Comparison of Autoregressive Moving Average and State Space Methods for Monthly Time Series Modelling of Labrador and South-East Quebec River Flows


  • Carrisa Sparkes Newfoundland and Labrador Hydro
  • Leonard M. Lye Memorial University of Newfoundland
  • Susan Richter Senior Hydrotechnical Engineer (Retired)


Time series data such as monthly stream flows can be modelled using time series methods and then used to forecast flows for short term planning. Two methods of time series modelling were reviewed and compared; the well-known autoregressive moving average (ARMA) method and the State- Space Time-Series (SSTS) method.  ARMA has been used in hydrology to model and simulate flows with good results and is widely accepted for this purpose.  SSTS modelling is a method that was developed in the 1990s and is relatively unused for modelling river flow time series data. The work described in this paper focuses on modelling the stream flows from basins of different sizes using these two time series modelling methods and comparing the results.  Three rivers in Labrador and South-East Quebec were modelled; the Romaine, Ugjoktok and Alexis Rivers.  These rivers are located in various areas of the study region, having different drainage aspects and differing basin sizes.  Both models were compared for accuracy of prediction, ease of software use and simplicity of model to determine the preferred time series methodology approach for modelling these rivers.

Author Biographies

Carrisa Sparkes, Newfoundland and Labrador Hydro


Leonard M. Lye, Memorial University of Newfoundland

Professor and Associate Dean Faculty of Engineering and Applied Science

Susan Richter, Senior Hydrotechnical Engineer (Retired)

Retired Senior Hydrotechnical Engineer






Environmental Modeling, Risk Assessment and Decision Making (EMR)