IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v295y2024ics0378377424001100.html
   My bibliography  Save this article

Quantitative analysis of vegetation drought propagation process and uncertainty in the Yellow River Basin

Author

Listed:
  • Li, Liang
  • Peng, Qing
  • Wang, Maodong
  • Cao, Yuxin
  • Gu, Xiaobo
  • Cai, Huanjie

Abstract

Understanding the full propagation process of drought, from meteorological drought (MD) to vegetation drought (VD), could promote drought monitoring and early warning in the ecosystems. This study characterized MD, soil moisture drought (SD), and VD and their propagations using the Standardized Precipitation Evapotranspiration Index (SPEI), the Soil Moisture Anomaly Percentage Index (SMAPI), and the Vegetation Health Index (VHI) to enhance understanding of the drought hazard in the Yellow River Basin (YRB), China. Drought events, duration, magnitude, intensity, and interval were identified from these time series via the run theory and percentile thresholds. The relationships between MD, SD, and VD were examined by cross-correlating the SPEI, SMAPI, and VHI. Finally, the effects of climate and grid properties on drought characteristics and propagations were investigated. The results showed that the upland had a low risk for all droughts, while the midland had a low risk for MD and a high risk for SD, and the lowland had a high risk for MD in the YRB. For the full-time data, the lowland had the strongest correlations and shortest time lags, while the upland had the weakest correlations and longest time lags for full propagation from MD to SD to VD. However, seasonality and multi-threshold characteristics in extreme drought dominated the propagation process of VD. For monthly data, midland showed the strongest correlations and shortest time lags in summer, while lowland showed the strongest correlations and shortest time lags in other seasons for full propagation of VD. For multi-threshold data, the 0–30th percentile had stronger correlations and shorter time lags for full propagation of VD. Meteorology showed a stronger correlation with all drought characteristics and drought propagation than soil properties and land use. These findings provide valuable insights for enhancing the vegetation aspects of drought monitoring and early warning in the YRB.

Suggested Citation

  • Li, Liang & Peng, Qing & Wang, Maodong & Cao, Yuxin & Gu, Xiaobo & Cai, Huanjie, 2024. "Quantitative analysis of vegetation drought propagation process and uncertainty in the Yellow River Basin," Agricultural Water Management, Elsevier, vol. 295(C).
    • Handle: RePEc:eee:agiwat:v:295:y:2024:i:c:s0378377424001100
    DOI: 10.1016/j.agwat.2024.108775
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377424001100
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2024.108775?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:295:y:2024:i:c:s0378377424001100. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.