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The use of genetic expression programming to optimize the parameters of the Muskingum method comparison with numerical methods, Euphrates river a case study

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The Muskingham method uses two formulas to describe the translation of flow surges in a river bed. The continuity formula is the first formula, while the relationship between the reach’s storage, inflow, and outflow is the second formula (the discharge storage formula); these formulas are applied to a portion of the river between two river cross sections. Several methods can be utilized to estimate the model’s parameters. This section contrasts the conventional graphic approach with three numerical methods: Genetic algorithm, Exponential regression, and Classical fourth-order Runge-Kutta. This application’s most noticeable plus point was the need to employ a few hydrological variables, such as intake, output, and duration. The location of the Euphrates entrance to the Iraqi territory in Husaybah city was chosen with its hydrological data during the period (1993-2017) to conduct this study. The goal function is established by accuracy criterion approaches (Sum of squares error and sum of squared deviations). Depending on the simulation findings, the suggested predictive flood routing idea was highly acceptable with the prospect of adopting the Genetic Expression Programming model as a suitable and more accurate replacement to existing methods such as the Muskingum model and other numerical models, where this method gave results (R2 = 0.9984, SSQ = 1.06, SSSD = 80.75), These results achieved a hydrograph that is largely identical to what was given by the hydrological method called Muskingham.
Rocznik
Strony
507--519
Opis fizyczny
Bibliogr. 34 poz., il., tab.
Twórcy
  • Department of Civil Engineering, College of Engineering/University of Babylon, Babylon, Iraq
autor
  • Department of Building and Construction Technical, Al-Mussaib Technical College, Al-Furat Al-Awsat Technical University, Babylon, Iraq
autor
  • Department of Civil Engineering, College of Engineering/Dijlah University College, Baghdad, Iraq
  • Building and Construction Engineering Technology Department, Al-Mustaqbal University College, Hillah, Iraq
  • Al-Turath University College, Baghdad, Iraq
Bibliografia
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  • [9] M. Najafzadeh, A. Tafarojnoruz, and S.Y. Lim, “Prediction of local scour depth downstream of sluice gates using data-driven models”, ISH Journal of Hydraulic Engineering, vol. 23, no. 2, pp. 195-202, 2017, doi: 10.1080/09715010.2017.1286614.
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  • [12] S. Karkheiran, A. Kabiri-Samani, M. Zekri, and H.M. Azamathulla, “Scour at bridge piers in uniform and armored beds under steady and unsteady flow conditions using ANN-APSO and ANN-GA algorithms”, ISH Journal of Hydraulic Engineering, vol. 27, no. sup1, pp. 220-228, 2021, doi: 10.1080/09715010.2019.1617796.
  • [13] M. Esmaeili, “Prediction of scour depth around inclined bridge Piers group using optimized ANFIS system parameters with GA”, Journal of Water and Soil Conservation, vol. 22, no. 6, pp. 283-294, 2016, https://dorl.net/dor/20.1001.1.23222069.1394.22.6.18.0.
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  • [20] M.T. Ayvaz and G. Gurarslan, “A new partitioning approach for nonlinear Muskingum flood routing models with lateral flow contribution”, Journal of Hydrology, vol. 553, pp. 142-159, 2017, doi: 10.1016/j.jhydrol.2017.07.050.
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  • [22] G. Zucco, G. Tayfur, and T. Moramarco, “Reverse flood routing in natural channels using genetic algorithm”, Water Resources Management, vol. 29, no. 12, pp. 4241-4267, 2015, doi: 10.1007/s11269-015-1058-z.
  • [23] M.A. Kadhim, N.K. Al-Bedyry, and I.I. Omran, “Evaluation of flood routing models and their relationship to the hydraulic properties of the Diyala River bed”, in IOP Conference Series: Earth and Environmental Science, vol. 961, no. 1, art. no. 12058, 2022, doi: 10.1088/1755-1315/961/1/012058.
  • [24] M.A.A. Kadim, I.I. Omran, and A.A.S. Al-Taai, “Optimization of the nonlinear Muskingum model parameters for the river routing, Tigris River a case study”, International Journal of Design & Nature and Ecodynamics, vol. 16, no. 6, pp. 649-656, 2021, doi: 10.18280/ijdne.160605.
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  • [26] M. Chybiński and Ł. Polus, “Experimental and numerical investigations of laminated veneer lumber panels”, Archives of Civil Engineering, vol. 67, no. 3, pp. 351-372, 2021, doi: 10.24425/ace.2021.138060.
  • [27] D.J. Armaghani, et al., “On the use of neuro-swarm system to forecast the pile settlement”, Applied Sciences, vol. 10, no. 6, art. no. 1904, 2020, doi: 10.3390/app10061904.
  • [28] A.H. Haghiabi, H.M. Azamathulla, and A. Parsaie, “Prediction of head loss on cascade weir using ANN and SVM”, ISH Journal of Hydraulic Engineering, vol. 23, no. 1, pp. 102-110, 2017, doi: 10.1080/09715010.2016.1241724.
  • [29] H.-L. Nguyen, et al., “Development of hybrid artificial intelligence approaches and a support vector machine algorithm for predicting the marshall parameters of stone matrix asphalt”, Applied Sciences, vol. 9, no. 15, art. no. 3172, 2019, doi: 10.3390/app9153172.
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  • [31] A. Malik, A. Kumar, and O. Kisi, “Monthly pan-evaporation estimation in Indian central Himalayas using different heuristic approaches and climate based models”, Computers and Electronics in Agriculture, vol. 143, pp. 302-313, 2017, doi: 10.1016/j.compag.2017.11.008.
  • [32] S. Rost, “Water management in Mesopotamia from the sixth till the first millennium BC”, Wiley Interdisciplinary Reviews: Water, vol. 4, no. 5, art. no. e1230, 2017, doi: 10.1002/wat2.1230.
  • [33] R. Pappadà, E. Perrone, F. Durante, and G. Salvadori, “Spin-off Extreme Value and Archimedean copulas for estimating the bivariate structural risk”, Stochastic Environmental Research and Risk Assessment, vol. 30, no. 1, pp. 327-342, 2016, doi: 10.1007/s00477-015-1103-8.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2bedc043-5e56-41da-9076-b85ce7382bdd
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