Fuzzy Conceptual Hydrological Model for Water Flow Prediction
Tóm tắt
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.
Từ khóa
Tài liệu tham khảo
Bergstrom S (1995) The HBV model. In: Singh VP (ed) Computer models of watershed hydrology. Water Resources Publications, Littleton, pp 443–476
Chen J, Adams BJ (2006) Integration of artificial neural networks with conceptual models in rainfall-runoff modeling. J Hydrol 318(1):232–249
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
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):1619–1634
Hundecha Y, Bardossy A, WERNER HW (2001) Development of a fuzzy logic-based rainfall-runoff model. Hydrol Sci J 46(3):363–376
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
Nash J, Sutcliffe JV (1970) River flow forecasting through conceptual models part I-A discussion of principles. J Hydrol 10(3):282–290
Senbeta DA, Shamseldin AY, O’Connor KM (1999) Modification of the probability-distributed interacting storage capacity model. J Hydrol 224(3):149–168
SHW (State Hydraulic Works) (2012). 2011 Annual report, Ankara
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):2871–2888
Turan ME, Yudusev MA (2009) River flow estimation from upstream flow records by artificial intelligence methods. J Hydrol 369(1):71–77
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):4053–4068