In the flood disaster rescue, UAV swarms possess rapid and efficient search and rescue capabilities. However, the rational autonomous allocation of tasks to different UAVs remains a challenge. This paper first analyzes the characteristics and requirements of flood search and rescue missions, and then proposes a multi-objective and multi-task allocation algorithm. This algorithm comprehensively considers the flight performance of UAVs, sensor capabilities, and their matching relationships with task requirements. At the same time, it utilizes information from UAVs’ own perception and inter-vehicle communication to comprehensively consider multiple indicators (such as task completion time, coverage area, and resource utilization, etc.) to obtain the optimal task allocation plan. In order to verify the effectiveness of the algorithm, a series of simulation experiments were conducted. The experimental results show that the algorithm is able to cope with complex and changing environments and rescue task requirement.