Comparative assessment of IHACRES, AWBM, and Tank models for daily runoff simulation in wet and dry periods

Document Type : Complete scientific research article

Authors

1 M.Sc. Graduate, Dept. of Water Sciences and Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

2 Corresponding Author, Associate Prof., Dept. of Water Sciences and Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

3 Associate Prof., Dept. of Water Sciences and Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

4 Ph.D. Student, Dept. of Water Sciences and Engineering, Faculty of Agriculture, Birjand University, Birjand, Iran

5 Ph.D. Student, Dept. of Water Sciences and Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran.

Abstract

Background and objectives: Runoff is the main variable for the hydrological analysis of the watershed, and due to its importance, for several decades, hydrological research has focused on the simulation of rainfall-runoff relationships, which has led to the presentation of many models. Due to the multiplicity of hydrological models, choosing an optimal model among various models is not a simple process. For this purpose, in the present research, after selecting the Galikash watershed from the most flood-prone basins in Golestan province, the performance of three hydrological models AWBM, Tank, and IHACRES were evaluated and the parameters of the models were also analyzed for sensitivity and finally the efficiency of the models in wet and dry periods was examined.
Materials and methods: The amount of daily runoff from the watershed for a period of 30 years (1989-2019) was simulated using each of the mentioned models and using four criteria Nash-Sutcliffe evaluation coefficient, root mean square error, coefficient of determination, and mean absolute percentage error, the performance of each model has been checked in two periods of calibration and validation. After optimizing the values of all the parameters, the sensitivity of the parameters of each model has been analyzed. Finally, after specifying the drought condition with the SPI index, the performance of each model for two wet and dry periods has been investigated and evaluated.
Results: The results indicate that two rainfall-runoff models, IHACRES and AWBM, have almost similar performance. IHACRES model with Nash-Sutcliffe coefficients of 0.73 and 0.75 and RMSE of 2.97 and 2.94, respectively, in two calibration and validation periods and AWBM model with Nash-Sutcliffe coefficients of 0.74 and 0.69 and RMSE of 2.92 and 3.24 for the calibration and validation periods have shown good performance, but the Tank model was not successful in simulating the watershed runoff and its performance is lower than the two other models. The sensitivity analysis of the model parameters also showed that Kbase, H11, and f parameters are the most sensitive to the change of their values in AWBM, Tank, and IHACRES models, respectively. Finally, the comparison of the performance of the models in wet and dry periods showed that all the models have succeeded in simulating the watershed runoff with high accuracy in the wet period, so that the Nash-Sutcliffe coefficient is 0.79, 0.74 and 0.78 for the three AWBM, Tank and IHACRES models, respectively, shows the acceptable performance of the models in simulating the runoff in wet period. While the evaluation of the results has shown the poor performance of all models in dry period, and the Nash-Sutcliffe coefficient obtained for the models is -0.05, -0.45, and 0.12 respectively, which shows the weakness of the models in simulation of the low flow.
Conclusion: In the evaluation of the three hydrological models AWBM, Tank, and IHACRES in daily runoff simulation, it was found that in general, with a small difference, the IHACRES model shows better results than the AWBM model. Also, in wet periods, according to the evaluations, the AWBM model led to good accuracy, while the IHACRES model has shown better performance than other models in dry period. Considering this issue, it can be said that the models performed weaker in simulating low flows that occur during dry periods, while the knowledge of streamflow conditions during dry periods can play an effective role in managing water resources. Therefore, to increase their accuracy, a solution should be found.

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References

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Journal of Water and Soil Conservation
Volume 31, Issue 1
April 2024
Pages 51-72

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