Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events

The Xijiang River is a main branch of the Pearl River, the largest river in South China. Droughts in this area have seriously influenced local water resource utilization, and socio-economic development. The spatiotemporal distribution of droughts and its responses to global climatic events are of cr...

Full description

Bibliographic Details
Main Authors: Jizhong Qiu, Yunpeng Wang, Jie Xiao
Format: Article
Language:English
Published: MDPI AG 2017-04-01
Series:Water
Subjects:
Online Access:http://www.mdpi.com/2073-4441/9/4/265
id doaj-a65d0483bfe34051bb0d710f45e06a0a
record_format Article
spelling doaj-a65d0483bfe34051bb0d710f45e06a0a2020-11-24T22:25:17ZengMDPI AGWater2073-44412017-04-019426510.3390/w9040265w9040265Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic EventsJizhong Qiu0Yunpeng Wang1Jie Xiao2Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, ChinaGuangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, ChinaGuangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, ChinaThe Xijiang River is a main branch of the Pearl River, the largest river in South China. Droughts in this area have seriously influenced local water resource utilization, and socio-economic development. The spatiotemporal distribution of droughts and its responses to global climatic events are of critical significance for the assessment and early warning of drought disasters. In this paper, the spatiotemporal patterns of droughts characterized by Rotated Empirical Orthogonal Function/Rotated Principal Components (REOF/RPC) in the Xijiang River Basin, China were evaluated using the Self-calibrated Palmer Drought Severity Index (Sc-PDSI). The drought responses to El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), India Ocean Dipole (IOD), and North Atlantic Oscillation (NAO) were analysed by Pearson correlation and multiple stepwise regression. The results showed that one year earlier NAO was the dominant factor impacting the droughts in the Xijiang Basin. Its contribution for the RPC2s of the annual, the first and second half years, winter, summer, autumn, and February were −0.556, −0.419, 0.597, −0.447, 0.542, 0.600, and −0.327, respectively. Besides the two adjacent Pacific and India oceans, the droughts seem be influenced by distant Atlantic climatic events. These results offer new reference insights into the early warning of droughts as well as the planning and management of water resources in the study area.http://www.mdpi.com/2073-4441/9/4/265droughtglobal climatic eventsspatiotemporal distributionteleconnectioncontributionXijiang River Basin
collection DOAJ
language English
format Article
sources DOAJ
author Jizhong Qiu
Yunpeng Wang
Jie Xiao
spellingShingle Jizhong Qiu
Yunpeng Wang
Jie Xiao
Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events
Water
drought
global climatic events
spatiotemporal distribution
teleconnection
contribution
Xijiang River Basin
author_facet Jizhong Qiu
Yunpeng Wang
Jie Xiao
author_sort Jizhong Qiu
title Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events
title_short Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events
title_full Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events
title_fullStr Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events
title_full_unstemmed Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events
title_sort spatiotemporal distribution of droughts in the xijiang river basin, china and its responses to global climatic events
publisher MDPI AG
series Water
issn 2073-4441
publishDate 2017-04-01
description The Xijiang River is a main branch of the Pearl River, the largest river in South China. Droughts in this area have seriously influenced local water resource utilization, and socio-economic development. The spatiotemporal distribution of droughts and its responses to global climatic events are of critical significance for the assessment and early warning of drought disasters. In this paper, the spatiotemporal patterns of droughts characterized by Rotated Empirical Orthogonal Function/Rotated Principal Components (REOF/RPC) in the Xijiang River Basin, China were evaluated using the Self-calibrated Palmer Drought Severity Index (Sc-PDSI). The drought responses to El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), India Ocean Dipole (IOD), and North Atlantic Oscillation (NAO) were analysed by Pearson correlation and multiple stepwise regression. The results showed that one year earlier NAO was the dominant factor impacting the droughts in the Xijiang Basin. Its contribution for the RPC2s of the annual, the first and second half years, winter, summer, autumn, and February were −0.556, −0.419, 0.597, −0.447, 0.542, 0.600, and −0.327, respectively. Besides the two adjacent Pacific and India oceans, the droughts seem be influenced by distant Atlantic climatic events. These results offer new reference insights into the early warning of droughts as well as the planning and management of water resources in the study area.
topic drought
global climatic events
spatiotemporal distribution
teleconnection
contribution
Xijiang River Basin
url http://www.mdpi.com/2073-4441/9/4/265
work_keys_str_mv AT jizhongqiu spatiotemporaldistributionofdroughtsinthexijiangriverbasinchinaanditsresponsestoglobalclimaticevents
AT yunpengwang spatiotemporaldistributionofdroughtsinthexijiangriverbasinchinaanditsresponsestoglobalclimaticevents
AT jiexiao spatiotemporaldistributionofdroughtsinthexijiangriverbasinchinaanditsresponsestoglobalclimaticevents
_version_ 1725758406011125760