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Article

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

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State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
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College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
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College of Computer and Information Engineering, Hohai University, Nanjing 211100, China
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School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
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Binjiang College, Nanjing University of Information Science & Technology, No.333 Xishan Road, Wuxi 214105, China
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Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(11), 4132; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17114132
Received: 18 April 2020 / Revised: 29 May 2020 / Accepted: 4 June 2020 / Published: 10 June 2020
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. View Full-Text
Keywords: data-driven modeling; objective function selection; Zhidan watershed; IHACRES; hydromad; China data-driven modeling; objective function selection; Zhidan watershed; IHACRES; hydromad; China
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MDPI and ACS Style

Baddoo, T.D.; Li, Z.; Guan, Y.; Boni, K.R.C.; Nooni, I.K. Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions. Int. J. Environ. Res. Public Health 2020, 17, 4132. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17114132

AMA Style

Baddoo TD, Li Z, Guan Y, Boni KRC, Nooni IK. Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions. International Journal of Environmental Research and Public Health. 2020; 17(11):4132. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17114132

Chicago/Turabian Style

Baddoo, Thelma D., Zhijia Li, Yiqing Guan, Kenneth R.C. Boni, and Isaac K. Nooni 2020. "Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions" International Journal of Environmental Research and Public Health 17, no. 11: 4132. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17114132

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