In an actual concrete dam construction, the efficiency of thermal field reconstruction directly affects the timeliness of temperature control measures. Therefore, using lightweight methods to obtain real-time, accurate thermal fields is crucial for concrete temperature control. To balance both accuracy and efficiency, this study proposes an optimization method for thermal field reconstruction in concrete dams. The method consists of three components: evaluating interpolation algorithms, optimizing the number of monitoring points, and analyzing their positions. Specifically, a distributed temperature sensing system is employed for concrete monitoring, with a “Z-shaped” optical fiber layout. Three interpolation algorithms—Kriging, Natural Neighbor, and Inverse Distance Weighting—are quantitatively evaluated, with Kriging showing the highest accuracy. Sensitivity analysis, combined with the control variable method, is used to assess the impact of the monitoring point number and position. Lightweight application procedures are then proposed, using reconstructed thermal field results to guide strategy formulation and parameter adjustment for the intelligent cooling control system. A case study demonstrates that this method ensures the effectiveness and timeliness of concrete temperature control measures. The proposed approach enables real-time updates of concrete temperature control measures in sync with the progress of the pouring process, providing a valuable reference for similar projects.