Comparing optimization methods of SIMHYD model parameters to simulate daily flow discharge in the Kouzetopraghi Watershed, Ardabil

Sharifi, Zahra; Mostafazadeh, Raoof; Esmali Ouri, Abazar; Hazbavi, Zeinab; Golshan, Mohammad

doi:10.22034/hyd.2023.49595.1617

Document Type : پژوهشی

Authors

¹ M.Sc. in Watershed Management, University of Mohaghegh Ardabili University, Ardabil, Iran

² Associate Professor, Department of Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili

³ Dept. Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

⁴ Ph.D in Watershed Management, Natural Resources and Watershed Management Office, Astara, Guilan, Iran

https://doi.org/10.22034/hyd.2023.49595.1617

Abstract

Daily flow data are a prerequisite for water resources management, but it is not possible to measure it in many upstream watersheds. In this study, different optimization algorithms have been used to evaluate the efficiency of the SIMHYD model. Therefore, the discharge data of Kouzetopraghi rive gauge station was selected as the study data (805 km2) located in Ardabil province. The daily data of rainfall, evapotranspiration of the meteorological stations in the study area were used to simulate the daily river flow data. Optimization methods including genetic algorithm, comprehensive competitive evolution, search pattern, multi-start search pattern, uniform random sampling, Rosenbrook, multi-start Rosenbrook optimization were evaluated based on statistical efficiency criteria. The mean value of discharge values by genetic algorithms, multi-year pattern search, uniform random sampling, multi-start Rosenbark, Rosenbork, comprehensive competitive evolution, search pattern were 0.031, 0.023, 0.085, 0.032, 0.024, 0.032, 0.031, respectively. The results showed that the change of optimization algorithms has a significant effect on the calibration accuracy of the model, so that the values of the Nash-Sutcliffe efficiency criteria for the employed algorithms were 0.42, 0.31, -8.55, 0.38, 0.56, 0.023, and 0.24, respectively. The Rosenbrook algorithm had higher accuracy in calibrating the SIMHYD hydrological model compared to other algorithms used. A part of the modeling error can be related to the inconsistency of precipitation and runoff data due to the multiplicity of stations.

Keywords

20.1001.1.23833254.1402.10.34.2.1

References

Aghabeigi, N., Esmali-Ouri, A., Mostafazadeh, R., Gholshan, M. (2020). The Effects of Climate Change on Runoff Using IHACRES Hydrologic Model in Some of Watersheds, Ardabil Province. Irrigation and Water Engineering, 10(2):181-192. (In Persian).

Bergstra, J., & Bengio, Y. (2012). Random search for hyper-parameter optimization. Machine Learning Research, 13, 281-305.

Bormann, B., Breuer, L., Giertz, S., Huisman, J.A., & Viney, N.R. (2009). Uncertainties in environmental modelling and consequences for policy makingpart of the series NATO science for peace and security series c: environmental security. Chapter: Spatially explicit versus lumped models in catchment hydrology–experiences from two case studies, 3-2.

Dargaribi, F., Khorsandi Kohanstani, Z., Mozayyn, M., & Arman, N. (2017). Evaluation of the efficiency of GR4J and GR2M rainfall-runoff models in Darehtakht basin runoff simulation. Watershed Engineering and Management, 9(3), 360-370. (In Persian)

Dovonec, E. (2000). A physically based distributed hydrologic model, M.Sc. Thesis. The Pennsylvania State University. 209 pp.

Esfandyari Darabad, F., Pourganji, Z., Mostafazadeh, R., & Aghaie, M. (2022). Comparison of effective rainfall conversion methods to surface runoff in flood hydrograph simulation of Nanehkaran watershed, Ardabil province. Hydrogeomorphology, 9(32), 86-63. doi: 10.22034/hyd.2022.50000.1624 (In Persian)

Franchini, M., Galeati, G., & Berra, S. (2015). Global optimization techniques for the calibration of conceptual rainfall-runoff models. Hydrological Sciences Journal, 43 (3), 443-458.

Francis, H., Chiew, S., Zhang, H., and Potter, N. )2018(. Rainfall-Runoff modelling considerations to predict stream flow characteristics in ungauged catchments and under climate change. Water, 10(10), 1319pp.

Golshan, M., Esmaili, A., & Asadi, H. (2016). Comparison of Rosenberk, Genetics, URS, SCE-UA optimization methods to determine the parameters of the SIMHYD model for flow rate simulation. Geography and environmental sustainability, 18, 67-80. (In Persian)

Gorbani, A., Hazbavi, Z., Mostafazadeh, R., & Alaie, N. (2020). Analysis of the relationship between landscape metrics and soil erosion in the KoozeTapraghi watershed. Geography and Environmental Hazards, 36, 65-90. (In Persian)

Gudarzi, M., Jabbariyanamiri, B., & Azarnivand, H. (2018). Comparison of conceptual models in river hydrological simulation. Natural environment, 71(4), 509-521. (In Persian)

Gudarzi, M., Zahbiyun, B., Msahboani, A.R., & Kamal, A.R. (2012). Comparison of the performance of three hydrological models SWAT, IHACRES and SIMHYD in simulating runoff in Qarahsu basin. Water and irrigation management, 7(1): 25-40. (In Persian)

Khavarian, H., Aghaie, M., Mostafazadeh, R. (2020). Predicting the effects of land use changes on the monthly flow using hydrological model and Remote Sensing in the Kouzetopraghi watershed, Ardabil. Hydrogeomorphology, 7(24), 19-39. doi: 10.22034/hyd.2020.37489.1512 (In Persian).

