Quantifying Multi-hazards and Impacts Over Different Growth Periods of Maize: A Study Based on Index Construction

Dan Chen; Ying Guo; Rui Wang; Yunmeng Zhao; Kaiwei Li; Jiquan Zhang; Xingpeng Liu; Zhijun Tong; Chunli Zhao

doi:10.1007/s13753-023-00516-8

Volume 14 Issue 5

Nov. 2023

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Article Navigation > International Journal of Disaster Risk Science > 2023 > 14(5): 822-839

Dan Chen, Ying Guo, Rui Wang, Yunmeng Zhao, Kaiwei Li, Jiquan Zhang, Xingpeng Liu, Zhijun Tong, Chunli Zhao. Quantifying Multi-hazards and Impacts Over Different Growth Periods of Maize: A Study Based on Index Construction[J]. International Journal of Disaster Risk Science, 2023, 14(5): 822-839. doi: 10.1007/s13753-023-00516-8

Citation:

Dan Chen, Ying Guo, Rui Wang, Yunmeng Zhao, Kaiwei Li, Jiquan Zhang, Xingpeng Liu, Zhijun Tong, Chunli Zhao. Quantifying Multi-hazards and Impacts Over Different Growth Periods of Maize: A Study Based on Index Construction[J]. International Journal of Disaster Risk Science, 2023, 14(5): 822-839. doi: 10.1007/s13753-023-00516-8

Citation:

Dan Chen, Ying Guo, Rui Wang, Yunmeng Zhao, Kaiwei Li, Jiquan Zhang, Xingpeng Liu, Zhijun Tong, Chunli Zhao. Quantifying Multi-hazards and Impacts Over Different Growth Periods of Maize: A Study Based on Index Construction[J]. International Journal of Disaster Risk Science, 2023, 14(5): 822-839. doi: 10.1007/s13753-023-00516-8

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Quantifying Multi-hazards and Impacts Over Different Growth Periods of Maize: A Study Based on Index Construction

doi: 10.1007/s13753-023-00516-8

Dan Chen¹,
Ying Guo¹,
Rui Wang¹,
Yunmeng Zhao¹,
Kaiwei Li^1,2,3,4,
Jiquan Zhang^{1,2,3,4
,
,},
Xingpeng Liu^1,2,3,4,
Zhijun Tong^1,2,3,4,
Chunli Zhao⁵

1. School of Environment, Northeast Normal University, Changchun, 130024, China;
2. Jilin Province Science and Technology Innovation Center of Agro-Meteorological Disaster Risk Assessment and Prevention, Northeast Normal University, Changchun, 130024, China;
3. Key Laboratory for Vegetation Ecology, Ministry of Education, Changchun, 130024, China;
4. State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, Northeast Normal University, Changchun, 130024, China;
5. College of Forestry and Grassland, Jilin Agricultural University, Changchun, 130024, China

Funds:

This study was supported by the National K&D Program of China (2022YFD2300201), the National Natural Science Foundation of China (U21A2040), the Major Science and Technology Program of Jilin Province (YDZJ202303CGZH023), the National Natural Science Foundation of China (42077443), the Science and Technology Development Planning of Jilin Province (20210203153SF), the Key Scientific and Technology Research and Development Program of Jilin Province (20200403065SF), and the Construction Project of the Science and Technology Innovation Center (20210502008ZP).

Accepted Date: 2023-10-06

Available Online: 2023-11-23

Publish Date: 2023-10-31

Abstract

Abstract

Owing to the complexity and variability of global climate, the study of extreme events to ensure food security is particularly critical. The standardized precipitation requirement index (SPRI) and chilling injury index (I_Ci) were introduced using data from agrometeorological stations on the Songliao Plain between 1981 and 2020 to identify the spatial and temporal variability of drought, waterlogging, and low-temperature cold damage during various maize growth periods. Compound drought and low-temperature cold damage events (CDLEs) and compound waterlogging and low-temperature cold damage events (CWLEs) were then identified. To measure the intensity of compound events, the compound drought and low-temperature cold damage magnitude index (CDLMI), and compound waterlogging and low-temperature cold damage magnitude index (CWLMI) were constructed by fitting marginal distributions. Finally, the effects of extreme events of various intensities on maize output were examined. The findings demonstrate that: (1) There were significant differences in the temporal trends of the SPRI and I_Ci during different maize growth periods. Drought predominated in the middle growth period (MP), waterlogging predominated in the early growth period (EP) and late growth period (LP), and both drought and waterlogging tended to increase in intensity and frequency. The frequency of low-temperature cold damage showed a decreasing trend in all periods. (2) The CDLMI and CWLMI can effectively determine the intensity of CDLEs and CWLEs in the study area; these CDLEs and CWLEs had higher intensity and frequency in the late growth period. (3) Compared to single events, maize relative meteorological yield had a more significant negative correlation with the CDLMI and CWLMI.
- Compound events magnitude index,
- Drought,
- Growth periods,
- Low-temperature cold damage,
- Spatiotemporal distribution,
- Waterlogging

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References(48)

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