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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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. Nadarajah, Saralees & Kotz, Samuel, 2006. "The beta exponential distribution," Reliability Engineering and System Safety, Elsevier, vol. 91(6), pages 689-697.
    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.
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    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.

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