Rainfall-Runoff relationship for streamflow discharge forecasting by ANN modelling

Abstract

Rainfall-runoff modeling has been considered as one of the major problems in water resources management, especially in most developing countries such as Thailand. Artificial Neural Network (ANN) models are powerful prediction tools for the relation between rainfall and runoff parameters. Lam Phachi watershed is located in Western Thailand. In each year, people usually undergo drought problem in dry season or flooding problem in wet season due to the influence of the monsoon leading to soil erosion and sediment deposition in the watershed. The goal of this work is to implement ANN for daily streamflow discharge forecasting in Lam Phachi watershed, Suan Phung, Rachaburi, Thailand. For model calibration and validation, two time series of rainfall and discharge are daily recorded from only one hydrologic station (K. 17) in water years 2009-2012. The data from the first three years are used as the training dataset and the last year are used as the test dataset. The results showed that the coefficient of determination (R 2 ) of ANN equal to 0.88. On the other hand, these results could be applied to solve the problems in water resource studies and management.

Methods for Hydropower Discharge Prediction: A Review

“…The implementation of ANNs to issues with water resources is quickly gaining popularity owing to their enormous strength and potential in mapping non-linear system information. ANN has been commonly used in different areas such as in modelling the water quality [88]- [90], eutrophication prediction [91]- [93], flood forecasting [25], [94]- [96], rainfall-runoff modelling [97]- [99], and storm surges prediction [100], [101]. ANN model has been implemented for discharge flow forecasting.…”

“…ANN model has been implemented for discharge flow forecasting. It had been shown that ANN can provide a high accuracy hydrological discharge flow prediction alternative in past research [24], [99], [102]. Moreover, the ANNs method is capable to forecast river flows using another neighbouring river flow information, which could be an essential tool for completing the missing flow data records [103].…”

Water flow Forecasting Methods for Optimal Water Resource Operation and Management: A Review

“…ANN model consists of a group of interconnected neurons normally organized in multiple layers. [45], [48], [49]. Additionally, ANN model has the ability to predict the river flow by using other nearby river flow information, which could be an important tool for covering the missing flow data records [50].…”

Imaging Analysis of Steel Rod Shrapnel Using Artificial Neural Networks

“…1) Reduce grey scale level, from 256 shades of grey to only 5 shades of grey which were dark, dark-grey, grey, light-grey and white by using (2).…”