| Popis: |
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. |
