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Optimal Drought Index Selection for Soil Moisture Monitoring at Multiple Depths in China’s Agricultural Regions

Author

Listed:
  • Peiwen Yao

    (State Key Lab for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Hong Fan

    (State Key Lab for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Qilong Wu

    (School of Resource and Environmental Sciences, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

Abstract

Droughts are a major driver of global environmental degradation, threatening lives and causing significant economic losses, with approximately 80% of these losses linked to agricultural drought, characterized by soil moisture deficits. Remote sensing technology offers high spatiotemporal resolution data for continuous monitoring of soil moisture and drought severity. However, the effectiveness of remote sensing drought indices across different soil depths remains unclear. This study assessed the performance of eight widely used drought indices—Perpendicular Drought Index (PDI), Modified Perpendicular Drought Index (MPDI), Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), Normalized Vegetation Supply Water Index (NVSWI), Temperature–Vegetation Dryness Index (TVDI), and Standardized Precipitation–Evapotranspiration Index (SPEI) at multiple timescales—in monitoring soil moisture at five depths (0–50 cm, at 10 cm intervals) across nine agricultural regions of China from 2001 to 2020. Results reveal that the monitoring performance of drought indices varies significantly across regions and soil depths, with a general decline in performance as soil depth increases. For soil depths between 10–40 cm, VCI and NVSWI exhibited the highest accuracy, while PDI, MPDI, and VHI performed optimally in the Northeast China Plain. At 50 cm depth, however, optical remote sensing indices struggled to accurately capture soil moisture conditions. Additionally, TCI and TVDI showed notable lag effects, with 4-month and 5-month delays, respectively, while SPEI exhibited cumulative effects over 3–6 months. These findings provide critical insights to guide the selection of appropriate drought indices for soil moisture monitoring, aiding agricultural drought management and decision-making.

Suggested Citation

  • Peiwen Yao & Hong Fan & Qilong Wu, 2025. "Optimal Drought Index Selection for Soil Moisture Monitoring at Multiple Depths in China’s Agricultural Regions," Agriculture, MDPI, vol. 15(4), pages 1-24, February.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:4:p:423-:d:1593111
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    References listed on IDEAS

    as
    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. Samaneh Zormand & Reza Jafari & Saeed Soltani Koupaei, 2017. "Assessment of PDI, MPDI and TVDI drought indices derived from MODIS Aqua/Terra Level 1B data in natural lands," 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. 86(2), pages 757-777, March.
    3. Laibao Liu & Lukas Gudmundsson & Mathias Hauser & Dahe Qin & Shuangcheng Li & Sonia I. Seneviratne, 2020. "Soil moisture dominates dryness stress on ecosystem production globally," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
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