Spring water temperature forecasting in rice-shrimp fields allows farmers to anticipate temperature trends in advance, providing critical guidance for decisions on seedling stocking timing, aquaculture management, disease prevention, and anti-stress preparation. Based on the principle of energy balance, this study analyzes variations in surface solar radiation, effective back radiation from the water surface, latent heat exchange, and sensible heat exchange. By calculating the energy budget deficit of the water body and applying heat balance and mass transport equations for a micro-element water body, a spring rice-shrimp field water temperature forecast model is established and validated. The results are as follows. (1) The trends of the forecasted water temperature are basically the same as those of the measured water temperature but exhibit phase lags, indicating a delayed response in predictions; (2) Under clear-sky conditions, hourly forecasts of water temperature exhibit small deviations from measurements, with average absolute errors for daily mean, maximum, and minimum temperatures ranging from 0.3 to 0.5℃. This model demonstrates practical applicability, high precision, and reliable results. Compared with statistical methods, this physically-based model offers stronger interpretability and superior simulation accuracy, thereby enhancing the accuracy of spring water temperature forecasts in rice-shrimp fields.