Abstract: Watering dam material in the compacting operation of rockfill dams has been a general practice to improve compaction quality. However, in the previous studies of the watering control, several questions are left unanswered, such as how to control the water volume accurately and how meteorological factors influence dam material moisture content during the construction process. Consequently, operation at the compaction starting stage is difficult to meet the requirement of design moisture content. To control the watering volume effectively, this study develops a model to predict the change of dam material moisture content considering meteorological factors, using chaotic time series and random forest regression to accurately control the watering volume. It focuses on three aspects: (1) using chaotic time series to make short-term prediction of meteorological information in a given time period; (2) developing a prediction model of moisture content change based on the random forest regression to predict the nonlinear variations in moisture content caused by meteorological factors, and validating the prediction accuracy using the ten-fold cross-verification; (3) accurately calculating the watering volume based on the predicted moisture content, the initial moisture content of dam material, the design moisture content, and the mass of dam material. Based on a practical project and its rolling and transport monitoring systems, our method is compared with the existing watering technique and verified in terms of effectiveness and accuracy. It is thought to be useful to science-based fine control on the watering volume of rockfill dam material.