Dynamic Evaluation of Agricultural Drought Hazard in Northeast China Based on Coupled Multi-Source Data

Kaiwei Li; Chunyi Wang; Guangzhi Rong; Sicheng Wei; Cong Liu; Yueting Yang; Bilige Sudu; Ying Guo; Qing Sun; Jiquan Zhang

doi:10.3390/rs15010057

Remote Sensing (Dec 2022)

Dynamic Evaluation of Agricultural Drought Hazard in Northeast China Based on Coupled Multi-Source Data

Kaiwei Li,
Chunyi Wang,
Guangzhi Rong,
Sicheng Wei,
Cong Liu,
Yueting Yang,
Bilige Sudu,
Ying Guo,
Qing Sun,
Jiquan Zhang

Affiliations

Kaiwei Li: School of Environment, Northeast Normal University, Changchun 130024, China
Chunyi Wang: Chinese Academy of Meteorological Sciences, Beijing 100081, China
Guangzhi Rong: School of Environment, Northeast Normal University, Changchun 130024, China
Sicheng Wei: School of Environment, Northeast Normal University, Changchun 130024, China
Cong Liu: School of Environment, Northeast Normal University, Changchun 130024, China
Yueting Yang: School of Environment, Northeast Normal University, Changchun 130024, China
Bilige Sudu: School of Environment, Northeast Normal University, Changchun 130024, China
Ying Guo: School of Environment, Northeast Normal University, Changchun 130024, China
Qing Sun: Chinese Academy of Meteorological Sciences, Beijing 100081, China
Jiquan Zhang: School of Environment, Northeast Normal University, Changchun 130024, China

DOI: https://doi.org/10.3390/rs15010057
Journal volume & issue: Vol. 15, no. 1
p. 57

Abstract

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As the climate warms, the impact of drought on plants has increased. We aimed to construct a comprehensive drought index (CDI), coupling soil-vegetation-atmosphere drought and heat conditions based on multi-source information, and to combine it with static and dynamic drought hazard evaluation models to analyze the spatial and temporal distribution characteristics of agricultural drought disasters and hazards during the growing season (May to September) in Northeast China (NEC). The results demonstrated that the CDI could combine the benefits of meteorology (standardized precipitation evapotranspiration index, SPEI), vegetation (vegetation health index, VHI), and soil (standardized soil moisture condition index, SMCI) indices. This was performed using a relative weighting method based on the remote sensing data of solar-induced chlorophyll fluorescence (SIF) to determine the weights of SPEI, VHI, and SMCI. The CDI for drought monitoring has the advantages of broad spatial range, long time range, and high accuracy, and can effectively reflect agricultural drought; the growing season in NEC showed a trend of becoming drier during 1982–2020. However, the trends of the drought index, the impact range of drought events, and the hazard of agricultural drought all turned around 2000. The drought hazard was highly significant (p 2 = 0.28). In the center and western portions of the study area, farmland and grassland areas were where higher levels of hazard were most commonly seen. The dynamic hazard index is significantly correlated with climatic yield anomalies and can reflect the actual impact of drought on crop yield. The study results serve as a scientific foundation for drought risk assessment and management, agricultural planning, and the formulation of drought adaptation policies, as well as for ensuring food security in China.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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