Non-Linear Autoregressive Dissolved Oxygen Prediction Model for Paddy Irrigation Channel

Abstract

This study has proposed a non-linear autoregressive model to predict one-day ahead dissolved oxygen in paddy field irrigation channel. A 32-day data is obtained from Kampung Padang To’ La in Pasir Mas, Kelantan using off-the shelf water quality parameter sensors. Analysis has revealed no correlation between dissolved oxygen with pH and electrical conductivity. A non-linear autoregressive model is then developed using the dissolved oxygen measurements and artificial neural network. A prediction model developed using Levenberg- Marquardt algorithm yielded the best results with overall regression of 0.9253. The model has also passed all correlation tests and can therefore, be accepted.

Seasonal Variations of pH and Dissolved Oxygen Concentrations in Major Rivers of Uttar Pradesh

“…Water having a pH range outside the recommended values show signs that water contains toxic metals or chemicals due to higher pH levels [21]. Literature survey [22] shows that dissolved oxygen in water is not much responsible for change in the pH of a solution as there is no physical-chemical connection was found between the two. Major focus in the present research work is on the study of correlation and variations between pH and DO, in Pre-Monsoon, Monsoon an Autumn season for surface river water.…”