Event-Based Rainfall-Runoff Forecasting in Pampanga River Basin, Philippines using Artificial Neural Networks (ANN)

• Published in: International Journal of Environmental and Rural Development Vol. 8; no. 1; pp. 33 - 38
• Main Authors: MALAGUIT, JCOB C., MAKAHIYA, MARRIANE F., MARK LEXTER D. DE LARA
• Format: Journal Article
• Language: English
• Published: Institute of Environmental Rehabilitation and Conservation, Research Center 2017
• Subjects: Artificial Neural Networks; event-based forecasting; Feedforward Backpropagation; rainfall-runoff model; river basin
• ISSN: 2185-159X; 2433-3700
• DOI: 10.32115/ijerd.8.1_33

This study developed a series of rainfall-runoff forecasting models that can be used in designing the flood warning system around Pampanga River Basin. The data regarding rainfall and water level of the river was obtained from the Hydrometeorological Division (HMD) of Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA). Data were collected from 2014 and 2015 hourly water level reading and rainfall reading. Feedforward Backpropagation Model, a variant of the Artificial Neural Network (ANN), was used in the study along with Gradient Descent with Adaptive Learning Rate Algorithm as a learning technique for the network. MATLAB R2009b was used to train and design the networks. A total of 45 networks were trained. Results of the training gave reasonable predictions for most of the stations with a minimum accuracy of 96%. Inaccuracy of training in some stations were attributed to the inconsistency in data and other factors.