Regional Crustal Vertical Deformation Driven by Terrestrial Water Load Depending on CORS Network and Environmental Loading Data: A Case Study of Southeast Zhejiang

Monitoring regional terrestrial water load deformation is of great significance to the dynamic maintenance and hydrodynamic study of the regional benchmark framework. In view of the lack of a spatial interpolation method based on the GNSS (Global Navigation Satellite System) elevation time series fo...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Wanqiu Li, Jie Dong, Wei Wang, Hanjiang Wen, Huanling Liu, Qiuying Guo, Guobiao Yao, Chuanyin Zhang
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
Acceso en línea:https://doaj.org/article/ab081b313abf4ec68184960289d6dcdd
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:ab081b313abf4ec68184960289d6dcdd
record_format dspace
spelling oai:doaj.org-article:ab081b313abf4ec68184960289d6dcdd2021-11-25T18:58:33ZRegional Crustal Vertical Deformation Driven by Terrestrial Water Load Depending on CORS Network and Environmental Loading Data: A Case Study of Southeast Zhejiang10.3390/s212276991424-8220https://doaj.org/article/ab081b313abf4ec68184960289d6dcdd2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7699https://doaj.org/toc/1424-8220Monitoring regional terrestrial water load deformation is of great significance to the dynamic maintenance and hydrodynamic study of the regional benchmark framework. In view of the lack of a spatial interpolation method based on the GNSS (Global Navigation Satellite System) elevation time series for obtaining terrestrial water load deformation information, this paper proposes to employ a CORS (Continuously Operating Reference Stations) network combined with environmental loading data, such as ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric data, the GLDAS (Global Land Data Assimilation System) hydrological model, and MSLA (Mean Sea Level Anomaly) data. Based on the load deformation theory and spherical harmonic analysis method, we took 38 CORS stations in southeast Zhejiang province as an example and comprehensively determined the vertical deformation of the crust as caused by regional terrestrial water load changes from January 2015 to December 2017, and then compared these data with the GRACE (Gravity Recovery and Climate Experiment) satellite. The results show that the vertical deformation value of the terrestrial water load in southeast Zhejiang, as monitored by the CORS network, can reach a centimeter, and the amplitude changes from −1.8 cm to 2.4 cm. The seasonal change is obvious, and the spatial distribution takes a ladder form from inland to coastal regions. The surface vertical deformation caused by groundwater load changes in the east–west–south–north–central sub-regions show obvious fluctuations from 2015 to 2017, and the trends of the five sub-regions are consistent. The amplitude of surface vertical deformation caused by groundwater load change in the west is higher than that in the east. We tested the use of GRACE for the verification of CORS network monitoring results and found a relatively consistent temporal distribution between both data sets after phase delay correction on GRACE, except for in three months—November in 2015, and January and February in 2016. The results show that the comprehensive solution based on the CORS network can effectively improve the monitoring of crustal vertical deformation during regional terrestrial water load change.Wanqiu LiJie DongWei WangHanjiang WenHuanling LiuQiuying GuoGuobiao YaoChuanyin ZhangMDPI AGarticleCORS networkGRACEcomprehensive calculationcrustal vertical deformationterrestrial water loadChemical technologyTP1-1185ENSensors, Vol 21, Iss 7699, p 7699 (2021)
institution DOAJ
collection DOAJ
language EN
topic CORS network
GRACE
comprehensive calculation
crustal vertical deformation
terrestrial water load
Chemical technology
TP1-1185
spellingShingle CORS network
GRACE
comprehensive calculation
crustal vertical deformation
terrestrial water load
Chemical technology
TP1-1185
Wanqiu Li
Jie Dong
Wei Wang
Hanjiang Wen
Huanling Liu
Qiuying Guo
Guobiao Yao
Chuanyin Zhang
Regional Crustal Vertical Deformation Driven by Terrestrial Water Load Depending on CORS Network and Environmental Loading Data: A Case Study of Southeast Zhejiang
description Monitoring regional terrestrial water load deformation is of great significance to the dynamic maintenance and hydrodynamic study of the regional benchmark framework. In view of the lack of a spatial interpolation method based on the GNSS (Global Navigation Satellite System) elevation time series for obtaining terrestrial water load deformation information, this paper proposes to employ a CORS (Continuously Operating Reference Stations) network combined with environmental loading data, such as ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric data, the GLDAS (Global Land Data Assimilation System) hydrological model, and MSLA (Mean Sea Level Anomaly) data. Based on the load deformation theory and spherical harmonic analysis method, we took 38 CORS stations in southeast Zhejiang province as an example and comprehensively determined the vertical deformation of the crust as caused by regional terrestrial water load changes from January 2015 to December 2017, and then compared these data with the GRACE (Gravity Recovery and Climate Experiment) satellite. The results show that the vertical deformation value of the terrestrial water load in southeast Zhejiang, as monitored by the CORS network, can reach a centimeter, and the amplitude changes from −1.8 cm to 2.4 cm. The seasonal change is obvious, and the spatial distribution takes a ladder form from inland to coastal regions. The surface vertical deformation caused by groundwater load changes in the east–west–south–north–central sub-regions show obvious fluctuations from 2015 to 2017, and the trends of the five sub-regions are consistent. The amplitude of surface vertical deformation caused by groundwater load change in the west is higher than that in the east. We tested the use of GRACE for the verification of CORS network monitoring results and found a relatively consistent temporal distribution between both data sets after phase delay correction on GRACE, except for in three months—November in 2015, and January and February in 2016. The results show that the comprehensive solution based on the CORS network can effectively improve the monitoring of crustal vertical deformation during regional terrestrial water load change.
