Pre-construction assessments of bird collision risk at proposed wind farms are often confounded by insufficient or poor quality data describing avian flight paths through the development area. These limitations can compromise the practical value of wind farm impact studies. We used radar- and observer-based methods to quantify great white pelican flights in the vicinity of a planned wind farm on the Cape west coast, South Africa, and modelled turbine collision risk under various scenarios. Model outputs were combined with pre-existing demographic data to evaluate the possible influence of the wind farm on the pelican population, and to examine impact mitigation options. We recorded high volumes of great white pelican movement through the wind farm area, coincident with the breeding cycle of the nearby colony and associated with flights to feeding areas located about 50 km away. Pelicans were exposed to collision risk at a mean rate of 2.02 High Risk flights.h-1. Risk was confined to daylight hours, highest during the middle of the day and in conditions of strong north-westerly winds, and 82% of High Risk flights were focused on only five of the proposed 35 turbine placements. Predicted mean mortality rates (22 fatalities.yr-1, 95% Cl, 16–29, with average bird and blade speeds and 95% avoidance rates) were not sustainable, resulting in a negative population growth rate (λ = 0.991). Models suggested that removal of the five highest risk turbines from the project, or institution of a curtailment regimen that shuts down at least these turbines at peak traffic times, could theoretically reduce impacts to manageable levels. However, in spite of the large quantities of high quality data used in our analyses, our collision risk model remains compromised by untested assumptions about pelican avoidance rates and uncertainties about the existing dynamics of the pelican population, and our findings are probably not reliable enough to ensure sustainable development.