IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i23p10489-d1532992.html
   My bibliography  Save this article

Assessment of Vegetation Vulnerability in the Haihe River Basin Under Compound Heat and Drought Stress

Author

Listed:
  • Hui Yin

    (College of Civil Engineering and Architecture, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China)

  • Fuqing Bai

    (College of Civil Engineering and Architecture, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China)

  • Huiming Wu

    (Guangzhou Zhukeyuan Engineering Survey and Design Co., Ltd., Guangzhou 510610, China)

  • Meng Yan

    (Guangzhou Zhukeyuan Engineering Survey and Design Co., Ltd., Guangzhou 510610, China)

  • Shuai Zhou

    (School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, No. 19 Taiji Road, Handan Economic and Technological, Development Zone, Handan 056038, China)

Abstract

With the intensification of global warming, droughts and heatwaves occur frequently and widely, which have a serious impact on the healthy growth of vegetation. The challenge is to accurately characterize vegetation vulnerability under compound heat and drought stress using correlation-based methods. This article uses the Haihe River Basin, an ecologically sensitive area known for experiencing droughts nine out of ten years, as an example. Firstly, using daily precipitation and maximum temperature data from 38 meteorological stations in the basin from 1965 to 2019, methods such as univariate linear regression and the Mann–Kendall mutation test were employed to identify the temporal variation patterns of meteorological elements in the basin. Secondly, the Pearson correlation coefficient and other methods were applied to determine the most likely months for compound dry and hot events, and the joint distribution pattern and recurrence period of concurrent high temperature and intense drought events were explored. Finally, a vegetation vulnerability assessment model based on Vine Copula in compound dry and hot climates was constructed to quantify the relationship of the response of watershed vegetation to different extreme events (high temperature, drought, and compound dry and hot climates). The results indicated that the basin’s precipitation keeps decreasing, evaporation rises, and the supply–demand conflict grows more severe. The correlation between the Standardized Precipitation Index (SPI) and Standardized Temperature Index (STI) is strongest at the 3-month scale from June to August. Meanwhile, in most areas of the basin, the Standardized Normalized Difference Vegetation Index (sNDVI) is positively correlated with the SPI and negatively correlated with the STI. Compared to a single drought or high-temperature event, compound dry and hot climates further exacerbate the vegetation vulnerability of the Haihe River Basin. In compound dry and hot climates, the probability of vegetation loss in June, July, and August is as high as 0.45, 0.32, and 0.38, respectively. Moreover, vegetation vulnerability in the southern and northwestern mountainous areas of the basin is higher, and the ecological risk is severe. The research results contribute to an understanding of the vegetation’s response to extreme climate events, aiming to address terrestrial ecosystem risk management in response to climate change.

Suggested Citation

  • Hui Yin & Fuqing Bai & Huiming Wu & Meng Yan & Shuai Zhou, 2024. "Assessment of Vegetation Vulnerability in the Haihe River Basin Under Compound Heat and Drought Stress," Sustainability, MDPI, vol. 16(23), pages 1-19, November.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:23:p:10489-:d:1532992
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/23/10489/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/23/10489/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    2. Hu, Juan & Zhao, Xinyu & Gu, Liming & Liu, Peng & Zhao, Bin & Zhang, Jiwang & Ren, Baizhao, 2023. "The effects of high temperature, drought, and their combined stresses on the photosynthesis and senescence of summer maize," Agricultural Water Management, Elsevier, vol. 289(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    2. Rand Kwong Yew Low, 2018. "Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 423-463, November.
    3. Roger M. Cooke & Harry Joe & Bo Chang, 2020. "Vine copula regression for observational studies," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(2), pages 141-167, June.
    4. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    5. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    6. Zhang, Dalu, 2014. "Vine copulas and applications to the European Union sovereign debt analysis," International Review of Financial Analysis, Elsevier, vol. 36(C), pages 46-56.
    7. Portier, François & Segers, Johan, 2018. "On the weak convergence of the empirical conditional copula under a simplifying assumption," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 160-181.
    8. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.
    9. Sun, Fuqiang & Fu, Fangyou & Liao, Haitao & Xu, Dan, 2020. "Analysis of multivariate dependent accelerated degradation data using a random-effect general Wiener process and D-vine Copula," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    10. Zhichao Zhang & Fan Zhang & Zhuang Zhang, 2013. "Strategic Asset Allocation for China's Foreign Reserves: A Copula Approach," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 21(6), pages 1-21, November.
    11. Zhiwei Bai & Hongkui Wei & Yingying Xiao & Shufang Song & Sergei Kucherenko, 2021. "A Vine Copula-Based Global Sensitivity Analysis Method for Structures with Multidimensional Dependent Variables," Mathematics, MDPI, vol. 9(19), pages 1-20, October.
    12. Zhi, Bangdong & Wang, Xiaojun & Xu, Fangming, 2022. "Managing inventory financing in a volatile market: A novel data-driven copula model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    13. Ozonder, Gozde & Miller, Eric J., 2021. "Longitudinal investigation of skeletal activity episode timing decisions – A copula approach," Journal of choice modelling, Elsevier, vol. 40(C).
    14. Mazo, Gildas & Averyanov, Yaroslav, 2019. "Constraining kernel estimators in semiparametric copula mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 170-189.
    15. Bassetti, Federico & De Giuli, Maria Elena & Nicolino, Enrica & Tarantola, Claudia, 2018. "Multivariate dependence analysis via tree copula models: An application to one-year forward energy contracts," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1107-1121.
    16. Dominique Guegan & Bertrand K. Hassani, 2011. "Operational risk: a Basel II++ step before Basel III," Documents de travail du Centre d'Economie de la Sorbonne 11053, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    17. Rubén Albeiro Loaiza Maya & Jose Eduardo Gomez-Gonzalez & Luis Fernando Melo Velandia, 2015. "Latin American Exchange Rate Dependencies: A Regular Vine Copula Approach," Contemporary Economic Policy, Western Economic Association International, vol. 33(3), pages 535-549, July.
    18. Maziar Sahamkhadam, 2021. "Dynamic copula-based expectile portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 209-223, May.
    19. Schinke-Nendza, A. & von Loeper, F. & Osinski, P. & Schaumann, P. & Schmidt, V. & Weber, C., 2021. "Probabilistic forecasting of photovoltaic power supply — A hybrid approach using D-vine copulas to model spatial dependencies," Applied Energy, Elsevier, vol. 304(C).
    20. Beatrice D. Simo-Kengne & Kofi A. Ababio & Jules Mba & Ur Koumba, 2018. "Behavioral portfolio selection and optimization: an application to international stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(3), pages 311-328, August.

    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:gam:jsusta:v:16:y:2024:i:23:p:10489-:d:1532992. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.