Examination on a Forecast Model of Paddy Water Temperature Applying 2 Layer Heat-Balance Model and Weather Forecasting Data

Ponding water temperature in paddy fields is an essential factor that relates to the water management system and affects the magnitude of high-temperature damage of paddy rice. Accurate prediction of hourly water temperature dynamics continues to be a challenging task due to the immediacy of water management and the uncertainty of the meteorological forecast. We describe a forecast model of water temperature, which predicts changes per hour in water temperature using meteorological forecast data from the Meso-Spectral model provided by the Japan Meteorological Agency. The model based on two heat balance equations: for the vegetation community and the water body. LAI (leaf area index) is an important parameter to describe the thermal exchange in the vegetation community, and we estimated LAI indirectly by the hourly changes of heat budget of water body . The model was examined with field experiments in the rice-growing season from 2016 to 2018 at four different locations. The predicted water temperature at low air temperature conditions(<28°C) showed good agreement with observation data (root mean square error of 1.655°C), however, while the observed air temperature is higher than 28°C, the prediction accuracy of water temperature became low. The proposed model can predict water temperature and estimate LAI for given water depth, forecast meteorological data, which improves our understanding of the impact of climate change on the paddy field environment. Moreover, the irrigation system can be pre-managed by this method; for example, continuous irrigation can be performed when the predicted water temperature is higher than a certain threshold to protect rice from high-temperature damage.