[1]陈艾琳,戴晓爱*,张诗琪,等.2007—2016年四川省土壤干旱时空动态分析[J].山地学报,2020,(1):31-41.[doi:10.16089/j.cnki.1008-2786.000488]
　CHEN Ailin,DAI Xiaoai*,ZHANG Shiqi,et al.Spatiotemporal Dynamic Analysis of Soil Drought from 2007 to 2016 in Sichuan Province[J].Mountain Research,2020,(1):31-41.[doi:10.16089/j.cnki.1008-2786.000488]
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2007—2016年四川省土壤干旱时空动态分析()
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2020年第1期
页码:
31-41
栏目:
山地环境
出版日期:
2020-02-01

文章信息/Info

Title:
Spatiotemporal Dynamic Analysis of Soil Drought from 2007 to 2016 in Sichuan Province
文章编号:
1008-2786-(2020)1-031-11
作者:
陈艾琳1; 戴晓爱1*; 张诗琪1; 周 旋2
1.成都理工大学 地球科学学院,成都 610059; 2.电子科技大学 信息与软件工程学院,成都 610054
Author(s):
CHEN Ailin1;  DAI Xiaoai1*; ZHANG Shiqi1;  ZHOU Xuan2
1. School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China; 2. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
关键词:
四川省;  干旱;  温度植被干旱指数(TVDI);  标准化降雨指数(SPI);  GIS
Keywords:
Sichuan province;  Temperature Vegetation Dryness Index(TVDI);  Standardized Precipitation Index(SPI);  GIS
分类号:
P237
DOI:
10.16089/j.cnki.1008-2786.000488
文献标志码:
A
摘要:
四川作为农业大省,旱灾是导致农业减产最主要的因素。通过遥感和GIS手段进行四川省土壤干旱程度的时空分析,提高干旱的空间可视化程度,加强干旱监测的时效性尤为重要。本研究基于四川省2007—2016年逐季度的MODIS数据和1961—2011 年40个气象站的月降水资料,采用温度植被干旱指数(TVDI)计算得到四川省干旱等级分布情况,辅以标准化降雨指数(SPI)进行相关性分析,并通过线性回归、反距离权重空间插值、GIS空间分析模型重建等方法,分析近十年来四川省地区以季度为时间尺度的土壤干旱时空变化特征,制作各时相土壤干旱分布图展示其微变化。结果表明:(1)在月时间尺度上, SPI-1与TVDI呈中等至强负相关关系,即TVDI值越小,SPI 值越大,干旱程度越轻; 验证结果表明TVDI 都能够较好地对四川省的干旱空间分布状况进行反映。(2)四川省各区域、各季节干旱分布不均:空间上,干旱频发的区域集中在四川盆地及攀西南部区域。时间上,在春季,四川盆地区域的土壤干旱程度大致呈现加剧—持续—减缓的趋势; 夏季,四川盆地的干旱变化趋势是加剧—减缓—加剧; 秋季,四川盆地的干旱变化趋势是加剧—减缓—持续减缓; 冬季,全川干旱程度变化不明显。本文的研究结果对四川省开展农业防灾减灾,引导农业灌溉具有指导意义。
Abstract:
For Sichuan, a major agricultural province in China, drought is the most important factor leading to the cutback in its agricultural production. It is crucial to carry out dynamic monitoring of soil drought, improve the timeliness of the monitoring, and enhance its visualization of soil drought space in Sichuan province through RS and GIS are in urgent need. Based on quarterly MODIS data from 2007 to 2016 and monthly precipitation data of 40 Meteorological Stations from 1961 to 2011, the distribution of drought levels in Sichuan province was calculated by Temperature Vegetation Dryness Index(TVDI). Together with Standardized Precipitation Index(SPI), the correlation analysis was carried out. Through linear regression, inverse distance weighted interpolation, and GIS spatial analysis model reconstruction, the spatiotemporal variation of soil drought in Sichuan from 2007 to 2016 was analyzed and micro-variations about drought distribution of each period were shown. The results showed:(1)On monthly time scale, SPI-1 and TVDI presented a moderate to strong negative correlation, which indicated that the smaller TVDI value and the greater SPI value, the lesser drought degree. The verification result showed that TVDI could well reflect the spatial distribution status of drought in Sichuan.(2)On quarterly time scale, drought of each region in different seasons showed an uneven distribution. In view of space, the most drought prone areas concentrated in the Sichuan Basin and the southern part of Panxi. In view of time, in spring, soil drought variation presented a worsen-still-ameliorate trend in the Sichuan Basin; in summer, it presented worsen-ameliorate-worsen trend; in autumn, it presented a worsen-ameliorate-still trend; in winter, the change was not obvious. The result would provide support for a better irrigation, and help reduce disaster risks in Sichuan province.

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备注/Memo

备注/Memo:
收稿日期(Received date):2019-07-15; 改回日期(Accepted date):2019-12-20
基金项目(Foundation item):四川省留学人员科技活动项目择优资助(10900-19BZ08-014); 大学生创新创业训练计划项目(201810616069); 四川省教育厅高校人文社科重点项目(ZHYJ17-ZD01)。[Selective Funding for Scientific and Technological Activities of Overseas Students in Sichuan(10900-19BZ08-014); Undergraduate Innovation and Entrepreneurship Training Program(201810616069); Key Projects of Humanities and Social Sciences in Colleges and Universities of Sichuan Province(ZHYJ17-ZD01)]
作者简介(Biography):陈艾琳(1996-),女,四川资阳人,硕士研究生,主要研究方向:3S技术与土壤水资源。[CHEN Ailin(1996-), female, born in Ziyang, Sichuan province, M.Sc. candidate, research on 3S technology and soil water resources] E-mail: 810337358@qq.com
*通讯作者(Corresponding author):戴晓爱(1979-),女,博士,副教授,主要研究方向:高光谱遥感与环境资源遥感。[DAI Xiaoai(1979-), female, Ph.D., associate professor, specialized in hyperspectral remote sensing and remote sensing of environmental resources] E-mail: Daixiaoai@163.com
更新日期/Last Update: 2020-01-30