A Comparison of Multivariate and Univariate Time Series Models Applied in Tree Sap Flux Analyses

Abstract

AbstractAccurate model predictions of the tree sap flux in sapwood are critical for forestry water management, primarily due to data availability limitations. Time series models have been used in tree sap flux analyses since 2005. Classic autoregressive models such as the ARIMA (autoregressive integrated moving average), ARIMAX (ARIMA with exogenous variables), SARIMA (seasonal ARIMA) and SARIMAX (seasonal ARIMAX) models are designed and tested for two common exotic species (Eucalyptus citriodora Hook. f. and Acacia auriculaeformis A. Chun) in dry and wet seasons in South China. The performance of the models is assessed with a scoring system for integrating six statistical indices. The results show that taking both seasonal term and exogenous variables into account could improve day sap flux prediction accuracy.