[en] Highlights: • Wind tunnel validation for ensemble Kalman filter (EnKF)-based source inversion. • Six wind tunnel experiments replicating a heterogeneous nuclear power plant site. • Multi-scenario validation with various meteorological and topographical aspects. • EnKF shows good convergence and is insensitive to its own parameter settings. • The largest uncertainties come from the air dispersion model used in EnKF. - Abstract: Source inversion uses air dispersion models and environmental measurements to determine the atmospheric radionuclide release rate, which is critical in formulating an emergency response to nuclear incidents. Because source inversion methods are vulnerable to multiple uncertainties, site-specific validations that consider multiple air dispersion scenarios are important in ensuring their correct implementation. To comprehensively evaluate the ensemble Kalman filter (EnKF) for source inversion, a site-specific validation based on six wind tunnel experiments was performed for a highly heterogeneous nuclear power plant site in China. The six experiments cover the typical meteorology of the site and various topography types, providing abundant air dispersion scenarios for validation. The sensitivity of the EnKF to the initial guess, inflation factor, and position/number of measurements is also investigated. The results demonstrate that EnKF offers stable convergence and a reasonably bounded error in all experiments. Furthermore, the EnKF is insensitive to the initial guess, inflation factor, and number of measurements. However, it is sensitive to the position of the measurements and the air dispersion scenario. This sensitivity results from the complicated biases in air dispersion models, which highlight the key to improving the performance of EnKF.