Investigating different methods of estimating annual flood discharge in basins and presenting a new regression model based on physiographic features
Abstract Due to the high cost of constructing a hydrometric station, it is not possible to measure water level on all rivers. Therefore, the estimation of water flow of these rivers is one of the basic needs of water resources projects. In this research, various experimental methods presented to est...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-05-01
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| Series: | Applied Water Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s13201-025-02474-6 |
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| Summary: | Abstract Due to the high cost of constructing a hydrometric station, it is not possible to measure water level on all rivers. Therefore, the estimation of water flow of these rivers is one of the basic needs of water resources projects. In this research, various experimental methods presented to estimate the annual flood discharge in the basins, including the regression, Inglis and De’Souza and the Indian Department of Irrigation (IDOI), Turc, Coutagine, Khosla, Indian Council of Agricultural Research (ICAR), Justin and Lacey methods were examined and evaluated in a number of sub-basins of the Dareh-Rood in Ardabil province. In this research, the discharge data of 7 hydrometric stations with a common statistical period of 15 years were collected during 1380–94 and the incomplete data related to the stations were completed using statistical methods. Then, using ArcGIS and WMS software, the physiographic characteristics of the sub-basins, including the area, slope, shape factor and average height of the sub-basins were extracted. The root mean square error, relative percentage error (ε), mean absolute error (MAE), Coefficient of residual mass and model efficiency (EF) were calculated to evaluate the models. The results showed that the order of the accuracy of the methods decreases from the regression method, Coutagine, Turc, IDOI, ICAR, Lacey, JUSTIN, Inglis and De’Souza and Khosla, respectively. For the regression model, these statistics were estimated as 21.9 21.09, 0.01 and 0.1, respectively. The results showed that except for the regression model, none of the experimental methods provided reliable results and amount of runoff estimated by the regression model for different basins is in good agreement with the observed runoff data. |
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| ISSN: | 2190-5487 2190-5495 |