四川省水稻高温热害风险及灾损评估
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摘要
高温热害是四川省最主要的农业气象灾害之一,研究高温热害对水稻的影响对于四川省农业可持续发展、保障水稻的安全生产具有重要意义。本文以1981—2015年四川省84个气象台站的逐日气象资料、农业气象观测站水稻生育期资料和县级水稻产量资料为基础,利用水稻高温热害指数,构建四川省水稻关键生育期和全生育期综合高温热害风险模型;分离水稻气象产量,建立高温热害影响下水稻气象产量与高温热害指数间的统计模型,开展1981—2015年四川省水稻高温热害风险和灾损评估。研究结果表明:四川省水稻抽穗扬花期,高温热害较高风险区和高风险区主要集中在盆地东北大部和盆地南部的个别地区,其中达州、广安和泸州的部分地区为高风险区。而低风险区主要分布在盆地西部、南部和川西南的大部地区。灌浆结实期,水稻高温热害较高风险区和高风险区主要集中在盆地东北和盆地南部的大部分地区,其中泸州大部、南充和宜宾的个别地区为高风险区。而低风险区主要分布在盆地北部、西部和川西南的大部地区。水稻全生育阶段高温热害较高风险区和高风险区主要集中在盆地东北和盆地南部的大部分地区,其中泸州、南充和达州的部分地区为高风险区。而低风险区主要分布在盆地北部、西部和川西南的大部地区。构建的水稻高温热害灾损评估模型简单实用,验证结果表明高温热害年水稻统计产量与模拟产量间的相对误差绝对值都小于1.5%,建立的模型能反映四川省高温热害对水稻产量的影响,同时能够较好地评估高温热害下四川省水稻的产量损失。进一步的灾损评估结果表明,高温热害危害下代表站点水稻的减产率为5.6%～10.2%。
Under global climate change, agricultural meteorological disasters have been increasing. Heat stress has been one of the most important agrometeorological disasters in Sichuan Province, the affected area, frequency and intensity of heat stress have significantly changed. Therefore, research on the impact of heat stress on rice is critical for sustainable agricultural development and safe production in Sichuan Province. In this study, the following data were used to evaluate the risk of cultivation and yield loss of rice in Sichuan Province due to heat stress: 1) daily climate variables(average temperature, maximum temperature and relative humidity) from 84 meteorological stations in Sichuan Province for the period 1981–2015; 2) developmental stages(from heading to flowering, and from grain-filling to harvest) of rice in 84 agro-meteorological observation stations in Sichuan Province for the period1981–2015; 3) rice yields for the 84 stations in Sichuan Province during the period 1981–2015. The hazard index of heat stress at different rice developmental stages were calculated based on the Chinese National Standard, GB/T 21985—2008 Temperature Index of High Temperature Harm for Main Crops. The meteorological yield of rice was separated from actual yield. And then the risk evaluation model for rice in Sichuan Province due to heat stress was constructed by using rice hazard index for the critical development stages and the whole growth period, and rice yield loss due to heat stress was evaluated. The results showed the average hazard index of heat stress in the period 1981–2015 was highest(6.0) for grain-filling to harvest growth stage, medium(5.0) for the whole growth period and lowest(4.0) for heading to flowering growth stage in Sichuan Province. For the heading-flowering stage, most of the northeast basin and parts of the southern basin were under high or sub-high-risk of heat stress. Dazhou, Guang'an and Luzhou were under high-risk. The western basin, southern basin and southwest Sichuan were under low-risk. For the filling to harvest stage,most of the northeast basin and the southern basin were under high or sub-high-risk of heat stress. Luzhou, part of Nanchong and Yibin were high-risk areas. Most of the western basin, northern basin and southwest Sichuan were low-risk areas. For the whole growth period, most of the northeast basin and southern basin were under high or sub-high-risk. Luzhou, Nanchong and Dazhou were high-risk areas. Most of the western basin, northern basin and southwest Sichuan were low-risk areas. The statistical model for rice yield loss due to heat stress was simple and practicable. Using Yanjiang, Yingshan, Longchang, Yanting and Dazhu as the case study,the differences in historical statistical yields and simulated yields of rice for the years of heat stress were analyzed. The relative error between the statistical yield and the simulated yield of rice affected by heat stress was less than 1.5%. The verification results showed that the model was synthetically reflective of the impact of heat stress on rice yield and that it highly accurately evaluated rice yield loss. The assessment showed that the range of yield loss of rice in typical areas of Sichuan due to heat stress was 5.6%–10.2%.