format article
author Wanqiu Li
Jie Dong
Wei Wang
Hanjiang Wen
Huanling Liu
Qiuying Guo
Guobiao Yao
Chuanyin Zhang
author_facet Wanqiu Li
Jie Dong
Wei Wang
Hanjiang Wen
Huanling Liu
Qiuying Guo
Guobiao Yao
Chuanyin Zhang
author_sort Wanqiu Li
title Regional Crustal Vertical Deformation Driven by Terrestrial Water Load Depending on CORS Network and Environmental Loading Data: A Case Study of Southeast Zhejiang
title_short Regional Crustal Vertical Deformation Driven by Terrestrial Water Load Depending on CORS Network and Environmental Loading Data: A Case Study of Southeast Zhejiang
title_full Regional Crustal Vertical Deformation Driven by Terrestrial Water Load Depending on CORS Network and Environmental Loading Data: A Case Study of Southeast Zhejiang
title_fullStr Regional Crustal Vertical Deformation Driven by Terrestrial Water Load Depending on CORS Network and Environmental Loading Data: A Case Study of Southeast Zhejiang
title_full_unstemmed Regional Crustal Vertical Deformation Driven by Terrestrial Water Load Depending on CORS Network and Environmental Loading Data: A Case Study of Southeast Zhejiang
title_sort regional crustal vertical deformation driven by terrestrial water load depending on cors network and environmental loading data: a case study of southeast zhejiang
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/ab081b313abf4ec68184960289d6dcdd
work_keys_str_mv AT wanqiuli regionalcrustalverticaldeformationdrivenbyterrestrialwaterloaddependingoncorsnetworkandenvironmentalloadingdataacasestudyofsoutheastzhejiang
AT jiedong regionalcrustalverticaldeformationdrivenbyterrestrialwaterloaddependingoncorsnetworkandenvironmentalloadingdataacasestudyofsoutheastzhejiang
AT weiwang regionalcrustalverticaldeformationdrivenbyterrestrialwaterloaddependingoncorsnetworkandenvironmentalloadingdataacasestudyofsoutheastzhejiang
AT hanjiangwen regionalcrustalverticaldeformationdrivenbyterrestrialwaterloaddependingoncorsnetworkandenvironmentalloadingdataacasestudyofsoutheastzhejiang
AT huanlingliu regionalcrustalverticaldeformationdrivenbyterrestrialwaterloaddependingoncorsnetworkandenvironmentalloadingdataacasestudyofsoutheastzhejiang
AT qiuyingguo regionalcrustalverticaldeformationdrivenbyterrestrialwaterloaddependingoncorsnetworkandenvironmentalloadingdataacasestudyofsoutheastzhejiang
AT guobiaoyao regionalcrustalverticaldeformationdrivenbyterrestrialwaterloaddependingoncorsnetworkandenvironmentalloadingdataacasestudyofsoutheastzhejiang
AT chuanyinzhang regionalcrustalverticaldeformationdrivenbyterrestrialwaterloaddependingoncorsnetworkandenvironmentalloadingdataacasestudyofsoutheastzhejiang
_version_ 1718410481308270592