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Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions

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  • Thelma Dede Baddoo

    (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
    College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Zhijia Li

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

  • Yiqing Guan

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

  • Kenneth Rodolphe Chabi Boni

    (College of Computer and Information Engineering, Hohai University, Nanjing 211100, China)

  • Isaac Kwesi Nooni

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
    Binjiang College, Nanjing University of Information Science & Technology, No.333 Xishan Road, Wuxi 214105, China)

Abstract

The identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data (IHACRES) model has been proven to be an efficient yet basic model to simulate rainfall–runoff processes due to the difficulty in obtaining the comprehensive data required by physical models, especially in data-scarce, semi-arid regions. The success of a calibration process is tremendously dependent on the objective function chosen. However, objective functions have been applied largely in over daily and monthly scales and seldom over sub-daily scales. This study, therefore, implements the IHACRES model using ‘hydromad’ in R to simulate flood events with data limitations in Zhidan, a semi-arid catchment in China. We apply objective function constraints by time aggregating the commonly used Nash–Sutcliffe efficiency into daily and hourly scales to investigate the influence of objective function constraints on the model performance and the general capability of the IHACRES model to simulate flood events in the study watershed. The results of the study demonstrated the advantage of the finer time-scaled hourly objective function over its daily counterpart in simulating runoff for the selected flood events. The results also indicated that the IHACRES model performed extremely well in the Zhidan watershed, presenting the feasibility of the use of the IHACRES model to simulate flood events in data scarce, semi-arid regions.

Suggested Citation

  • Thelma Dede Baddoo & Zhijia Li & Yiqing Guan & Kenneth Rodolphe Chabi Boni & Isaac Kwesi Nooni, 2020. "Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions," IJERPH, MDPI, vol. 17(11), pages 1-26, June.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:11:p:4132-:d:369474
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    References listed on IDEAS

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    1. Zeileis, Achim & Grothendieck, Gabor, 2005. "zoo: S3 Infrastructure for Regular and Irregular Time Series," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i06).
    2. Eyad Abushandi & Broder Merkel, 2013. "Modelling Rainfall Runoff Relations Using HEC-HMS and IHACRES for a Single Rain Event in an Arid Region of Jordan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2391-2409, May.
    3. Wickham, Hadley, 2007. "Reshaping Data with the reshape Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i12).
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    Cited by:

    1. Ja Bawk Marip & Xuyin Yuan & Hai Zhu & Isaac Kwesi Nooni & Solomon O. Y. Amankwah & Nana Agyemang Prempeh & Eyram Norgbey & Taitiya Kenneth Yuguda & Zaw Myo Khaing, 2020. "Spatial Distribution and Environmental Significance of Phosphorus Fractions in River Sediments and Its Influencing Factor from Hongze and Tiaoxi Watersheds, Eastern China," IJERPH, MDPI, vol. 17(16), pages 1-14, August.

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