Neural Networks and Wavelet Conjunction Model for Intermittent Streamflow Forecasting

Intermittent streamflow estimates are important for water quality management, planning water supplies, hydropower, and irrigation systems. This paper proposes the application of a conjunction model (neurowavelet) for forecasting daily intermittent streamflow. The neurowavelet conjunction model is improved by combining two methods, discrete wavelet transform and artificial neural networks (ANN), for 1 day ahead streamflow forecasting and results are compared with those of the single ANN model. Intermittent streamflow data from two stations in the Thrace Region, the European part of Turkey, in the northwest part of the country are used in the study. The comparison results revealed that the suggested model could significantly increase the forecast accuracy of single ANN in forecasting daily intermittent streamflows. The neurowavelet conjunction model reduced the prediction root mean square errors and mean absolute errors with respect to the single ANN model by 74–65% and 43–12%, and increased the determinati...

[1]  Jorge J. Moré,et al.  The Levenberg-Marquardt algo-rithm: Implementation and theory , 1977 .

[2]  Thomas A. McMahon,et al.  Stochastic generation of monthly flows for ephemeral streams , 1980 .

[3]  R. Srikanthan,et al.  Stochastic time series modelling of arid zone streamflows / Modèle stochastique des séries des temps élémentaires des valeurs d'écoulement total dans une zone aride , 1980 .

[4]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Nachimuthu Karunanithi,et al.  Neural Networks for River Flow Prediction , 1994 .

[6]  Jason Smith,et al.  Neural-Network Models of Rainfall-Runoff Process , 1995 .

[7]  A. Shamseldin.  Application of a neural network technique to rainfall-runoff modelling , 1997 .

[8]  Christian W. Dawson,et al.  An artificial neural network approach to rainfall-runoff modelling , 1998 .

[9]  Laurence C. Smith,et al.  Stream flow characterization and feature detection using a discrete wavelet transform , 1998 .

[10]  Slobodan P. Simonovic,et al.  Short term streamflow forecasting using artificial neural networks , 1998 .

[11]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[12]  A. Tokar,et al.  Rainfall-Runoff Modeling Using Artificial Neural Networks , 1999 .

[13]  H. Aksoy,et al.  A model for daily flows of intermittent streams , 2000 .

[14]  Chun-tian Cheng,et al.  FUZZY ITERATION METHODOLOGY FOR RESERVOIR FLOOD CONTROL OPERATION 1 , 2001 .

[15]  Yen-Chang Chen,et al.  A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction , 2001 .

[16]  Andrew Metcalfe,et al.  Bivariate stochastic modelling of ephemeral streamflow , 2002 .

[17]  Bellie Sivakumar,et al.  River flow forecasting: use of phase-space reconstruction and artificial neural networks approaches , 2002 .

[18]  K. P. Sudheer,et al.  Modelling evaporation using an artificial neural network algorithm , 2002 .

[19]  K. P. Sudheer,et al.  A data‐driven algorithm for constructing artificial neural network rainfall‐runoff models , 2002 .

[20]  Juan B. Valdés,et al.  NONLINEAR MODEL FOR DROUGHT FORECASTING BASED ON A CONJUNCTION OF WAVELET TRANSFORMS AND NEURAL NETWORKS , 2003 .

[21]  Ping Wang,et al.  Multiscale characteristics of the rainy season rainfall and interdecadal decaying of summer monsoon in North China , 2003 .

[22]  S. Jain,et al.  Radial Basis Function Neural Network for Modeling Rating Curves , 2003 .

[23]  Hikmet Kerem Cigizoglu,et al.  Estimation, forecasting and extrapolation of river flows by artificial neural networks , 2003 .

[24]  Ozgur Kisi,et al.  River Flow Modeling Using Artificial Neural Networks , 2004 .

[25]  Chien-Ming Chou,et al.  Application of wavelet‐based multi‐model Kalman filters to real‐time flood forecasting , 2004 .

[26]  F. Anctil,et al.  An exploration of artificial neural network rainfall-runoff forecasting combined with wavelet decomposition , 2004 .

[27]  Paulin Coulibaly,et al.  Wavelet analysis of variability in annual Canadian streamflows , 2004 .

[28]  Hikmet Kerem Cigizoglu,et al.  Application of Generalized Regression Neural Networks to Intermittent Flow Forecasting and Estimation , 2005 .

[29]  Yan Li,et al.  Comparison of Several Flood Forecasting Models in Yangtze River , 2005 .

[30]  Chuntian Cheng,et al.  Long-Term Prediction of Discharges in Manwan Hydropower Using Adaptive-Network-Based Fuzzy Inference Systems Models , 2005, ICNC.

[31]  Chuntian Cheng,et al.  Using support vector machines for long-term discharge prediction , 2006 .

[32]  Mohamed Nasr Allam,et al.  Rainfall‐runoff modelling using artificial neural networks technique: a Blue Nile catchment case study , 2006 .

[33]  Turgay Partal,et al.  Long-term trend analysis using discrete wavelet components of annual precipitations measurements in Marmara region (Turkey) , 2006 .

[34]  Kwok-wing Chau,et al.  Particle Swarm Optimization Training Algorithm for ANNs in Stage Prediction of Shing Mun River , 2006 .

[35]  G. Sahoo,et al.  Flow forecasting for a Hawaii stream using rating curves and neural networks , 2006 .

[36]  Ozgur Kisi,et al.  Streamflow Forecasting Using Different Artificial Neural Network Algorithms , 2007 .

[37]  Ozgur Kisi,et al.  Comparison of different ANN techniques in river flow prediction , 2007 .

[38]  Ozgur Kisi,et al.  Stream flow forecasting using neuro‐wavelet technique , 2008 .