An agricultural drought index for assessing droughts using a water balance method: a case study in Jilin Province, Northeast China

Cao, Yijing; Chen, Shengbo; Wang, Lei; Zhu, Bingxue; Lu, Tianqi; Yu, Yan. 2019 An agricultural drought index for assessing droughts using a water balance method: a case study in Jilin Province, Northeast China. Remote Sensing, 11 (9), 1066. https://doi.org/10.3390/rs11091066

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Official URL: http://dx.doi.org/10.3390/rs11091066

Abstract/Summary

Drought, which causes the economic, social, and environmental losses, also threatens food security worldwide. In this study, we developed a vegetation-soil water deficit (VSWD) method to better assess agricultural droughts. The VSWD method considers precipitation, potential evapotranspiration (PET) and soil moisture. The soil moisture from different soil layers was compared with the in situ drought indices to select the appropriate depths for calculating soil moisture during growing seasons. The VSWD method and other indices for assessing the agricultural droughts, i.e., Scaled Drought Condition Index (SDCI), Vegetation Health Index (VHI) and Temperature Vegetation Dryness Index (TVDI), were compared with the in situ and multi-scales of Standardized Precipitation Evapotranspiration Index (SPEIs). The results show that the VSWD method has better performance than SDCI, VHI, and TVDI. Based on the drought events collected from field sampling, it is found that the VSWD method can better distinguish the severities of agricultural droughts than other indices mentioned here. Moreover, the performances of VSWD, SPEIs, SDCI and VHI in the major historical drought events recorded in the study area show that VSWD has generated the most sensible results than others. However, the limitation of the VSWD method is also discussed.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/rs11091066
ISSN:	2072-4292
Date made live:	16 Aug 2019 15:29 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/524798

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.3390/rs11091066

ISSN:

2072-4292

Date made live:

16 Aug 2019 15:29 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/524798