Abstract

Thailand experiences severe floods and droughts that affect agriculture. New techniques, such as Data-Based-Mechanistic modelling are being developed to study rainfall and river flow to improve flood and drought alleviation policies and practices. Dynamic Harmonic Regression models are used to analyze rainfall and discharge time series across Thailand to define seasonality, trends and to forecast rainfall and discharge and their spatial distribution. Statistical patterns in the frequency of extreme rainfall and flow periods are identified with a view to improving predictions of medium and longer-term rainfall and river flow patterns. The results show temporal and spatial variation within the annual rainfall pattern in the study catchments. For example, the seasonality of the rainfall in the south is less pronounced (more equatorial). The discharge seasonal pattern shows stronger semi-annual cycles, with the weakest pattern in the south of country, whereas the strongest discharge seasonality is observed in the far north. The overall areal rainfall trend has not changed significantly over the last 20 years. Dry years can be associated with ENSO events. The discharge trend also tended to dip in ENSO years. The DHR forecasts of rainfall and river flow data for 1998-1999 using data up to 1997 have low prediction errors.