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Assessment of meteorological and agricultural droughts using in-situ observations and remote sensing data

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  • Zuo, Depeng
  • Cai, Siyang
  • Xu, Zongxue
  • Peng, Dingzhi
  • Kan, Guangyuan
  • Sun, Wenchao
  • Pang, Bo
  • Yang, Hong

Abstract

Most research on drought assessment adopted historical in-situ observations, however, there has been increased data availability from remote sensing during the recent years. This study utilizes the two sources of data in drought assessment. Using the historical in-situ observations, the spatiotemporal variations of meteorological drought were firstly investigated by calculating the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) at 1, 3, 6-month time scales in Northeast China. Using remote sensing data, the combined deficit index (CDI) for agricultural drought assessment was computed based on tri-monthly sum of deficit in antecedent rainfall and deficit in monthly NDVI at land cover type and sub-type levels in the same region. In the end, the agricultural drought calculated by the CDI was evaluated against the deficit in crop yield, as well as deficit in Land Surface Temperature (LST) and Evapotranspiration (ET), in order to verify the applicability of the CDI for agricultural drought assessment in the study region. The results showed that the CDI has better correlations with the SPEI (R2 = 0.48) than the SPI (R2 = 0.05) at 3-month scales with weight factor a = 0.5 in dry farming areas. The spatial pattern of the CDI showed that the area of agricultural drought increased from July to October. In addition, a significant linear correlation was found between the CDI and anomaly in annual agricultural yield (R2 = 0.55), and anomaly in monthly land surface temperature (R2 = 0.42). The results prove that the CDI calculated by remote sensing data is not only a reliable indicator for agricultural drought assessment in Northeast China, but also provides useful information for agricultural drought disaster prevention and mitigation, and water management improvement.

Suggested Citation

  • Zuo, Depeng & Cai, Siyang & Xu, Zongxue & Peng, Dingzhi & Kan, Guangyuan & Sun, Wenchao & Pang, Bo & Yang, Hong, 2019. "Assessment of meteorological and agricultural droughts using in-situ observations and remote sensing data," Agricultural Water Management, Elsevier, vol. 222(C), pages 125-138.
    • Handle: RePEc:eee:agiwat:v:222:y:2019:i:c:p:125-138
    DOI: 10.1016/j.agwat.2019.05.046
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    1. Zhou, Keke & Li, Jianzhu & Zhang, Ting & Kang, Aiqing, 2021. "The use of combined soil moisture data to characterize agricultural drought conditions and the relationship among different drought types in China," Agricultural Water Management, Elsevier, vol. 243(C).
    2. Wang, Fei & Lai, Hexin & Li, Yanbin & Feng, Kai & Zhang, Zezhong & Tian, Qingqing & Zhu, Xiaomeng & Yang, Haibo, 2022. "Dynamic variation of meteorological drought and its relationships with agricultural drought across China," Agricultural Water Management, Elsevier, vol. 261(C).
    3. V. K. Prajapati & M. Khanna & M. Singh & R. Kaur & R. N. Sahoo & D. K. Singh, 2021. "Evaluation of time scale of meteorological, hydrological and agricultural drought indices," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(1), pages 89-109, October.
    4. Wei Pei & Cuizhu Tian & Qiang Fu & Yongtai Ren & Tianxiao Li, 2022. "Risk analysis and influencing factors of drought and flood disasters in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 1599-1620, February.
    5. Cai, Siyang & Zuo, Depeng & Wang, Huixiao & Xu, Zongxue & Wang, GuoQing & Yang, Hong, 2023. "Assessment of agricultural drought based on multi-source remote sensing data in a major grain producing area of Northwest China," Agricultural Water Management, Elsevier, vol. 278(C).
    6. Kaur, Lakhvinder & Rishi, Madhuri S. & Chaudhary, Bhagwan Singh, 2022. "Assessment of meteorological and agricultural droughts using remote sensing and their impact on groundwater in an agriculturally productive part of Northwest India," Agricultural Water Management, Elsevier, vol. 274(C).
    7. Yuan Li & Yi Dong & Dongqin Yin & Diyou Liu & Pengxin Wang & Jianxi Huang & Zhe Liu & Hongshuo Wang, 2020. "Evaluation of Drought Monitoring Effect of Winter Wheat in Henan Province of China Based on Multi-Source Data," Sustainability, MDPI, vol. 12(7), pages 1-19, April.

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