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遥感技术与应用  2019, Vol. 34 Issue (4): 865-873    DOI: 10.11873/j.issn.1004-0323.2019.4.0865
遥感应用     
考虑下垫面类型的干旱指数比较研究
王展鹏1(),宋立生1(),兰子焱2,杨梦颖1,鲁丹1
1. 西南大学地理科学学院 遥感大数据应用重庆市工程研究中心,重庆 400715
2. 西南大学 含弘学院, 重庆 400715
Evaluation of Drought Indices of Metrology, Hydrology and Agriculture over the Continental United States
Zhanpeng Wang1(),Lisheng Song1(),Ziyan Lan2,Menying Yang1,Dan Lu1
1. Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
2. Hanhong College, Southwest University, Chongqing 400715, China
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摘要:

干旱作为常见的自然灾害,在世界各地发生的频率日渐增加,已对经济发展、农业生产和人类生活等方面产生了严重影响。但是干旱的类型较多,包括气象干旱、土壤干旱、水文干旱、农田干旱等,无法用单个干旱指数对不同类型的干旱进行监测。按照干旱发生类型,利用气象干旱指数(Standardized Precipitation Index SPI)、土壤水分干旱指数(Soil Moisture Index, SMI)和蒸发压力干旱指数(Evaporative Stress Index, ESI)对美国的旱情进行监测。研究结果表明:不同干旱指数之间呈显著相关,相关系数R在0.7以上。ESI整体监测精度较高,它能够真实反映地表水分盈亏状况,同时与遥感数据结合,可以实现从田块到全球不同尺度干旱实时监测。不同植被类型覆盖下垫面对不同类型干旱响应存在较大差异,草地下垫面对不同类型的干旱响应较为一致,但是随着地上生物量的增加,不同干旱指数监测结果之间差异逐渐增大。因此,在干旱监测时需要考虑植被的结构特征,植被与气候之间的相互作用,才能具体分析不同下垫面的受灾情况,进一步考虑更适合的方法以及干旱指数监测不同下垫面的干旱情况。

关键词: 干旱指数ESISPISMI    
Abstract:

Droughts are one of the more normally natural hazards on a year-to-year basis. And the drought are significant and widespread, affecting economic development, agriculture and people health at any one time. There are various drought indexes have been developed to monitor this hazard which arise precipitation decrease, soil moisture deficit and vegetation stress. However, single drought index cannot consider all of these anomaly to warn and monitor the drought. In this study, remote sensing based data including GLDAS climate data involve precipitation and soil moisture, GLEAM ET and GRACE dataset simulated terrestrial water storage are used to calculate multiple drought indicators including SPI, SMI, ESI and TWSC. These drought indicators refer to anomaly of precipitation, soil moisture and vegetation water supply, and terrestrial water storage change, respectively. Then they were used combined and compared to track the droughts events in United State of American. The results showed that all the drought indexes performed reliable and consistent with each other well, with correlation coefficient value greater than 0.7. However, the ESI performed more reliable, which can reflect the plant water stress under dry condition, additionally, it can be computed in combined with satellite observed data with high spatial resolution to monitor the drought conditions from field scale to global scale. The vegetation have divergent responses to the meteorological, hydrological and droughts except under grassland. The differences between the three drought indexes increase along with the elevated aboveground biomass. Therefore, the land surface vegetation covered conditions involve canopy structure and feedback between plants and climate, which relevant in a drought monitor is often a curial consideration in determining the application of drought indexes.

Key words: Drought indexes    ESI    SPI    SMI
收稿日期: 2018-05-11 出版日期: 2019-10-16
ZTFLH:  Q948  
基金资助: 国家自然基金青年基金项目(41701377);中央高校基本科研业务费专项资金项目(XDJK2017C004);西南大学博士基金(含人才引进计划)项目(SWU11042)
通讯作者: 宋立生     E-mail: wangzp0825@email.swu.edu.cn;songls@swu.edu.cn
作者简介: 王展鹏 (1997-),男,湖北武汉人,本科生,主要从事环境遥感研究。E?mail:wangzp0825@email.swu.edu.cn
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引用本文:

王展鹏,宋立生,兰子焱,杨梦颖,鲁丹. 考虑下垫面类型的干旱指数比较研究[J]. 遥感技术与应用, 2019, 34(4): 865-873.

Zhanpeng Wang,Lisheng Song,Ziyan Lan,Menying Yang,Dan Lu. Evaluation of Drought Indices of Metrology, Hydrology and Agriculture over the Continental United States. Remote Sensing Technology and Application, 2019, 34(4): 865-873.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.4.0865        http://www.rsta.ac.cn/CN/Y2019/V34/I4/865

图 1  美国本土土地利用类型空间分布图
SMI-1SMI-3ESI-3TWSC
SPI-6Pearson 相关性0.591 6**0.714 5**0.694 9**0.253 2
显著性(双侧)0000.001 5
SMI-1Pearson 相关性0.869 9**0.634 7**0.167 2
显著性(双侧)000.038 2
SMI-3Pearson 相关性0.771 0**0.223 7**
显著性(双侧)00.005 3
ESI-3Pearson 相关性0.273 8**
显著性(双侧)0.000 6
注:**. 在 0.01 水平(双侧)上显著相关
表1  主要的4个指数平均值的相关性
图2  2003~2015年SPI、ESI、SMI、TWSC的监测情况
图3  主要指数的空间相关性
图4  不同下垫面3种干旱指数之间的比较
耕地裸地林地灌木草地
SPI-6与ESI-3相关性0.29950.80280.59080.86580.8173
SPI-6与SMI-3相关性0.61830.79030.67360.80970.7017
ESI-3与SMI-3相关性0.53460.86640.62760.89630.8450
表2  不同类别植被干旱指数间的相关性
图5  2012年干旱形成过程对比分析
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