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

Document Type : Research Article

Authors

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

Abstract

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.

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References

[1] V. Chow, D. Maidment, L. Mays, Applied hydrology McGraw-Hill International editions, New York, USA,  (1988).
[2] A. Alizadeh, Principles of applied hydrology, Mashhad: Emam Reza University,  (2008). (in persian).
[3] F.N. Madden, K.R. Godfrey, M.J. Chappell, R. Hovorka, R.A. Bates, A comparison of six deconvolution techniques, Journal of pharmacokinetics and biopharmaceutics, 24 (1996) 283-299.
[4] H. Saba, M. Kamalian, I. Raeisizadeh, Determining impending slip of slop and optimized embankment operation volume of earth dams using a combination of neural networks and genetic algorithms, Amirkabir Journal of Civil Engineering, 50(4) (2018) 233-234. (in persian).
[5] F. Masoumi, S.N. Bashi-Azghadi, A. Afshar, Application of Achieve-Based Genetic Algorithm for Consequence Management of Contaminant Entering in Water Distribution Networks, Amirkabir Journal of Civil Engineering, 53(8) (2021) 3593-3604. (in persian).
[6] S. Sadeghi, J. Samani, H. Samani, Optimal Design of Storm Sewer Network Based on Risk Analysis by Combining Genetic Algorithm and SWMM Model, Amirkabir Journal of Civil Engineering, 54(5) (2022) 1903-1924. (in persian).
[7] S.-H. Dong, Genetic algorithm based parameter estimation of Nash model, Water resources management, 22 (2008) 525-533.
[8] J. Drisya, D. Sathish Kumar, Automated calibration of a two-dimensional overland flow model by estimating Manning's roughness coefficient using genetic algorithm, Journal of Hydroinformatics, 20(2) (2018) 440-456.
[9] S. Farzin, H. Noori, H. Karami, Developing the performance of modern methods using multi-objective optimization in urban runoff control, Iran-Water Resources Research, 14(3) (2018) 45-58. (in persian).
[10] H. Nouri, A. Ildoromi, M. Sepehri, M. Artimani, Comparing Three Main Methods of Artificial Intelligence in Flood Estimation in Yalphan Catchment, Geography and Environmental Planning, 29(4) (2019) 35-50. (in persian).
[11] A.M. Melesse, W.D. Graham, J.D. Jordan, Spatially distributed watershed mapping and modeling: GIS-based storm runoff response and hydrograph analysis: Part 2, Journal of Spatial Hydrology, 3(2) (2003) 1-28.
[12] B. Saghafian, A. Shokouhi, A corrected time-area technique for one-dimensional flow, International Journal of Civil Engineering, 4(1) (2006) 34-41.
[13] M. Zakeri Niri, B. Saghafian, S. Golian, T. Moramarco, A. Shamsai, Derivation of travel time based on diffusive wave approximation for the time-area hydrograph simulation, Journal of Hydrologic Engineering, 17(1) (2012) 85-91.
[14] T. Sabzevari, S. Noroozpour, M. Pishvaei, Effects of geometry on runoff time characteristics and time-area histogram of hillslopes, Journal of Hydrology, 531 (2015) 638-648.
[15] S. Sadeghi, R. Mostafazadeh, A. Sadoddin, Changeability of simulated hydrograph from a steep watershed resulted from applying Clark’s IUH and different time–area histograms, Environmental Earth Sciences, 74 (2015) 3629-3643.
[16] Y. Her, C. Heatwole, HYSTAR Sediment Model: Distributed Two‐Dimensional Simulation of Watershed Erosion and Sediment Transport Using Time‐Area Routing, JAWRA Journal of the American Water Resources Association, 52(2) (2016) 376-396.
[17] B. Saghafian, A.M. Van Lieshout, H.M. Rajaei, Distributed catchment simulation using a raster GIS, International Journal of Applied Earth Observation and Geoinformation, 2(3-4) (2000) 199-203.
[18] J. Chabokpour, Operation of the non-linear Muskingum model in the prediction of the pollution breakthrough curves through the river reaches, Amirkabir Journal of Civil Engineering, 54(1) (2022) 21-34. (in persian).
[19] M. Mohammadi Hashemi, B. Saghafian, M. Zakeri Niri, M. Najarchi, Applicability of Rainfall–Runoff Models in Two Simplified Watersheds, Iranian Journal of Science and Technology, Transactions of Civil Engineering,  (2021) 1-12.
[20] S.K. Singh, Identifying representative parameters of IUH, Journal of irrigation and drainage engineering, 133(6) (2007) 602-608.
[21] S.K. Singh, Optimal instantaneous unit hydrograph from multistorm data, Journal of irrigation and drainage engineering, 132(3) (2006) 298-302.
[22] Y. Xiong, C.S. Melching, Comparison of kinematic-wave and nonlinear reservoir routing of urban watershed runoff, Journal of Hydrologic Engineering, 10(1) (2005) 39-49.
[23] J. Liang, C.S. Melching, Experimental evaluation of the effect of storm movement on peak discharge, International Journal of Sediment Research, 30(2) (2015) 167-177.
[24] D.E. Overton, M.E. Meadows, Stormwater modeling, Elsevier, 2013.
[25] A.D. Feldman, Hydrologic modeling system HEC-HMS: technical reference manual, US Army Corps of Engineers, Hydrologic Engineering Center, 2000.
[26] USDA, United States Department of Agriculture, in, Agricultural Research Service, 2007.
[27] B. Zahraee, S.M. Hoseini, Genetic Algorithm and Engineering Optimization, Gutenberg publication, 2014.
Amirkabir Journal of Civil Engineering
Volume 55, Issue 6
September 2023
Pages 1159-1178

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