Kheirfam, H., Mostafazadeh, R., Sadeghi, S.H.R. (2013). - Daily discharge prediction using IHACRES model in some watersheds of Golestan Province. Journal of Watershed Management Research, 4(7):114-127. (In Persian).

Mohammadivand, M., Araginezhad, Sh., Ebrahimi, K., & Modaresi, F. (2019). Evaluating the Performance of Sacramento, AWBM and SimHyd Models in Simulating the Imama Basin Runoff Using Automatic Genetic Algorithm Optimization Optimizer. Iranian Soil and Water Research, 7(50), 1759-1769. (In Persian)

Moriasi, D.N., Arnold, J.G., Van Liew, M. W., Binger, R. L., Harmel, R.D., & Veith, T. L. (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885-900.

Mostafazadeh, R., Asgari, E. (2021) Performance assessment of GR4J rainfall-runoff model in daily flow simulation of Nirchai Watershed, Ardabil province. Irrigation and Water Engineering, 11(3), 79-95 (In Persian).

Piramun, N., Abdollahi, Kh, Mirabbasi Najafabadi, R., & Nekuyimehr, M. (2019). Evaluation of efficiency of TANK-SIMHYD rainfall-runoff models in Beheshtabad river flow simulation. National Conference on Rainwater Reservoir Surface Systems, Ferdowsi University of Mashhad. (In Persian)

Qi, W., Chen, J., Li, L., Xu, Ch., Li, J., Xiang, Y., & Zhang, sh. (2020). A framework to regionalize conceptual model parameters for global hydrological modeling. Hydrology and Earth System Sciences. https://doi.org/10.5194/hess-2020-127, 2020.

Razagiyan, H., Shahedi, K., Mohseni, B. (2018). Evaluating the efficiency of SIMHYD rainfall-runoff model under different climate change scenarios. Watershed Management Research Journal, 9(17), 216-224. (In Persian)

Rostamkhalaj, M., Mogaddamniya, A.R., Salmani, H., & Sepahvand, A.R. (2016). Comparative performance of precipitation-runoff models of AWBM, Sacramento, SIMHYD, SMAR, Tank. Iranian Natural Ecosystems Quarterly, 7(2), 47-63. (In Persian)

Ruhani, H., & Vafakhah, M. (2013). Automatic calibration of two precipitation models - tank runoff and SIMHYD using genetic algorithm. Rangeland and watershed management, 66(4), 521-533. (In Persian)

Sadegitebs, S., Purreza Bilandi, M., & Khazimehnezhad, H. (2015). Comparison and evaluation of global optimization methods in estimating the parameters of the daily runoff hydrological model. Irrigation Science and Engineering, 38(3), 130-142. (In Persian)

Said, M., Hyandye, C., Mjemah, I., & Komakech, H. (2021). Evaluation and prediction of the impacts of laud cover changes on hydrological processes in data constrained southern slopes of Kilimaujaro, Tauzanoa. Earth, 2, 225-247.

Sorooshian, S., Duan, Q., & Gupta, H. V. (1993). Calibration of rainfall-runoff models: application of global optimization to the Sacramento soil moisture accounting model. Advancing Earth and Space Science, 29(4), 1185-1194.

Sun, G., Wen, J., Yang, J., Hou, S., & Zhang, W. (2021). Study on hydrological process simulation of lumped hydrological model in Wujiang River Basin. Earth and Environmental Science, 826, 012-028.

Wang, G.Q., Zhang, J.Y., Pagano, T.C., Liu, Y.L., Liu, C.S., Bao, Z.X., & Jin, J.L. )2015(. Using hydrological simulation to detect human- disturbed epoch in runoff. Water Science & Technology, 71(5), 691-699.

Yu, B., & Zhu, Z. (2015). A comparative assessment of AWBM and SIMHYD for forested watershed. Hydrological Sciences Journal, 60(7-8), 1200-1212.

Zabinsky, Z. B. (2009). Random Search Algorithms, Wiley Encyclopedia of Operations. Research and Management Science.

Zhang, Y., & Chiew, F. (2009). Relative merits of different methods for runoff predictions in ungauged catchments. Water Resources Research, 45(7), 1-13.

Zhang, H., Yang, Q., Shao, J., & Wang, G.) 2019(. Dynamic stream flow simulation via online gradient-boosted regression tree. Journal of Hydrologic Engineering, 24(10), 04019041.

Zeiaei, K., esmali, A., Mostafazadeh, R., & Golshan, M. (2021). Assessing the effects of various land use change scenarios on runoff using SWAT model in the Ahl Iman watershed. Hydrogeomorphology, 8(27), 138-123. doi: 10.22034/hyd.2021.44819.1578 (In Persian)

Comparing optimization methods of SIMHYD model parameters to simulate daily flow discharge in the Kouzetopraghi Watershed, Ardabil

References

References

Volume 10, Issue 34 - Serial Number 34May 2023Pages 51-33

Volume 10, Issue 34 - Serial Number 34
May 2023
Pages 51-33