Analysing the performance of the NARX model for forecasting the water level in the Chikugo River estuary, Japan

K Vidyalashmi; Megha Chandana L; J S Nandana; Gubash Azhikodan; K L Priya; Katsuhide Yokoyama; Suresh Kumar Paramasivam

doi:10.1016/j.envres.2024.118531

Analysing the performance of the NARX model for forecasting the water level in the Chikugo River estuary, Japan

Environ Res. 2024 Feb 27;251(Pt 1):118531. doi: 10.1016/j.envres.2024.118531. Online ahead of print.

Authors

K Vidyalashmi¹, Megha Chandana L¹, J S Nandana¹, Gubash Azhikodan², K L Priya³, Katsuhide Yokoyama⁴, Suresh Kumar Paramasivam⁵

Affiliations

¹ Department of Civil Engineering, TKM College of Engineering, Kollam, Kerala, India.
² Department of Civil and Environmental Engineering, Tokyo Metropolitan University, 1-1, Minami-Osawa, Hachioji, Tokyo, 192-0397, Japan. Electronic address: gubash@tmu.ac.jp.
³ Department of Civil Engineering, TKM College of Engineering, Kollam, Kerala, India. Electronic address: klpriyaram@gmail.com.
⁴ Department of Civil and Environmental Engineering, Tokyo Metropolitan University, 1-1, Minami-Osawa, Hachioji, Tokyo, 192-0397, Japan.
⁵ Department of Civil Engineering, University College of Engineering, Panruti, 607106, India.

PMID: 38423499
DOI: 10.1016/j.envres.2024.118531

Abstract

Estuaries are dynamic environments which are driven by various natural processes like river discharge, tides, waves, influx of saline water and sediments, etc. These ecosystems are the most sensitive to sea level rise and fluctuations in river discharge associated with climate change. A direct response of sea level rise and river discharge can be observed in the water level of estuaries. However, existing models have not considered these parameters for forecasting water level. This paper focuses on developing a water level forecast model for the Chikugo River estuary in Japan using Nonlinear Autoregressive with Exogenous inputs (NARX Model). NARX neural network was used to do the one-step-ahead prediction of water level considering the various parameters that can very well be influenced by climate change: previous water level, river discharge, and salinity. Accordingly, three models were developed: (i) Model I considering previous water level; (ii) Model II additionally considering river discharge; and (iii) Model III additionally considering salinity. All the models showed appreciable performance in forecasting the water level. Model III had the best correlation with the water level with a cross-correlation value of 0.6030, while the river discharge had only a cross-correlation of 0.1113 indicating that the Chikugo River estuary is tide-dominated. The model was trained using different combinations of available data - previous water level, river discharge, and salinity. Cross-correlation results showed a better correlation between water level and salinity than various other combinations trained. Therefore, tidal intrusion influences the water level in the estuary, thereby depicting that sea level rise can affect the water level, and its influence can be well predicted by the developed model. The water level significantly affects the flora and fauna and the predictability of future estuarine floods can help in taking necessary mitigation strategies.

Keywords: Climate change; NARX model; Saline intrusion; Time series analysis; Water level forecast.