Journal metrics

Journal metrics

  • IF value: 2.281 IF 2.281
  • IF 5-year value: 2.693 IF 5-year 2.693
  • CiteScore value: 2.43 CiteScore 2.43
  • SNIP value: 1.193 SNIP 1.193
  • SJR value: 0.965 SJR 0.965
  • IPP value: 2.31 IPP 2.31
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 73 Scimago H index 73
Discussion papers | Copyright
https://doi.org/10.5194/nhess-2018-194
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 05 Sep 2018

Research article | 05 Sep 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Monthly and seasonal rainfall (1963–2017) for a typhoon-influenced area in a Chinese karst basin

Chongxun Mo1,2,3, Yuli Ruan1,2,3, Jiaqi He1,2,3, Guikai Sun1,2,3, and Juliang Jin4 Chongxun Mo et al.
  • 1College of architecture and civil engineering Guangxi University, Nanning, China
  • 2Key Laboratory of Disaster Prevention and structural Safety of Ministry of Education, Nanning, China
  • 3Guangxi Key Laboratories of Disaster Prevention and Engineering Safety, Nanning, China
  • 4School of Civil Engineering, Hefei University of Technology, Hefei 230009, China

Abstract. Under the dual influence of global warming and typhoon weather, the characteristics of monthly and seasonal rainfall become more complicated and extreme, leading to more frequent rainfall and flood disasters. The objective of this study is to propose a framework for analysing the characteristics of rainfall and its correlation with typhoons. The proposed framework consists of an analysis of inner-annual distribution, inter-annual variation as well as correlation between rainfall and typhoons. Especially, a DVM method is proposed to compute the rationality and reliability of the abrupt change time analysis. Finally, the proposed framework was successfully implemented using a 55-year time series (1963–2017) of rainfall data recorded by 12 rain gauges in Chengbi River Basin (South China).The results are as follows. (1) The relative variability of monthly rainfall is relatively large (above 30%), and the rainfall tends to be centralized, and is mainly concentrated in July. (2) The monthly average rainfall is relatively stable, the seasonal rainfall decreases in spring and summer, while increases in autumn and winter. The abrupt change occurred during 1980s–1990s.The main periods of rainfall in summer and winter are shorter than those in spring and autumn. (3) The typhoon-caused rain is the main factor affecting the summer and autumn rainfall while the number of typhoons has the least influence. It is suggested that the impact of typhoon should be taken into consideration in the modelling of spatial and temporal evolution of hazardous rainfall evens and their social hazard assessment for a typhoon-influenced area .Besides, preventive measures should be strengthened for flood and waterlogging disasters and that the reservoir should be operated at different FLWLs during different flood sub seasons in Chengbi River Basin.

Download & links
Chongxun Mo et al.
Interactive discussion
Status: open (until 31 Oct 2018)
Status: open (until 31 Oct 2018)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Chongxun Mo et al.
Chongxun Mo et al.
Viewed
Total article views: 97 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
82 14 1 97 1 0
  • HTML: 82
  • PDF: 14
  • XML: 1
  • Total: 97
  • BibTeX: 1
  • EndNote: 0
Views and downloads (calculated since 05 Sep 2018)
Cumulative views and downloads (calculated since 05 Sep 2018)
Viewed (geographical distribution)
Total article views: 97 (including HTML, PDF, and XML) Thereof 94 with geography defined and 3 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited
Saved
No saved metrics found.
Discussed
No discussed metrics found.
Latest update: 20 Sep 2018
Publications Copernicus
Download
Citation
Share