Characterizing Droughts During the Rice Growth Period in Northeast China Based on Daily SPEI Under Climate Change

In agricultural production, droughts occurring during the crucial growth periods of crops hinder crop development, while the daily-scale standardized precipitation evapotranspiration index (<i>SPEI</i>) can be applied to accurately identify the drought characteristics. In this study, we used the statistical downscaling method to obtain the daily precipitation (<i>P<sub>r</sub></i>), maximum air temperature (<i>T<sub>max</sub></i>) and minimum air temperature (<i>T<sub>min</sub></i>) during the rice growing season in Heilongjiang Province from 2015 to 2100 under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 in CMIP6, to study the spatial and temporal characteristics of drought during the rice growing season in cold region and the effect of climate change on drought characteristics. The potential evapotranspiration (<i>PET<sub>0</sub></i>) was calculated using the regression correction method of the Hargreaves formula recommended by the FAO, and the daily <i>SPEI</i> was calculated to quantitatively identify the drought classification. The Pearson correlation coefficient was used to analyze the correlation between the meteorological factors (<i>P<sub>r</sub></i>, <i>T<sub>max</sub></i>, <i>T<sub>min</sub></i>), <i>PET<sub>0</sub></i> and <i>SPEI</i>. The results showed that: (1) Under 3 SSP scenarios, <i>P<sub>r</sub></i> showed an increasing trend from the northwest to the southeast, <i>T<sub>max</sub></i> showed an increasing trend from the northeast to the southwest, and higher <i>T<sub>min</sub></i> was mainly distributed in the east and west regions. (2) <i>PET<sub>0</sub></i> indicated an overall interannual rise in the three future SSP scenarios, with higher values mainly distributed in the central and western regions. The mean daily <i>PET<sub>0</sub></i> values ranged from 4.8 to 6.0 mm/d. (3) Under SSP1-2.6, rice mainly experienced mild drought and moderate drought (-0.5 ≥ <i>SPEI</i> > -1.5). The predominant drought classifications experienced were mild, moderate, and severe drought under SSP2-4.5 and SSP8.5 (-0.5 ≥ <i>SPEI</i> > -2.0). (4) The tillering stage experienced the highest drought frequency and drought intensity, with the longest drought lasting 24 days. However, the heading flower stage had the lowest drought frequency and drought intensity. The drought barycenter was mainly in Tieli and Suihua. (5) The <i>PET<sub>0</sub></i> was most affected by the <i>T<sub>max</sub></i>, while the <i>SPEI</i> was most affected by the <i>P<sub>r</sub></i>. This study offers a scientific and rational foundation for understanding the drought sensitivity of rice in Northeast China, as well as a rationale for the optimal scheduling of water resources in agriculture in the future.

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Journal
Plants
Published
2024-12-25
DOI
https://doi.org/10.3390/plants14010030
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1
Primary Topic
Hydrology and Drought Analysis
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article

Characterizing Droughts During the Rice Growth Period in Northeast China Based on Daily SPEI Under Climate Change

Zhongyi Sun, Tangzhe Nie, Peng Chen, Tianyi Wang et al.
1 citations
Plants
Hydrology and Drought Analysis
0.28
article

Characterizing Droughts During the Rice Growth Period in Northeast China Based on Daily SPEI Under Climate Change

Zhongyi Sun, Tangzhe Nie, Peng Chen, Tianyi Wang, Xiu Liu, Shuai Yin, Chong Du, Tiecheng Li, Lili Jiang
article en
1 citations

Abstract

In agricultural production, droughts occurring during the crucial growth periods of crops hinder crop development, while the daily-scale standardized precipitation evapotranspiration index (<i>SPEI</i>) can be applied to accurately identify the drought characteristics. In this study, we used the statistical downscaling method to obtain the daily precipitation (<i>P<sub>r</sub></i>), maximum air temperature (<i>T<sub>max</sub></i>) and minimum air temperature (<i>T<sub>min</sub></i>) during the rice growing season in Heilongjiang Province from 2015 to 2100 under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 in CMIP6, to study the spatial and temporal characteristics of drought during the rice growing season in cold region and the effect of climate change on drought characteristics. The potential evapotranspiration (<i>PET<sub>0</sub></i>) was calculated using the regression correction method of the Hargreaves formula recommended by the FAO, and the daily <i>SPEI</i> was calculated to quantitatively identify the drought classification. The Pearson correlation coefficient was used to analyze the correlation between the meteorological factors (<i>P<sub>r</sub></i>, <i>T<sub>max</sub></i>, <i>T<sub>min</sub></i>), <i>PET<sub>0</sub></i> and <i>SPEI</i>. The results showed that: (1) Under 3 SSP scenarios, <i>P<sub>r</sub></i> showed an increasing trend from the northwest to the southeast, <i>T<sub>max</sub></i> showed an increasing trend from the northeast to the southwest, and higher <i>T<sub>min</sub></i> was mainly distributed in the east and west regions. (2) <i>PET<sub>0</sub></i> indicated an overall interannual rise in the three future SSP scenarios, with higher values mainly distributed in the central and western regions. The mean daily <i>PET<sub>0</sub></i> values ranged from 4.8 to 6.0 mm/d. (3) Under SSP1-2.6, rice mainly experienced mild drought and moderate drought (-0.5 ≥ <i>SPEI</i> > -1.5). The predominant drought classifications experienced were mild, moderate, and severe drought under SSP2-4.5 and SSP8.5 (-0.5 ≥ <i>SPEI</i> > -2.0). (4) The tillering stage experienced the highest drought frequency and drought intensity, with the longest drought lasting 24 days. However, the heading flower stage had the lowest drought frequency and drought intensity. The drought barycenter was mainly in Tieli and Suihua. (5) The <i>PET<sub>0</sub></i> was most affected by the <i>T<sub>max</sub></i>, while the <i>SPEI</i> was most affected by the <i>P<sub>r</sub></i>. This study offers a scientific and rational foundation for understanding the drought sensitivity of rice in Northeast China, as well as a rationale for the optimal scheduling of water resources in agriculture in the future.

PlantsVol. 14(1)
Hohai University (CN), Northeast Agricultural University (CN), Chinese Academy of Sciences (CN), Hainan University (CN), Aerospace Information Research Institute (CN), Institute of Geographic Sciences and Natural Resources Research (CN), State Key Laboratory of Remote Sensing Science (CN), Heilongjiang University (CN)
National Natural Science Foundation of China, Ministry of Agriculture and Rural Affairs of the People's Republic of China
Climate action
Openalex Percentile: Top 39%
Hydrology and Drought Analysis
0.28
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