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Keywords = hydromad

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26 pages, 3441 KiB  
Article
Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions
by Thelma Dede Baddoo, Zhijia Li, Yiqing Guan, Kenneth Rodolphe Chabi Boni and Isaac Kwesi Nooni
Int. J. Environ. Res. Public Health 2020, 17(11), 4132; https://doi.org/10.3390/ijerph17114132 - 10 Jun 2020
Cited by 5 | Viewed by 3199
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, [...] Read more.
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. Full article
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13 pages, 1608 KiB  
Article
Combining an R-Based Evolutionary Algorithm and Hydrological Model for Effective Parameter Calibration
by Mun-Ju Shin and Yun Seok Choi
Water 2018, 10(10), 1339; https://doi.org/10.3390/w10101339 - 27 Sep 2018
Cited by 8 | Viewed by 3395
Abstract
The hydrological model assessment and development (hydromad) modeling package is an R-based package that can be applied to simulate hydrological models and optimize parameters. As the hydromad package is incompatible with hydrological models outside the package, the parameters of such models cannot be [...] Read more.
The hydrological model assessment and development (hydromad) modeling package is an R-based package that can be applied to simulate hydrological models and optimize parameters. As the hydromad package is incompatible with hydrological models outside the package, the parameters of such models cannot be directly optimized. Hence, we proposed a method of optimizing the hydrological-model parameters by combining the executable (EXE) file of the hydrological model with the shuffled complex evolution (SCE) algorithm provided by the hydromad package. A physically based, spatially distributed, grid-based rainfall–runoff model (GRM) was employed. By calibrating the parameters of the GRM, the performance of the model was found to be reasonable. Thus, the hydromad can be used to optimize the hydrological-model parameters outside the package if the EXE file of the hydrological model is available. The time required to optimize the parameters depends on the type of event, even for the same catchment area. Full article
(This article belongs to the Special Issue Catchment Modelling)
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