Pavement is closely linked to the hydrological characteristics of the surface, which affects the infiltration and retention of surface runoff, leading to changes in thermo-physical surface indicators such as surface albedo, surface emissivity, volumetric heat capacity, thermal diffusivity, average soil temperature and surface humidity. Green drainage facilities, particularly bioswales, can mitigate runoff and improve microclimates by altering the flow path of water and thermo-physical surface indicators. While the thermo-physical indicators of artificial pavement surfaces such as sand, asphalt, cement, brick and stone have been studied and applied, those of bioswales have yet to be thoroughly investigated, and there is a dearth of scientific evaluation methods for their thermal effect. In this study, a genetic algorithm-based method for calibrating thermo-physical surface indicators was established, and its reliability was validated by comparing the thermo-physical indicators of asphalt pavement surfaces with existing literature. Two bioswales covering 200 m2 were designed and constructed, and their surface air temperature (1.5-meter from the surface) was monitored under irrigating and non-irrigated scenarios, and the thermo-physical indicators of two bioswales surface were determined. The temperature of bioswales in relevant literature was calculated by using the calibration results, and compared with the measured air temperature. The calibration method exhibited an error range of −9.6% to + 4.3%, and the surface temperature error resulting from the application of calibration parameters was 0.9133 to 0.9338. By establishing a method for determining the thermo-physical indicators of surface pavement and obtaining the thermo-physical indicators of bioswale surfaces using the surface temperature data, this study provides essential support for evaluating the thermal environment effect of bioswales.