Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors

China is the largest agricultural country with the largest population and booming socio-economy, and hence, remarkably increasing water demand. In this sense, it is practically critical to obtain knowledge about spatiotemporal variations of the territorial water storage (TWS) and relevant driving fa...

Full description

Bibliographic Details
Published in:Sustainability
Main Authors: Qingzhong Huang, Qiang Zhang, Chong-Yu Xu, Qin Li, Peng Sun
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2019
Subjects:
Online Access:https://doi.org/10.3390/su11236646
id ftmdpi:oai:mdpi.com:/2071-1050/11/23/6646/
record_format openpolar
spelling ftmdpi:oai:mdpi.com:/2071-1050/11/23/6646/ 2023-08-20T04:08:27+02:00 Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors Qingzhong Huang Qiang Zhang Chong-Yu Xu Qin Li Peng Sun agris 2019-11-25 application/pdf https://doi.org/10.3390/su11236646 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/su11236646 https://creativecommons.org/licenses/by/4.0/ Sustainability; Volume 11; Issue 23; Pages: 6646 GRACE terrestrial water storage climate change correlation analysis Text 2019 ftmdpi https://doi.org/10.3390/su11236646 2023-07-31T22:49:40Z China is the largest agricultural country with the largest population and booming socio-economy, and hence, remarkably increasing water demand. In this sense, it is practically critical to obtain knowledge about spatiotemporal variations of the territorial water storage (TWS) and relevant driving factors. In this study, we attempted to investigate TWS changes in both space and time using the monthly GRACE (Gravity Recovery and Climate Experiment) data during 2003–2015. Impacts of four climate indices on TWS were explored, and these four climate indices are, respectively, El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific decadal oscillation (PDO). In addition, we also considered the impacts of precipitation changes on TWS. We found significant correlations between climatic variations and TWS changes across China. Meanwhile, the impacts of climate indices on TWS changes were shifting from one region to another across China with different time lags ranging from 0 to 12 months. ENSO, IOD and PDO exerted significant impacts on TWS over 80% of the regions across China, while NAO affected TWS changes over around 40% of the regions across China. Moreover, we also detected significant relations between TWS and precipitation changes within 9 out of the 10 largest river basins across China. These results highlight the management of TWS across China in a changing environment and also provide a theoretical ground for TWS management in other regions of the globe. Text North Atlantic North Atlantic oscillation MDPI Open Access Publishing Indian Pacific Sustainability 11 23 6646
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic GRACE
terrestrial water storage
climate change
correlation analysis
spellingShingle GRACE
terrestrial water storage
climate change
correlation analysis
Qingzhong Huang
Qiang Zhang
Chong-Yu Xu
Qin Li
Peng Sun
Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors
topic_facet GRACE
terrestrial water storage
climate change
correlation analysis
description China is the largest agricultural country with the largest population and booming socio-economy, and hence, remarkably increasing water demand. In this sense, it is practically critical to obtain knowledge about spatiotemporal variations of the territorial water storage (TWS) and relevant driving factors. In this study, we attempted to investigate TWS changes in both space and time using the monthly GRACE (Gravity Recovery and Climate Experiment) data during 2003–2015. Impacts of four climate indices on TWS were explored, and these four climate indices are, respectively, El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific decadal oscillation (PDO). In addition, we also considered the impacts of precipitation changes on TWS. We found significant correlations between climatic variations and TWS changes across China. Meanwhile, the impacts of climate indices on TWS changes were shifting from one region to another across China with different time lags ranging from 0 to 12 months. ENSO, IOD and PDO exerted significant impacts on TWS over 80% of the regions across China, while NAO affected TWS changes over around 40% of the regions across China. Moreover, we also detected significant relations between TWS and precipitation changes within 9 out of the 10 largest river basins across China. These results highlight the management of TWS across China in a changing environment and also provide a theoretical ground for TWS management in other regions of the globe.
format Text
author Qingzhong Huang
Qiang Zhang
Chong-Yu Xu
Qin Li
Peng Sun
author_facet Qingzhong Huang
Qiang Zhang
Chong-Yu Xu
Qin Li
Peng Sun
author_sort Qingzhong Huang
title Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors
title_short Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors
title_full Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors
title_fullStr Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors
title_full_unstemmed Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors
title_sort terrestrial water storage in china: spatiotemporal pattern and driving factors
publisher Multidisciplinary Digital Publishing Institute
publishDate 2019
url https://doi.org/10.3390/su11236646
op_coverage agris
geographic Indian
Pacific
geographic_facet Indian
Pacific
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_source Sustainability; Volume 11; Issue 23; Pages: 6646
op_relation https://dx.doi.org/10.3390/su11236646
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/su11236646
container_title Sustainability
container_volume 11
container_issue 23
container_start_page 6646
_version_ 1774720709436637184