Under global climate change, agricultural meteorological disasters have been increasing. Heat stress has been one of the most important agrometeorological disasters in Sichuan Province, the affected area, frequency and intensity of heat stress have significantly changed. Therefore, research on the impact of heat stress on rice is critical for sustainable agricultural development and safe production in Sichuan Province. In this study, the following data were used to evaluate the risk of cultivation and yield loss of rice in Sichuan Province due to heat stress: 1) daily climate variables(average temperature, maximum temperature and relative humidity) from 84 meteorological stations in Sichuan Province for the period 1981–2015; 2) developmental stages(from heading to flowering, and from grain-filling to harvest) of rice in 84 agro-meteorological observation stations in Sichuan Province for the period1981–2015; 3) rice yields for the 84 stations in Sichuan Province during the period 1981–2015. The hazard index of heat stress at different rice developmental stages were calculated based on the Chinese National Standard, GB/T 21985—2008 Temperature Index of High Temperature Harm for Main Crops. The meteorological yield of rice was separated from actual yield. And then the risk evaluation model for rice in Sichuan Province due to heat stress was constructed by using rice hazard index for the critical development stages and the whole growth period, and rice yield loss due to heat stress was evaluated. The results showed the average hazard index of heat stress in the period 1981–2015 was highest(6.0) for grain-filling to harvest growth stage, medium(5.0) for the whole growth period and lowest(4.0) for heading to flowering growth stage in Sichuan Province. For the heading-flowering stage, most of the northeast basin and parts of the southern basin were under high or sub-high-risk of heat stress. Dazhou, Guang'an and Luzhou were under high-risk. The western basin, southern basin and southwest Sichuan were under low-risk. For the filling to harvest stage,most of the northeast basin and the southern basin were under high or sub-high-risk of heat stress. Luzhou, part of Nanchong and Yibin were high-risk areas. Most of the western basin, northern basin and southwest Sichuan were low-risk areas. For the whole growth period, most of the northeast basin and southern basin were under high or sub-high-risk. Luzhou, Nanchong and Dazhou were high-risk areas. Most of the western basin, northern basin and southwest Sichuan were low-risk areas. The statistical model for rice yield loss due to heat stress was simple and practicable. Using Yanjiang, Yingshan, Longchang, Yanting and Dazhu as the case study,the differences in historical statistical yields and simulated yields of rice for the years of heat stress were analyzed. The relative error between the statistical yield and the simulated yield of rice affected by heat stress was less than 1.5%. The verification results showed that the model was synthetically reflective of the impact of heat stress on rice yield and that it highly accurately evaluated rice yield loss. The assessment showed that the range of yield loss of rice in typical areas of Sichuan due to heat stress was 5.6%–10.2%.
引文
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[9]WU H,HUBBARD K G,WILHITE D A.An agricultural drought risk-assessment model for corn and soybeans[J].International Journal of Climatology,2004,24(6):723-741
[10]姚凤梅,张佳华.1981-2000年水稻生长季相对极端高温事件及其气候风险的变化[J].自然灾害学报,2009,18(4):37-42YAO F M,ZHANG J H.Change of relative extreme high temperature events and climate risk in rice growing period in China from 1981 to 2000[J].Journal of Natural Disasters,2009,18(4):37-42
[11]谢志清,杜银,高苹,等.江淮流域水稻高温热害灾损变化及应对策略[J].气象,2013,39(6):774-781XIE Z Q,DU Y,GAO P,et al.Impact of high-temperature on single cropping rice over Yangtze-Huaihe River valley and response measures[J].Meteorological Monthly,2013,39(6):774-781
[12]霍治国,李世奎,王素艳,等.主要农业气象灾害风险评估技术及其应用研究[J].自然资源学报,2003,l8(6):692-703HUO Z G,LI S K,WANG S Y,et al.Study on the risk evaluation technologies of main agrometeorological disasters and their application[J].Journal of Natural Resources,2003,18(6):692-703
[13]ZHANG D,WANG G L,ZHOU H C.Assessment on agricultural drought risk based on variable fuzzy sets model[J].Chinese Geographical Science,2011,21(2):167-175
[14]ZOU Q,ZHOU J Z,ZHOU C,et al.Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP[J].Stochastic Environmental Research and Risk Assessment,2013,27(2):525-546
[15]黄崇福.自然灾害风险分析与管理[M].北京:科学出版社,2012HUANG C F.Risk Analysis and Management of Natural Disasters[M].Beijing:Science Press,2012
[16]杨平,张丽娟,赵艳霞,等.黄淮海地区夏玉米干旱风险评估与区划[J].中国生态农业学报,2015,23(1):110-118YANG P,ZHANG L J,ZHAO Y X,et al.Risk assessment and zoning of drought for summer maize in the Huang-Huai-Hai Region[J].Chinese Journal of Eco-Agriculture,2015,23(1):110-118
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[18]HAN L Y,ZHANG Q,MA P L,et al.The spatial distribution characteristics of a comprehensive drought risk index in southwestern China and underlying causes[J].Theoretical and Applied Climatology,2016,124(3/4):517-528
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