Skip to main content
Erschienen in: Water Resources Management 14/2018

20.08.2018

Investigation the Effect of Using Variable Values for the Parameters of the Linear Muskingum Method Using the Particle Swarm Algorithm (PSO)

verfasst von: Jalal Bazargan, Hadi Norouzi

Erschienen in: Water Resources Management | Ausgabe 14/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Flood routing is a technique to determine the flood hydrograph at a point of downstream where is of great importance and flood-induced risks can cause irreparable damages. Routing methods can be classified into two categories: hydraulic routing and hydrologic routing. Hydrologic methods are less accurate than hydraulic methods but they are widely used for engineering of rivers due to simplicity and being acceptable. Muskingum is a simple, widely used hydrologic method in the flood routing. In present study, accuracy of the linear Muskingum method has been evaluated using the Particle Swarm Optimization (PSO) algorithm in a Karun River reach bounded to the Mollasani hydrometric station and Ahwaz station upstream and downstream of the river, respectively. The results suggest that if three distinct values rather than constant values are used for X, K, ∆푡 parameters in the Muskingum method, the accuracy of computed outflow will be increased particularly in the peak section of hydrograph so that the Mean Relative Error (MRE) of the peak hydrograph section was 2.44% when constants were. However, in the case of using three different values for these parameters, the error value reached 0.89%.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Al-Humoud JM, Esen II (2006) Approximate methods for the estimation of Muskingum flood routing parameters. Water Resour Manag 20(6):979–990CrossRef Al-Humoud JM, Esen II (2006) Approximate methods for the estimation of Muskingum flood routing parameters. Water Resour Manag 20(6):979–990CrossRef
Zurück zum Zitat Ayvaz MT, Gurarslan G (2017) A new partitioning approach for nonlinear Muskingum flood routing models with lateral flow contribution. J Hydrol 553:142–159CrossRef Ayvaz MT, Gurarslan G (2017) A new partitioning approach for nonlinear Muskingum flood routing models with lateral flow contribution. J Hydrol 553:142–159CrossRef
Zurück zum Zitat Barati R (2011) Parameter estimation of nonlinear Muskingum models using Nelder-mead simplex algorithm. J Hydrol Eng 16(11):946–954CrossRef Barati R (2011) Parameter estimation of nonlinear Muskingum models using Nelder-mead simplex algorithm. J Hydrol Eng 16(11):946–954CrossRef
Zurück zum Zitat Choudhury P, Shrivastava RK, Narulkar SM (2002) Flood routing in river networks using equivalent Muskingum inflow. J Hydrol Eng 7(6):413–419CrossRef Choudhury P, Shrivastava RK, Narulkar SM (2002) Flood routing in river networks using equivalent Muskingum inflow. J Hydrol Eng 7(6):413–419CrossRef
Zurück zum Zitat Chow, Vente (1959) open channel hydraulics, Newyork;Macgraw-Hill book company Chow, Vente (1959) open channel hydraulics, Newyork;Macgraw-Hill book company
Zurück zum Zitat Chu HJ, Chang LC (2009) Applying particle swarm optimization to parameter estimation of the nonlinear Muskingum model. J Hydrol Eng 14(9):1024–1027CrossRef Chu HJ, Chang LC (2009) Applying particle swarm optimization to parameter estimation of the nonlinear Muskingum model. J Hydrol Eng 14(9):1024–1027CrossRef
Zurück zum Zitat Di Cesare N, Chamoret D, Domaszewski M (2015) A new hybrid PSO algorithm based on a stochastic Markov chain model. Adv Eng Softw 90:127–137CrossRef Di Cesare N, Chamoret D, Domaszewski M (2015) A new hybrid PSO algorithm based on a stochastic Markov chain model. Adv Eng Softw 90:127–137CrossRef
Zurück zum Zitat Eberhart R, Kennedy J (1995). A new optimizer using particle swarm theory. In Micro Machine and Human Science, 1995. MHS'95., Proceedings of the Sixth International Symposium on (pp. 39–43). IEEE Eberhart R, Kennedy J (1995). A new optimizer using particle swarm theory. In Micro Machine and Human Science, 1995. MHS'95., Proceedings of the Sixth International Symposium on (pp. 39–43). IEEE
Zurück zum Zitat Haddad OB, Hamedi F, Orouji H, Pazoki M, Loáiciga HA (2015) A re-parameterized and improved nonlinear Muskingum model for flood routing. Water Resour Manag 29(9):3419–3440CrossRef Haddad OB, Hamedi F, Orouji H, Pazoki M, Loáiciga HA (2015) A re-parameterized and improved nonlinear Muskingum model for flood routing. Water Resour Manag 29(9):3419–3440CrossRef
Zurück zum Zitat Kang L, Zhou L, Zhang S (2017) Parameter estimation of two improved nonlinear Muskingum models considering the lateral flow using a hybrid algorithm. Water Resour Manag 31(14):4449–4467CrossRef Kang L, Zhou L, Zhang S (2017) Parameter estimation of two improved nonlinear Muskingum models considering the lateral flow using a hybrid algorithm. Water Resour Manag 31(14):4449–4467CrossRef
