This paper presents the evaluation of adaptive control augmentation algorithms for wind disturbance rejection in small rotorcraft UAVs. The following control algorithms are developed in an effort to mitigate wind effects: baseline nonlinear dynamic inversion (NLDI), NLDI augmented with adaptive artificial neural networks (ANN), and NLDI augmented with ℒ1 output-feedback adaptive control. A six degrees-of-freedom nonlinear simulation environment is developed to evaluate the performance under different wind disturbance conditions. Monte Carlo analysis and a set of metrics are applied to compare and assess the overall performance of the developed control algorithms within a predefined wind envelope. These metrics provide a performance evaluation for trajectory tracking, angular rates tracking, attitude angle tracking and total energy consumption. The individual metrics are combined to provide the global performance index for the quadrotor with the developed control algorithms. Outdoor flight test results are included in this paper and the capabilities of these controllers to reduce wind disturbance effects on different flight tracking parameters are analyzed. The performance of the developed control laws is evaluated under nominal, low, medium and high wind disturbance conditions.