地面变形的时空演变,对该地区的水资源管理和基础设施维护具有参考意义。