湖北农业科学 ›› 2024, Vol. 63 ›› Issue (6): 12-21.doi: 10.14088/j.cnki.issn0439-8114.2024.06.003

• 资源·环境 • 上一篇    下一篇

基于GTWR模型的安徽省气候对水稻生产力影响的时空分布规律

曹浩然, 孟梅   

  1. 新疆农业大学公共管理学院(法学院),乌鲁木齐 830002
  • 收稿日期:2023-05-11 出版日期:2024-06-25 发布日期:2024-06-26
  • 通讯作者: 孟 梅,女,新疆乌鲁木齐人,教授,博士,主要从事区域经济、农村发展、土地资源可持续利用和资源环境经济,(电子信箱)785161662@qq.com。
  • 作者简介:曹浩然(2000-),女,安徽阜阳人,在读硕士研究生,主要从事耕地多功能利用与粮食安全研究,(电话)18734074180(电子信箱)3102366696@qq.com。
  • 基金资助:
    国家自然科学基金项目(71663052)

The temporal and spatial distribution of the influence of climate on rice productivity in Anhui Province based on GTWR model

CAO Hao-ran, MENG Mei   

  1. School of Public Administration(Faculty of Law), Xinjiang Agricultural University, Urumqi 830002, China
  • Received:2023-05-11 Published:2024-06-25 Online:2024-06-26

摘要: 以气温和降水量作为气候变化的2个因素,以安徽省为研究区域,基于2001—2020年气温、降水量及水稻产量数据,使用时空地理加权回归(GTWR)模型分析气温与降水量2个因素对水稻产量的作用机制。结果表明,2001—2020年,安徽省各市水稻年平均产量在时间上出现持续波动的现象,在空间上也存在特定的集聚现象;安徽省西北部地区气温、降水量与水稻产量呈正相关关系,其中蚌埠市正相关关系最为显著;在安徽省所有城市中,淮南市和六安市的水稻产量受气温和降水量影响最为明显,而淮北市水稻产量受气温和降水量的影响相对较小,说明该地区其他因素对水稻产量具有更深影响。

关键词: 温度, 降水量, 水稻产量, 时空地理加权回归(GTWR), 安徽省

Abstract: Taking temperature and precipitation as the two factors of climate change and Anhui Province as the study area, based on the data of temperature, precipitation and rice yield from 2001 to 2020, the mechanism of temperature and precipitation on rice yield was analyzed by geographically and temporally weighted regression(GTWR). The results showed that from 2001 to 2020, the rice yield of each city in Anhui Province showed a continuous fluctuation in time, and there were also specific agglomeration phenomena in space. The temperature and precipitation were positively correlated with rice yield in the northwest of Anhui Province, and the positive correlation was the most significant in Bengbu City. Among all the cities in Anhui Province, the rice yield in Huainan City and Lu’an City was the most significantly affected by temperature and precipitation, while the rice yield in Huaibei City was relatively less affected by temperature and precipitation, indicating that other factors in this region had a deeper impact on rice yield.

Key words: temperature, precipitation, rice yield, geographically and temporally weighted regression(GTWR), Anhui Province

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