Skip to main content
Erschienen in: Water Resources Management 2/2016

01.01.2016

Fuzzy Conceptual Hydrological Model for Water Flow Prediction

verfasst von: Mustafa Erkan Turan, Mehmet Ali Yurdusev

Erschienen in: Water Resources Management | Ausgabe 2/2016

Einloggen

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

search-config
loading …

Abstract

Reliability in flow prediction is key to designing water resources projects. Over prediction may result in overdesign whereas under prediction brings about insufficient capacity solutions. While the former means insufficient use of financial resources, the latter may result in some water demand unmet. Therefore, so many techniques have been developed and used to make better flow prediction. In this study, this traditional problem is revisited in an attempt to improve the modeling performance of long used conceptual hydrological models. This is attained by incorporating fuzzy systems into a presently used conceptual model. The fuzzy integration process is carried out through the replacement of the storage elements of conceptual model by fuzzy systems. The case study undertaken has proved that the fuzzy conceptual model developed is quite competitive with ordinary conceptual model and promises improved predictions.

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 Bergstrom S (1995) The HBV model. In: Singh VP (ed) Computer models of watershed hydrology. Water Resources Publications, Littleton, pp 443–476 Bergstrom S (1995) The HBV model. In: Singh VP (ed) Computer models of watershed hydrology. Water Resources Publications, Littleton, pp 443–476
Zurück zum Zitat Chen J, Adams BJ (2006) Integration of artificial neural networks with conceptual models in rainfall-runoff modeling. J Hydrol 318(1):232–249CrossRef Chen J, Adams BJ (2006) Integration of artificial neural networks with conceptual models in rainfall-runoff modeling. J Hydrol 318(1):232–249CrossRef
Zurück zum Zitat Cordón O, Herrera F (1997) Evolutionary design of TSK fuzzy rule-based systems using (μ, λ)-evolution strategies. Proc Sixth IEEE Int Conf 1:509–514 Cordón O, Herrera F (1997) Evolutionary design of TSK fuzzy rule-based systems using (μ, λ)-evolution strategies. Proc Sixth IEEE Int Conf 1:509–514
Zurück zum Zitat Corzo GA, Solomatine DP, Wit MD, Werner M, Uhlenbrook S, Price RK (2009) Combining semi-distributed process-based and data-driven models in flow simulation: a case study of the Meuse river basin. Hydrol Earth Syst Sci 13(9):1619–1634CrossRef Corzo GA, Solomatine DP, Wit MD, Werner M, Uhlenbrook S, Price RK (2009) Combining semi-distributed process-based and data-driven models in flow simulation: a case study of the Meuse river basin. Hydrol Earth Syst Sci 13(9):1619–1634CrossRef
Zurück zum Zitat Hundecha Y, Bardossy A, WERNER HW (2001) Development of a fuzzy logic-based rainfall-runoff model. Hydrol Sci J 46(3):363–376CrossRef Hundecha Y, Bardossy A, WERNER HW (2001) Development of a fuzzy logic-based rainfall-runoff model. Hydrol Sci J 46(3):363–376CrossRef
Zurück zum Zitat Mouelhi C (2003) Vers une chaîne cohé rente de modé les pluie-dé bit conceptuels globaux aux pas de temps pluriannuel, annuel, mensuel et journalier. Thé se, E’ cole nationale du gé nie rural des eaux et forêts de Paris, France, p 274 Mouelhi C (2003) Vers une chaîne cohé rente de modé les pluie-dé bit conceptuels globaux aux pas de temps pluriannuel, annuel, mensuel et journalier. Thé se, E’ cole nationale du gé nie rural des eaux et forêts de Paris, France, p 274
Zurück zum Zitat Nash J, Sutcliffe JV (1970) River flow forecasting through conceptual models part I-A discussion of principles. J Hydrol 10(3):282–290CrossRef Nash J, Sutcliffe JV (1970) River flow forecasting through conceptual models part I-A discussion of principles. J Hydrol 10(3):282–290CrossRef
Zurück zum Zitat Senbeta DA, Shamseldin AY, O’Connor KM (1999) Modification of the probability-distributed interacting storage capacity model. J Hydrol 224(3):149–168CrossRef Senbeta DA, Shamseldin AY, O’Connor KM (1999) Modification of the probability-distributed interacting storage capacity model. J Hydrol 224(3):149–168CrossRef
Zurück zum Zitat SHW (State Hydraulic Works) (2012). 2011 Annual report, Ankara SHW (State Hydraulic Works) (2012). 2011 Annual report, Ankara
Zurück zum Zitat Tian Y, Xu YP, Zhang XJ (2013) Assessment of climate change impacts on river high flows through comparative use of GR4J, HBV and xinanjiang models. Water Resour Manag 27(8):2871–2888CrossRef Tian Y, Xu YP, Zhang XJ (2013) Assessment of climate change impacts on river high flows through comparative use of GR4J, HBV and xinanjiang models. Water Resour Manag 27(8):2871–2888CrossRef
Zurück zum Zitat Turan ME, Yudusev MA (2009) River flow estimation from upstream flow records by artificial intelligence methods. J Hydrol 369(1):71–77CrossRef Turan ME, Yudusev MA (2009) River flow estimation from upstream flow records by artificial intelligence methods. J Hydrol 369(1):71–77CrossRef
Zurück zum Zitat Zhang R, Santos CA, Moreira M, Freire PK, Corte-Real J (2013) Automatic calibration of the SHETRAN hydrological modelling system using MSCE. Water Resour Manag 27(11):4053–4068CrossRef Zhang R, Santos CA, Moreira M, Freire PK, Corte-Real J (2013) Automatic calibration of the SHETRAN hydrological modelling system using MSCE. Water Resour Manag 27(11):4053–4068CrossRef
Metadaten
Titel
Fuzzy Conceptual Hydrological Model for Water Flow Prediction
verfasst von
Mustafa Erkan Turan
Mehmet Ali Yurdusev
Publikationsdatum
01.01.2016
Verlag
Springer Netherlands
Erschienen in
Water Resources Management / Ausgabe 2/2016
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-015-1183-8

Weitere Artikel der Ausgabe 2/2016

Water Resources Management 2/2016 Zur Ausgabe