Identification of Drought and Drought Hazard Assessment in Midwest of Jilin Province Based on SVDI

LI Danjun; ZHANG Jiquan; GUO Enliang; WANG Rui

doi:10.13961/j.cnki.stbctb.2017.04.054

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Identification of Drought and Drought Hazard Assessment in Midwest of Jilin Province Based on SVDI

- Identification of Drought and Drought Hazard Assessment in Midwest of Jilin Province Based on SVDI
- Bulletin of Soiland Water Conservation Vol. 37, Issue 4, Pages: 321-326(2017)
- 作者机构：
  
  东北师范大学环境学院东北师范大学自然灾害研究所,吉林,长春,130024
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2017.04.054
  CLC：
- Published：2017
- 稿件说明：
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LI Danjun, ZHANG Jiquan, GUO Enliang, et al. Identification of Drought and Drought Hazard Assessment in Midwest of Jilin Province Based on SVDI[J]. Bulletin of Soiland Water Conservation, 2017, 37(4): 321-326.
DOI：

LI Danjun, ZHANG Jiquan, GUO Enliang, et al. Identification of Drought and Drought Hazard Assessment in Midwest of Jilin Province Based on SVDI[J]. Bulletin of Soiland Water Conservation, 2017, 37(4): 321-326. DOI： 10.13961/j.cnki.stbctb.2017.04.054.

摘要

[目的]在农作物生育期期间对吉林省中西部地区进行干旱的识别和量化，进行干旱危险性分析，为该地区农作物防旱减灾工作的展开提供参考。[方法]利用2005-2014年5-8月旬气象站数据和MODIS的NDVI 10 d合成产品，采用空间植被干旱指数（SVDI）研究典型年吉林省中西部干旱时空分布特征，并结合农业干旱减产及粮食产量分析其适用性，进一步利用逐旬SVDI概率密度分布计算旬时间尺度的干旱危险性及月时间尺度的干旱危险性分布。[结果]（1）与VCI指数相比，在作物生长前期和后期农业干旱减产和产量波动与SVDI呈现出更高的相关系数；（2）2005-2014年吉林省中西部重旱面积波动较为明显，重旱区域呈现出向中部和西南部地区转移的趋势；（3）吉林省中西部地区内5月上旬、下旬，6和8月下旬干旱发生概率较高；8月上旬和6月下旬干旱危险性较大；通榆县5-8月间干旱危险性较高。[结论]利用SVDI指数进行干旱的识别和量化是可行的，且在吉林省中西部作物生育期不同阶段干旱有明显的区域性。

Abstract

[Objective] To identify and quantify the drought during crop growing season in Midwest of Jilin Province and analyze drought hazard in order to provide scientific reference for drought mitigation.[Methods] Based on the meteorological data from May to August during 2005 to 2014 and the corresponding MODIS NDVI products that was combined every ten days and have 500 m resolution

SVDI(spatial vegetation drought index) was calculated to analyze SVDI spatial and temporal distribution characteristics. The index applicability was illustrated in terms of drought-induced agricultural production decrease and yield anomaly. Furthermore

the density distribution of ten-day SVDI from May to August was calculate to demonstrate drought hazard.[Results] (1) Compared with VCI

SVDI behave better for drought recognition. Combined with agricultural drought production and yield anomaly

SVDI showed higher correlation in the initial and final growth period of crop growing season. (2) During 2005-2014

the area hited by severe drought from May to August in Midwest of Jilin Province fluctuated obviously

and had a transiting trend to central and southwest parts. (3) In Midwest of Jilin Province

drought occurrence had higher probability in periods of early and late May

June

and late August

whereas

in early August and late June

the drought hazard are higher. Tongyu County has high drought hazard from May to August so that it should be taken as a key county to be protected.[Conclusion] The results showed that using SVDI to identify and quantify drought is feasible

also drought frequency during crop growing season in Midwest of Jilin Province shows obvious regional traits.

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