Drought Evolution Due to Climate Change and Links to Precipitation Intensity in the Haihe River Basin
Droughts often have a substantial impact on normal socio-economic activities and agricultural production. The Haihe River Basin, one of the primary food production areas in China, has become increasingly sensitive to alternating droughts and floods, and the sharp transitions between them, due to rap...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-11-01
|
Series: | Water |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4441/9/11/878 |
id |
doaj-eff954de21ad486c82ca5187a0982dde |
---|---|
record_format |
Article |
spelling |
doaj-eff954de21ad486c82ca5187a0982dde2020-11-24T21:48:27ZengMDPI AGWater2073-44412017-11-0191187810.3390/w9110878w9110878Drought Evolution Due to Climate Change and Links to Precipitation Intensity in the Haihe River BasinBin Liu0Zhihong Yan1Jinxia Sha2Su Li3State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaSchool of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056021, ChinaSchool of Earth Science and Engineering, Hebei University of Engineering, Handan 056021, ChinaSchool of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056021, ChinaDroughts often have a substantial impact on normal socio-economic activities and agricultural production. The Haihe River Basin, one of the primary food production areas in China, has become increasingly sensitive to alternating droughts and floods, and the sharp transitions between them, due to rapid economic development and population growth combined with climate change. In this study, we employ the self-organizing map (SOM) neural network method to perform a cluster analysis on 43 meteorological stations in the study area, dividing the basin into five sub-regions. Then daily precipitation data (1960–2015) are collected, and the number of continuous dry days is used as a drought index to investigate drought evolution trends. Lastly, the Pearson-III curve is used to analyze the first daily precipitation after different drought duration, and the relationships between precipitation intensity, drought duration, and interdecadal drought frequency are observed. The results demonstrate that under the climate warming of the Haihe River Basin, the frequency of droughts increases throughout the whole basin, while the droughts are of shorter duration, the probability of more intense first daily precipitation after droughts increases during the dry–wet transition. The research provides a useful reference for the planning and management of water resources in the Haihe River Basin.https://www.mdpi.com/2073-4441/9/11/878Haihe River Basindroughtprecipitation intensityclimate changePearson-III curve |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bin Liu Zhihong Yan Jinxia Sha Su Li |
spellingShingle |
Bin Liu Zhihong Yan Jinxia Sha Su Li Drought Evolution Due to Climate Change and Links to Precipitation Intensity in the Haihe River Basin Water Haihe River Basin drought precipitation intensity climate change Pearson-III curve |
author_facet |
Bin Liu Zhihong Yan Jinxia Sha Su Li |
author_sort |
Bin Liu |
title |
Drought Evolution Due to Climate Change and Links to Precipitation Intensity in the Haihe River Basin |
title_short |
Drought Evolution Due to Climate Change and Links to Precipitation Intensity in the Haihe River Basin |
title_full |
Drought Evolution Due to Climate Change and Links to Precipitation Intensity in the Haihe River Basin |
title_fullStr |
Drought Evolution Due to Climate Change and Links to Precipitation Intensity in the Haihe River Basin |
title_full_unstemmed |
Drought Evolution Due to Climate Change and Links to Precipitation Intensity in the Haihe River Basin |
title_sort |
drought evolution due to climate change and links to precipitation intensity in the haihe river basin |
publisher |
MDPI AG |
series |
Water |
issn |
2073-4441 |
publishDate |
2017-11-01 |
description |
Droughts often have a substantial impact on normal socio-economic activities and agricultural production. The Haihe River Basin, one of the primary food production areas in China, has become increasingly sensitive to alternating droughts and floods, and the sharp transitions between them, due to rapid economic development and population growth combined with climate change. In this study, we employ the self-organizing map (SOM) neural network method to perform a cluster analysis on 43 meteorological stations in the study area, dividing the basin into five sub-regions. Then daily precipitation data (1960–2015) are collected, and the number of continuous dry days is used as a drought index to investigate drought evolution trends. Lastly, the Pearson-III curve is used to analyze the first daily precipitation after different drought duration, and the relationships between precipitation intensity, drought duration, and interdecadal drought frequency are observed. The results demonstrate that under the climate warming of the Haihe River Basin, the frequency of droughts increases throughout the whole basin, while the droughts are of shorter duration, the probability of more intense first daily precipitation after droughts increases during the dry–wet transition. The research provides a useful reference for the planning and management of water resources in the Haihe River Basin. |
topic |
Haihe River Basin drought precipitation intensity climate change Pearson-III curve |
url |
https://www.mdpi.com/2073-4441/9/11/878 |
work_keys_str_mv |
AT binliu droughtevolutionduetoclimatechangeandlinkstoprecipitationintensityinthehaiheriverbasin AT zhihongyan droughtevolutionduetoclimatechangeandlinkstoprecipitationintensityinthehaiheriverbasin AT jinxiasha droughtevolutionduetoclimatechangeandlinkstoprecipitationintensityinthehaiheriverbasin AT suli droughtevolutionduetoclimatechangeandlinkstoprecipitationintensityinthehaiheriverbasin |
_version_ |
1725892020448264192 |