IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v120y2024i3d10.1007_s11069-023-06179-4.html
   My bibliography  Save this article

A nonparametric standardized runoff index for characterizing hydrological drought in the Shaying River Basin, China

Author

Listed:
  • Rong Gan

    (Zhengzhou University)

  • Shuqian Gu

    (Zhengzhou University)

  • Xiaoxia Tong

    (China Geological Environmental Monitoring Institute)

  • Jinqiang Lu

    (Zhengzhou University)

  • Hui Tang

    (Henan Institute of Geological Survey)

Abstract

Under the background of global warming and human activities, drought occurs frequently in the Shaying River Basin (SYRB). It is particularly important for agriculture and water resources management to comprehensively evaluate the evolution of hydrological drought in the river basin. In this study, we used the nonparametric standardized runoff index (NSRI) to investigate the temporal characteristics of hydrological drought in the SYRB from 1956 to 2013. The duration and severity of hydrological drought events were identified based on run theory, and the copula functions with the highest goodness of fit were used to investigate the drought return period. In addition, the double cumulative curve method was used to analyze the main causes of hydrological drought in the SYRB. The results indicated that: (1) From 1957 to 2013, the drought showed an increasing trend in the upper, middle and lower reaches of the SYRB, with frequent alternations of droughts, and the trend characteristic of drought was different in each subzone; (2) the frequency of drought decreased from upstream to downstream, but the duration and severity of drought increased; (3) Frank-copula was considered to be the best fitting two-dimensional copula function in the SYRB and the most severe drought lasted for 25 months, with drought severity of 11.485, and drought return period of 42.14 years; (4) human activities were the main reason for the decrease of runoff in the SYRB and the dominant factor for the intensification of hydrological drought in the basin.

Suggested Citation

  • Rong Gan & Shuqian Gu & Xiaoxia Tong & Jinqiang Lu & Hui Tang, 2024. "A nonparametric standardized runoff index for characterizing hydrological drought in the Shaying River Basin, 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. 120(3), pages 2233-2253, February.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:3:d:10.1007_s11069-023-06179-4
    DOI: 10.1007/s11069-023-06179-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-023-06179-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-023-06179-4?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.

    References listed on IDEAS

    as
    1. Elaheh Motevali Bashi Naeini & Ali Mohammad Akhoond-Ali & Fereydoun Radmanesh & Jahangir Abedi Koupai & Shahrokh Soltaninia, 2021. "Comparison of the Calculated Drought Return Periods Using Tri-variate and Bivariate Copula Functions Under Climate Change Condition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 4855-4875, November.
    2. Oh, Dong Hwan & Patton, Andrew J., 2016. "High-dimensional copula-based distributions with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 349-366.
    3. Fenech, Jean Pierre & Vosgha, Hamed & Shafik, Salwa, 2015. "Loan default correlation using an Archimedean copula approach: A case for recalibration," Economic Modelling, Elsevier, vol. 47(C), pages 340-354.
    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. Zahra Sadat Hosseini & Mahnoosh Moghaddasi & Shahla Paimozd, 2023. "Simultaneous Monitoring of Different Drought Types Using Linear and Nonlinear Combination Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1125-1151, February.
    2. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    3. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
    4. Rubén Loaiza‐Maya & Michael S. Smith & Worapree Maneesoonthorn, 2018. "Time series copulas for heteroskedastic data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 332-354, April.
    5. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    6. Jiawei Zhou & Xiaohong Chen & Chuang Xu & Pan Wu, 2022. "Assessing Socioeconomic Drought Based on a Standardized Supply and Demand Water Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 1937-1953, April.
    7. Ting Wei & Xuehua Zhao, 2024. "Assessment of spatial–temporal variation of precipitation and meteorological drought in Shanxi province, 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. 120(6), pages 5579-5599, April.
    8. Liping Wang & Xingnan Zhang & Shufang Wang & Mohamed Khaled Salahou & Yuanhao Fang, 2020. "Analysis and Application of Drought Characteristics Based on Theory of Runs and Copulas in Yunnan, Southwest China," IJERPH, MDPI, vol. 17(13), pages 1-17, June.
    9. Sahab Zandi & Kamesh Korangi & Mar'ia 'Oskarsd'ottir & Christophe Mues & Cristi'an Bravo, 2024. "Attention-based Dynamic Multilayer Graph Neural Networks for Loan Default Prediction," Papers 2402.00299, arXiv.org, revised Jun 2024.
    10. Giuseppe Buccheri & Davide Pirino & Luca Trapin, 2021. "Managing liquidity with portfolio staleness," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 215-239, June.
    11. Bauwens, Luc & Xu, Yongdeng, 2023. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
    12. Kimia Naderi & Mahnoosh Moghaddasi & Ashkan shokri, 2022. "Drought Occurrence Probability Analysis Using Multivariate Standardized Drought Index and Copula Function Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2865-2888, June.
    13. Jianqing Fan & Donggyu Kim & Minseok Shin & Yazhen Wang, 2024. "Factor and Idiosyncratic VAR-Ito Volatility Models for Heavy-Tailed High-Frequency Financial Data," Working Papers 202415, University of California at Riverside, Department of Economics.
    14. Rewat Khanthaporn, 2022. "Analysis of Nonlinear Comovement of Benchmark Thai Government Bond Yields," PIER Discussion Papers 183, Puey Ungphakorn Institute for Economic Research.
    15. Stanislav Anatolyev & Vladimir Pyrlik, 2021. "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers wp699, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    16. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Hamori, Shigeyuki & Motegi, Kaiji & Zhang, Zheng, 2019. "Calibration estimation of semiparametric copula models with data missing at random," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 85-109.
    18. BAUWENS Luc, & XU Yongdeng,, 2019. "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE 2019025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Óskarsdóttir, María & Bravo, Cristián, 2021. "Multilayer network analysis for improved credit risk prediction," Omega, Elsevier, vol. 105(C).
    20. Christensen, Kim & Christiansen, Charlotte & Posselt, Anders M., 2020. "The economic value of VIX ETPs," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 121-138.

    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:spr:nathaz:v:120:y:2024:i:3:d:10.1007_s11069-023-06179-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.