Analysis and predictive validity of Kelantan River flow using RQA and time series analysis

Abstract

An analysis of the Kelantan River flow for the period 2000 to 2014 and its predictive validity have been undertaken by utilizing recurrence plot (RP), recurrence quantification analysis (RQA), and auto regressive integrated moving average (ARIMA). The study presents the analysis results for flood detection and prediction of future values on a holdout sample of the 2014 data. The ARIMA model provides a better forecast when compared with the RQA predictive model. The analysis of the daily river flow dynamics reveals an abrupt change in the system and the detection of an attractor with outliers indicating higher series values; an indication of an early warning Models’ performance was based on the RMSE criterion and ARIMA model predicted a better result. The chaotic nature of the time series has also been investigated. This study could be used in understanding disastrous consequences of a river flooding.