Abstract
Simulation of runoff from a river catchment is a very difficult task and it involves a lot of data which need to be considered. However, the modelling is very essential to forecast the patterns of future runoff by observing and analysing previous patterns of runoff, based on the rainfall. This study presents the evaluation of rainfall-runoff modelling for the long-term runoff series using Artificial Neural Network (ANN) and Support Vector Machine (SVM). Both models are trained and validated using the data series of current and nine (9) antecedent rainfall. During the validation, the SVM model is better in the performance as compared the ANN model, with the R and RMSE values are 0.529-0.711 and 14.27-52.55 mm, respectively. However, the SVM model is underestimated for the peak discharge. Both models have the ability to derive the relationship between the inputs and outputs of the rainfall-runoff process.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IOP Conference Series: Earth and Environmental Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
