Evaluation of Combined Method of Deconvolution- Genetic Algorithm in Extracting Time-Area Histogram

Document Type : Research Article


1 Ph.D. candidate, Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran

2 Professor. Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

3 Associate professor. Department of Civil Engineering, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran

4 Associate professor, Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran


Runoff production is due to watershed response to rainfall events. Various research has been performed to accurately determine the watershed response. In most response models, as in kinematic wave-based models, require detailed input data such as cover characteristics, slope, initial moisture, and soil infiltration properties. In this study, a time-area histogram extraction technique was presented via genetic algorithm optimization and deconvolution methods and results were evaluated in theoretical and real watersheds. In the model presented, a set of rainfall-runoff events in matrix form were called as inputs while the corresponding time-area diagrams were extracted. The results showed that the accuracy of the model in estimating the response of a theoretical watershed was 99%, while similar accuracy in the direct approach was 74%. The accuracy of the model in estimating the response of the V-shaped geometric watershed and the real Walnut Gulch watershed reached an average of 99%. Therefore, the model introduced in this research is effective in determining the time-area diagram of the V-shaped watershed and may be used in other basins.


Main Subjects

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