Construction and Application of Dynamic Threshold Model for Agricultural Drought Grades Based on Near-Infrared and Short-Wave Infrared Bands for Spring Maize

Author:

Wu Xia1,Wang Peijuan2ORCID,Gong Yanduo3,Zhang Yuanda2,Wang Qi2,Li Yang2,Guo Jianping2,Han Shuxin1

Affiliation:

1. Heilongjiang Ecology Meteorological Center, Northeast Satellite Meteorological Data Center, Harbin 150030, China

2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China

3. Heilongjiang Meteorological Observatory, Harbin 150030, China

Abstract

Maize (Zea mays L.) is one of the most important grain crops in the world. Drought caused by climate change in recent years may greatly threaten water supply and crop production, even if the drought only lasts for a few days or weeks. Therefore, effective daily drought monitoring for maize is crucial for ensuring food security. A pivotal challenge in current related research may be the selection of data collection and the methodologies in the construction of these indices. Therefore, orthorectified reflectance in the short-wave infrared (SWIR) band, which is highly sensitive to variations in vegetation water content, was daily obtained from the MODIS MCD43A4 product. Normalized Difference Water Index (NDWI) calculated using the NIR and SWIR bands and days after planting (DAP) were normalized to obtain the Vegetation Water Index (VWI) and normalized days after planting (NDAP), respectively. The daily dynamic threshold model for different agricultural drought grades was constructed based on the VWI and NDAP with double-logistic fitting functions during the maize growing season, and its specific threshold was determined with historical drought records. Verification results indicated that the VWI had a good effect on the daily agricultural drought monitoring of spring maize in the “Golden Maize Belt” in northeast China. Drought grades produced by the VWI were completely consistent with historical records for 84.6% of the validation records, and 96.2% of the validation records differed by only one grade level or less. The VWI can not only daily identify the occurrence and development process of drought, but also well reflect the impact of drought on the yield of maize. Moreover, the VWI could be used to monitor the spatial evolution of drought processes at both regional and precise pixel scales. These results contribute to providing theoretical guidance for the daily dynamic monitoring and evaluation of spring maize drought in the “Golden Maize Belt” of China.

Funder

the National Key Research and Development Program of China

the National Natural Science Foundation of China

Special Project for Innovation and Development of CMA

the Basic Research Fund of CAMS

the Science and Technology Development Fund of CAMS

the Key innovation team of the China Meteorological Administration

Publisher

MDPI AG

Reference63 articles.

1. Difference and cause analysis of drought characteristics during growth period between the corn belts of China and the United States in Past 30 Years;Wang;Chin. J. Agrometeor.,2018

2. Characteristics of agricultural meteorological disasters in China from 1976 to 2015. Chin;Liu;J. Agrometeor.,2017

3. Impact simulation of drought at different growth stages on grain formation and yield of maize;Zhang;Chin. J. Agrometeor.,2015

4. Influence of agricultural meteorological disasters on output of crop in China;Wang;J. Nat. Disaster,2007

5. Seneviratne, S.I., Zhang, X., Adnan, M., Badi, W., Dereczynski, C., Luca, A.D., Ghosh, S., Iskandar, I., Kossin, J., and Lewis, S. (2021). Weather and Climate Extreme Events in a Changing Climate//IPCC Climate Change 2021: The Physical Science Basis, Cambridge University Press.

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