Development of Rice Paddy Model Based on Noah LSM: Consistent Parameterization of Subcanopy Resistance from the Ponded Water to Dense Rice Canopy

We developed a rice paddy model based on Noah land surface model (LSM) considering the standing water layer during the irrigation periods. In the model, we adopted a consistent subcanopy process from thin to thick canopy conditions and considered a small scalar roughness length of the water surface in the rice paddy fields. We evaluated the performance of the model using observations from three rice paddy sites with different leaf area index and water depth in Japan during the growing season. Two simulations were performed in an offline mode: a Noah LSM simulation with saturated soil moisture in the top two soil layers (IRRI) and a rice paddy model simulation (RICE). The average root mean squared errors of ground, sensible, and latent heat fluxes, and first soil layer temperature decreased by 20%, 16%, 17%, and 31%, respectively in the RICE simulation, compared to the IRRI simulation. The better performance of the RICE simulation was attributed to the consideration of the heat storage of the standing water layer during the irrigation periods and the realistic energy partitioning by the single-canopy model during the non-irrigation periods. Two sensitivity tests were performed related to the roughness length of the water and the constant mean water depth. When the small roughness length of the water surface during the irrigation periods was not considered, the subcanopy resistance decreased, which resulted in a cold bias in the daily mean ground and soil temperature and an overestimation of the daily mean latent heat flux under low leaf area index conditions. The use of constant mean water depth in the model did not significantly change simulated surface fluxes and ground and first soil layer temperature, implying that detailed information on temporally changing water depth is less important in the simulation.