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...
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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 |
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GRACE terrestrial water storage climate change correlation analysis |
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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 |
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Sustainability |
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11 |
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23 |
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6646 |
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