The composite drought index incorporated solar-induced chlorophyll fluorescence enhances the monitoring capability of short-term drought

被引:3
作者
Ren, Hangxing [1 ]
Du, Lin [1 ]
Peng, Chuanjing [1 ]
Yang, Jian [1 ]
Gao, Wei [1 ]
机构
[1] China Univ Geosci, Sch Geog & Informat Engn, Wuhan 430079, Peoples R China
关键词
Solar-induced chlorophyll fluorescence; Principal Component Analysis; Drought monitoring; Vegetation response; MULTISENSOR INTEGRATED INDEX; STATES; MODEL; USDM;
D O I
10.1016/j.jhydrol.2024.131361
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Understanding the response of vegetation to drought is significant for socio-economic development and biodiversity conservation. However, due to the complexity of drought, relying only on one approach, such as the surrounding physical environmental conditions or specific vegetation characteristics, does not yield precise results. To address this challenge, composite drought indices incorporating Normalized Difference Vegetation Index (NDVI) and other multiple variables, have been developed and shown promising effectiveness in drought detection. Compared to NDVI, solar-induced chlorophyll fluorescence (SIF) decreases due to the increased nonphotochemical quenching and reduced photosynthesis during short-term drought stress. This indicates a direct association between SIF and vegetation photosynthesis, offering advantages over NDVI in capturing drought effects. Nevertheless, SIF has not yet been fully integrated into composite drought indices. Therefore, this study focused on assessing the advantages of SIF for short-term drought monitoring by constructing a new composite drought index (CPDI) using the Principal Component Analysis (PCA) method. Subsequently, CPDI was employed to forecast future drought conditions. Overall, CPDI performs exceptionally well as a composite drought index in drought trend analysis and drought event identification, indeed advancing the monitoring capability for shortterm drought. Furthermore, the incorporation of SIF in CPDI, obtained from various data sources provides more timely monitoring of drought events, while the CPDI with NDVI reflects the cumulative effect of drought conditions over a longer period. In the future, it is potential to utilize the benefits of SIF in constructing drought indices or combine it with NDVI for comprehensive drought characterization.
引用
收藏
页数:13
相关论文
共 79 条
  • [1] Abtew W., 2013, Evaporation and evapotranspiration: Measurements and estimations, P53, DOI [DOI 10.1007/978-94-007-4737-1_5, DOI 10.1007/978-94-007-4737-1, 10.1007/978-94-007-4737-1]
  • [2] Remote sensing of drought: Progress, challenges and opportunities
    AghaKouchak, A.
    Farahmand, A.
    Melton, F. S.
    Teixeira, J.
    Anderson, M. C.
    Wardlow, B. D.
    Hain, C. R.
    [J]. REVIEWS OF GEOPHYSICS, 2015, 53 (02) : 452 - 480
  • [3] How well do meteorological indicators represent agricultural and forest drought across Europe?
    Bachmair, S.
    Tanguy, M.
    Hannaford, J.
    Stahl, K.
    [J]. ENVIRONMENTAL RESEARCH LETTERS, 2018, 13 (03):
  • [4] A Multivariate Drought Index for Seasonal Agriculture Drought Classification in Semiarid Regions
    Bageshree, K.
    Abhishek
    Kinouchi, Tsuyoshi
    [J]. REMOTE SENSING, 2022, 14 (16)
  • [5] Estimation of global GPP from GOME-2 and OCO-2 SIF by considering the dynamic variations of GPP-SIF relationship
    Bai, Jia
    Zhang, Helin
    Sun, Rui
    Li, Xing
    Xiao, Jingfeng
    Wang, Yan
    [J]. AGRICULTURAL AND FOREST METEOROLOGY, 2022, 326
  • [6] Bateni MM, 2018, WATER RESOUR MANAG, V32, P4345, DOI [10.1007/s11269-018-2056-8, 1]
  • [7] Hash-tree PCA: accelerating PCA with hash-based grouping
    Battulga, Lkhagvadorj
    Lee, Sang-Hyun
    Nasridinov, Aziz
    Yoo, Kwan-Hee
    [J]. JOURNAL OF SUPERCOMPUTING, 2020, 76 (10) : 8248 - 8264
  • [8] Propagation of Meteorological to Hydrological Droughts in India
    Bhardwaj, Kunal
    Shah, Deep
    Aadhar, Saran
    Mishra, Vimal
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2020, 125 (22)
  • [9] Unpacking the drivers of diurnal dynamics of sun-induced chlorophyll fluorescence (SIF): Canopy structure, plant physiology, instrument configuration and retrieval methods
    Chang, Christine Y.
    Wen, Jiaming
    Han, Jimei
    Kira, Oz
    LeVonne, Julie
    Melkonian, Jeffrey
    Riha, Susan J.
    Skovira, Joseph
    Ng, Sharon
    Gu, Lianhong
    Wood, Jeffrey D.
    Naethe, Paul
    Sun, Ying
    [J]. REMOTE SENSING OF ENVIRONMENT, 2021, 265
  • [10] Simulating spatially distributed solar-induced chlorophyll fluorescence using a BEPS-SCOPE coupling framework
    Cui, Tianxiang
    Sun, Rui
    Xiao, Zhiqiang
    Liang, Ziyu
    Wang, Jian
    [J]. AGRICULTURAL AND FOREST METEOROLOGY, 2020, 295