IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i6p3588-d522916.html
   My bibliography  Save this article

Seamless Integration of Rainfall Spatial Variability and a Conceptual Hydrological Model

Author

Listed:
  • Yan Zhou

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Zhongmin Liang

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Binquan Li

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Yixin Huang

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Kai Wang

    (Bureau of Hydrology, The Huaihe River Commission of the Ministry of Water Resources, Bengbu 233001, China)

  • Yiming Hu

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

Abstract

Rainfall is an important input to conceptual hydrological models, and its accuracy would have a considerable effect on that of the model simulations. However, traditional conceptual rainfall-runoff models commonly use catchment-average rainfall as inputs without recognizing its spatial variability. To solve this, a seamless integration framework that couples rainfall spatial variability with a conceptual rainfall-runoff model, named the statistical rainfall-runoff (SRR) model, is built in this study. In the SRR model, the exponential difference distribution (EDD) is proposed to describe the spatial variability of rainfall for traditional rain gauging stations. The EDD is then incorporated into the vertically mixed runoff (VMR) model to estimate the statistical runoff component. Then, the stochastic differential equation is adopted to deal with the flow routing under stochastic inflow. To test the performance, the SRR model is then calibrated and validated in a Chinese catchment. The results indicate that the EDD performs well in describing rainfall spatial variability, and that the SRR model is superior to the Xinanjiang model because it provides more accurate mean simulations. The seamless integration framework considering rainfall spatial variability can help build a more reasonable statistical rainfall-runoff model.

Suggested Citation

  • Yan Zhou & Zhongmin Liang & Binquan Li & Yixin Huang & Kai Wang & Yiming Hu, 2021. "Seamless Integration of Rainfall Spatial Variability and a Conceptual Hydrological Model," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3588-:d:522916
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/6/3588/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/6/3588/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohammad Rezaie-Balf & Zahra Zahmatkesh & Sungwon Kim, 2017. "Soft Computing Techniques for Rainfall-Runoff Simulation: Local Non–Parametric Paradigm vs. Model Classification Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 3843-3865, September.
    2. Peng Qi & Y. Jun Xu & Guodong Wang, 2020. "Quantifying the Individual Contributions of Climate Change, Dam Construction, and Land Use/Land Cover Change to Hydrological Drought in a Marshy River," Sustainability, MDPI, vol. 12(9), pages 1-16, May.
    3. Nadarajah, Saralees & Kotz, Samuel, 2006. "The beta exponential distribution," Reliability Engineering and System Safety, Elsevier, vol. 91(6), pages 689-697.
    4. Meng-Xuan Jie & Hua Chen & Chong-Yu Xu & Qiang Zeng & Jie Chen & Jong-Suk Kim & Sheng-lian Guo & Fu-Qiang Guo, 2018. "Transferability of Conceptual Hydrological Models Across Temporal Resolutions: Approach and Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1367-1381, March.
    5. Binquan Li & Zhongmin Liang & Qingrui Chang & Wei Zhou & Huan Wang & Jun Wang & Yiming Hu, 2020. "On the Operational Flood Forecasting Practices Using Low-Quality Data Input of a Distributed Hydrological Model," Sustainability, MDPI, vol. 12(19), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenlin Yuan & Lu Lu & Hanzhen Song & Xiang Zhang & Linjuan Xu & Chengguo Su & Meiqi Liu & Denghua Yan & Zening Wu, 2022. "Study on the Early Warning for Flash Flood Based on Random Rainfall Pattern," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(5), pages 1587-1609, March.