Zurück zum Zitat Latt ZZ (2015) Application of feedforward artificial neural network in Muskingum flood routing: a black-box forecasting approach for a natural river system. Water Resour Manag 29(14):4995–5014CrossRef Latt ZZ (2015) Application of feedforward artificial neural network in Muskingum flood routing: a black-box forecasting approach for a natural river system. Water Resour Manag 29(14):4995–5014CrossRef
Zurück zum Zitat McCarthy G. T. (1938). The unit hydrograph and flood routing. New London. Conference North Atlantic Division. US Army Corps of Engineers. New London. Conn. USA McCarthy G. T. (1938). The unit hydrograph and flood routing. New London. Conference North Atlantic Division. US Army Corps of Engineers. New London. Conn. USA
Zurück zum Zitat Moghaddam A, Behmanesh J, Farsijani A (2016) Parameters estimation for the new four-parameter nonlinear Muskingum model using the particle swarm optimization. Water Resour Manag 30(7):2143–2160CrossRef Moghaddam A, Behmanesh J, Farsijani A (2016) Parameters estimation for the new four-parameter nonlinear Muskingum model using the particle swarm optimization. Water Resour Manag 30(7):2143–2160CrossRef
Zurück zum Zitat Niazkar M, Afzali SH (2016) Application of new hybrid optimization technique for parameter estimation of new improved version of Muskingum model. Water Resour Manag 30(13):4713–4730CrossRef Niazkar M, Afzali SH (2016) Application of new hybrid optimization technique for parameter estimation of new improved version of Muskingum model. Water Resour Manag 30(13):4713–4730CrossRef
Zurück zum Zitat Perumal M, Price RK (2013) A fully mass conservative variable parameter McCarthy–Muskingum method: theory and verification. J Hydrol 502:89–102CrossRef Perumal M, Price RK (2013) A fully mass conservative variable parameter McCarthy–Muskingum method: theory and verification. J Hydrol 502:89–102CrossRef
Zurück zum Zitat Perumal M, Tayfur G, Rao CM, Gurarslan G (2017) Evaluation of a physically based quasi-linear and a conceptually based nonlinear Muskingum methods. J Hydrol 546:437–449CrossRef Perumal M, Tayfur G, Rao CM, Gurarslan G (2017) Evaluation of a physically based quasi-linear and a conceptually based nonlinear Muskingum methods. J Hydrol 546:437–449CrossRef
Zurück zum Zitat Samani HM, Shamsipour GA (2004) Hydrologic flood routing in branched river systems via nonlinear optimization. J Hydraul Res 42(1):55–59CrossRef Samani HM, Shamsipour GA (2004) Hydrologic flood routing in branched river systems via nonlinear optimization. J Hydraul Res 42(1):55–59CrossRef
Zurück zum Zitat Shi, Y., & Eberhart, R. (1998). A modified particle swarm optimizer. In Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on (pp. 69–73). IEEE Shi, Y., & Eberhart, R. (1998). A modified particle swarm optimizer. In Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on (pp. 69–73). IEEE
Zurück zum Zitat Subramanya K (1994) Engineering hydrology. 2nd ed Subramanya K (1994) Engineering hydrology. 2nd ed
Zurück zum Zitat Tsai CW (2005) Flood routing in mild-sloped rivers—wave characteristics and downstream backwater effect. J Hydrol 308(1):151–167CrossRef Tsai CW (2005) Flood routing in mild-sloped rivers—wave characteristics and downstream backwater effect. J Hydrol 308(1):151–167CrossRef
Zurück zum Zitat Vafakhah M, Dastorani A, Moghaddam Nia A (2015) Optimal parameter estimation for nonlinear Muskingum model based on artificial bee Colony algorithm. ECOPERSIA 3(1):847–865 Vafakhah M, Dastorani A, Moghaddam Nia A (2015) Optimal parameter estimation for nonlinear Muskingum model based on artificial bee Colony algorithm. ECOPERSIA 3(1):847–865
Zurück zum Zitat Yuan X, Wu X, Tian H, Yuan Y, Adnan RM (2016) Parameter identification of nonlinear Muskingum model with backtracking search algorithm. Water Resour Manag 30(8):2767–2783CrossRef Yuan X, Wu X, Tian H, Yuan Y, Adnan RM (2016) Parameter identification of nonlinear Muskingum model with backtracking search algorithm. Water Resour Manag 30(8):2767–2783CrossRef
Metadaten
Titel
Investigation the Effect of Using Variable Values for the Parameters of the Linear Muskingum Method Using the Particle Swarm Algorithm (PSO)
verfasst von
Jalal Bazargan
Hadi Norouzi
Publikationsdatum
20.08.2018
Verlag
Springer Netherlands
Erschienen in
Water Resources Management / Ausgabe 14/2018
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-018-2082-6

Weitere Artikel der Ausgabe 14/2018

Water Resources Management 14/2018 Zur Ausgabe