Application of ANN for coastal water quality prediction: Quang Binh case study

Abstract

The coastal areas of Quang Binh province play a crucial role not only in the economic and tourism development of the coastal province but also in the overall development of the Northern Central region. Therefore, monitoring and forecasting seawater quality in this region is vital. However, the water quality condition assessment faces many limitations due to the lack of measured data and the complication of numerical models. Meanwhile, the artificial intelligence model for simulating and predicting water quality has been widely applied due to its timely and reliable calculating abilities. This research has piloted the prediction of some water pollution parameters on the coast of Quang Binh province using an artificial neural network (ANN) model. This presents a novel approach to identifying implicit relationships between variables based on data analysis techniques via ANN. An ANN model was built to analyze the measured environmental time series data at Dong Hoi station, Quang Binh province, from 2002 to 2022. The calculation results of the training (70% of the data set, NSE: 0.81) and testing (the rest 30% of the data set, NSE: 0.5) of the model have satisfied the total coliform parameter, indicating the promise of applying the ANN model for water quality prediction.