Multi-factor joint return period of rainstorms and its agricultural risk analysis in Liaoning Province, China
Open Access
- 1 January 2019
- journal article
- research article
- Published by Taylor & Francis in Geomatics, Natural Hazards and Risk
- Vol. 10 (1) , 1988-2008
Abstract
Rainstorms are one of the frequent natural disasters which have significant impact on agricultural production and people’s lives. Considering the comprehensive influence of various factors on the rainstorm events, this study extracts four elements of rainstorms in the Liaoning Province based on meteorological data collected between 1957 and 2015. Combined four elements of rainstorms by copula function, the cumulative probability of the rainstorm events and the probability of their return period can be analysed. The results show that the joint return period of multiple factors combination is less than the return period of a single factor. The degree of accuracy of the joint return period is higher, which is consistent with the actual situation. During periods of 5, 10, 20, and 50 years, the occurrence probability varies according to the idea ‘the central region is higher, while the eastern and western regions are lower’. Special attention must be paid to the low values of the region in future rainstorm disaster prevention and mitigation work. Based on return periods, the agricultural risk grade can be divided into 5 levels. In ascending order, they are level I (Fuxin, Shenyang, Tieling), II (Dalian, Jinzhou, Panjin, Liaoyang), III (Huludao, Fushun), IV (Chaoyang, Yingkou, Anshan, Benxi), and V (Dandong).Keywords
This publication has 22 references indexed in Scilit:
- Use of beta regression for statistical downscaling of precipitation in the Campbell River basin, British Columbia, CanadaJournal of Hydrology, 2016
- Precipitation trend analysis using discrete wavelet transform at the Langat River Basin, Selangor, MalaysiaStochastic Environmental Research and Risk Assessment, 2016
- Rainstorm flash flood risk assessment using genetic programming: a case study of risk zoning in BeijingNatural Hazards, 2016
- Analysis of extreme precipitation characteristics in low mountain areas based on three-dimensional copulas—taking Kuandian County as an exampleTheoretical and Applied Climatology, 2015
- Integrated flood risk assessment and zonation method: a case study in Huaihe River basin, ChinaNatural Hazards, 2015
- Exploration of copula function use in crop meteorological drought risk analysis: a case study of winter wheat in Beijing, ChinaNatural Hazards, 2015
- Categorical data in local maximum likelihood: theory and applications to productivity analysisJournal of Productivity Analysis, 2014
- Risk assessment of rainstorm and flood disasters in China between 2004 and 2009 based on gray fixed weight cluster analysisNatural Hazards, 2013
- Combined use of MODIS, AVHRR and radiosonde data for the estimation of spatiotemporal distribution of precipitable waterJournal of Geophysical Research: Atmospheres, 2008
- Distribution functions of copulas: a class of bivariate probability integral transformsStatistics & Probability Letters, 2001