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Comparing the performances of multiple rainfall-runoff models of a karst watershed
Author(s) -
Md Moudud Hasan,
Md. Shariot-Ullah,
Ajoy Kumar Saha,
M. G. Mostofa Amin
Publication year - 2021
Publication title -
asian-australasian journal of bioscience and biotechnology
Language(s) - English
Resource type - Journals
eISSN - 2414-6293
pISSN - 2414-1283
DOI - 10.3329/aajbb.v6i1.54878
Subject(s) - watershed , surface runoff , black box , hydrology (agriculture) , environmental science , soil and water assessment tool , white box , runoff curve number , statistics , streamflow , mathematics , computer science , drainage basin , cartography , geology , geography , ecology , geotechnical engineering , machine learning , artificial intelligence , biology
Different modeling concepts, a simple (black-box) to a fully distributed modeling (white-box), were used to develop a rainfall-runoff model based on the watershed characteristics to estimate runoff at the watershed outlet. A conceptual (grey-box) model is usually a balance between the black-box and white-box model. In this study, three grey-box models were developed by varying model structures for a karst watershed. The performance of the grey-box models was evaluated and compared with a semi-distributed type (white-box) model that was developed using the Soil and Water Assessment Tool in a previous study. The evaluation was carried out using goodness-of-fit statistics and extreme flow analysis using WETSPRO (Water Engineering Time Series Processing tool). Nash-Sutcliffe efficiencies (NSE) of the grey-box models were from 0.39 to 0.77 in the calibration period and from 0.30 to 0.61 in the validation period. However, the white-box model performed better in terms of NSE but has a higher bias. The best grey-box model performed better in simulating extreme flow, whereas the white-box (SWAT) model adequately simulated daily flows. Asian Australas. J. Biosci. Biotechnol. 2021, 6 (1), 26-39

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