    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. Mahmoud Aldeni & Carl Lee & Felix Famoye, 2017. "Families of distributions arising from the quantile of generalized lambda distribution," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-18, December.
    2. Ali Genç, 2013. "A skew extension of the slash distribution via beta-normal distribution," Statistical Papers, Springer, vol. 54(2), pages 427-442, May.
    3. Abdus Saboor & Muhammad Nauman Khan & Gauss M. Cordeiro & Marcelino A. R. Pascoa & Juliano Bortolini & Shahid Mubeen, 2019. "Modified beta modified-Weibull distribution," Computational Statistics, Springer, vol. 34(1), pages 173-199, March.
    4. Alexander, Carol & Cordeiro, Gauss M. & Ortega, Edwin M.M. & Sarabia, José María, 2012. "Generalized beta-generated distributions," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1880-1897.
    5. Gauss Cordeiro & Elizabeth Hashimoto & Edwin Ortega & Marcelino Pascoa, 2012. "The McDonald extended distribution: properties and applications," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 409-433, July.
    6. Qinghe Zhao & Shengyan Ding & Xiaoyu Ji & Zhendong Hong & Mengwen Lu & Peng Wang, 2021. "Relative Contribution of the Xiaolangdi Dam to Runoff Changes in the Lower Yellow River," Land, MDPI, vol. 10(5), pages 1-21, May.
    7. Gauss M. Cordeiro & Giovana O. Silva & Edwin M. M. Ortega, 2016. "An extended-G geometric family," Journal of Statistical Distributions and Applications, Springer, vol. 3(1), pages 1-16, December.
    8. Yaoting Yang & Weizhong Tian & Tingting Tong, 2021. "Generalized Mixtures of Exponential Distribution and Associated Inference," Mathematics, MDPI, vol. 9(12), pages 1-22, June.
    9. Zakeia A. Al-saiary & Rana A. Bakoban & Areej A. Al-zahrani, 2019. "Characterizations of the Beta Kumaraswamy Exponential Distribution," Mathematics, MDPI, vol. 8(1), pages 1-12, December.
    10. Wagner Barreto-Souza & Vinícius Diniz Mayrink, 2019. "Semiparametric generalized exponential frailty model for clustered survival data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(3), pages 679-701, June.
    11. Elizabeth Hashimoto & Gauss Cordeiro & Edwin Ortega, 2013. "The new Neyman type A beta Weibull model with long-term survivors," Computational Statistics, Springer, vol. 28(3), pages 933-954, June.
    12. Mashail M. AL Sobhi, 2020. "The Inverse-Power Logistic-Exponential Distribution: Properties, Estimation Methods, and Application to Insurance Data," Mathematics, MDPI, vol. 8(11), pages 1-15, November.
    13. Amir Molajou & Vahid Nourani & Abbas Afshar & Mina Khosravi & Adam Brysiewicz, 2021. "Optimal Design and Feature Selection by Genetic Algorithm for Emotional Artificial Neural Network (EANN) in Rainfall-Runoff Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2369-2384, June.
    14. Hengxu Jin & Xiaoping Rui & Xiaoyan Li, 2022. "Analysing the Performance of Four Hydrological Models in a Chinese Arid and Semi-Arid Catchment," Sustainability, MDPI, vol. 14(6), pages 1-15, March.
    15. Joško Trošelj & Han Soo Lee & Lena Hobohm, 2023. "Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations," Sustainability, MDPI, vol. 15(18), pages 1-33, September.
    16. Majdah Badr & Muhammad Ijaz, 2021. "The Exponentiated Exponential Burr XII distribution: Theory and application to lifetime and simulated data," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-20, March.
    17. Hassan S. Bakouch & Abdus Saboor & Muhammad Nauman Khan, 2021. "Modified Beta Linear Exponential Distribution with Hydrologic Applications," Annals of Data Science, Springer, vol. 8(1), pages 131-157, March.
    18. Almalki, Saad J. & Nadarajah, Saralees, 2014. "Modifications of the Weibull distribution: A review," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 32-55.
    19. Abdulhakim A. Al-Babtain & Mohammed K. Shakhatreh & Mazen Nassar & Ahmed Z. Afify, 2020. "A New Modified Kies Family: Properties, Estimation Under Complete and Type-II Censored Samples, and Engineering Applications," Mathematics, MDPI, vol. 8(8), pages 1-24, August.
    20. Emrah Altun & Mustafa Ç. Korkmaz & Mahmoud El-Morshedy & Mohamed S. Eliwa, 2021. "A New Flexible Family of Continuous Distributions: The Additive Odd-G Family," Mathematics, MDPI, vol. 9(16), pages 1-17, 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:13:y:2021:i:6:p:3588-:d:522916. 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.