水稻抽穗扬花期极端高温发生时空特征及热害风险区识别——以南充市为例

以2000—2018年南充市水稻抽穗扬花期（7—8月）气象站点逐日最高气温数据为基础，通过年距平法、累计距平法提取南充市极端高温发生的时间特征；计算包括市域范围内及周边地区17个站点的多年水稻高温热害累积指数，并借助ANUSPLIN软件进行插值以获得南充市极端高温发生的空间特征；最终结合水稻种植范围、人口数量分布数据以及高温热害风险性分析模型识别南充市各等级水稻高温热害风险区。结果表明： 2006年为研究时段极端高温发生最严重的年份，其次是2017年，极端高温发生日数较常年明显偏多。2010年为南充市气温变化的转折点，2010—2018年平均日最高气温明显高于2000—2010年，预计未来极端高温天气出现的频率和强度持续增大。蓬安县、营山县为遭受极端高温天气最频繁的两个县，其次是高坪区、南部县和西充县。水稻高温热害高风险区在高坪区、营山县分布最多，中风险区在各县均有较广泛分布，而低风险区则集中分布在南部县西北部、阆中市北部和营山县东北部的山地、丘陵。水稻高温热害风险区的识别能为人们更好地安排农业生产和政府更科学地进行城市规划与改造等提供参考依据。

Spatio-temporal characteristics of extremely high temperature occurrences on rice during heading-flowering stage and identification of high-temperature disaster areas: An example of Nanchong City

Daily maximum temperature data during the rice heading-flowering stage(July-August) were obtained from the meteorological station for the period between 2000-2018, and the high-temperature temporal characteristics in Nanchong City were extracted using an accumulative anomaly method. The multi-year cumulative damage index of rice from heat injury was calculated in 17 stations within or around the Nanchong City, and the spatial characteristics of extremely high temperatures in Nanchong City were obtained using the ANUSPLIN interpolation software. The grade of each high-temperature disaster that occurred in rice areas of Nanchong City was eventually identified by combining the rice planting range, population distribution, and high-temperature disaster analysis model. The results showed that the year 2006 exhibited the highest intensity of extremely high temperature occurrences, which was followed by 2017; further, the number of days with extremely high temperatures was clearly higher than that observed in a year on average. The year 2010 represented the turning point of temperature change in Nanchong City; this is because the average daily maximum temperature between 2010 and 2018 was significantly higher than in the period between 2000-2010. It could be expected that the frequency and intensity of extremely high temperature occurrences would continue to increase in the near future. Peng''an and Yingshan were the two counties that were most frequently affected by extremely high temperatures, which were followed by the Gaoping District, Nanbu County, and Xichong County. The areas with high risk of heat damage were mostly distributed in the Gaoping and Yingshan counties; the areas with intermediate risk were widely distributed in all the counties, while low-risk areas were mainly distributed in the hilly regions situated toward the northwest of Nanbu, north of Langzhong, and northeast of Yingshan. Identifying high-temperature disaster areas can provide scientific references to the government for achieving a more organized agricultural sector and transforming urban areas.