Efficiently transporting emergency supplies to affected areas in a timely manner is a critical function of disaster management. Following an emergency, the complexities of the environment and road conditions, coupled with significant uncertainties in the supply and demand of emergency materials, pose substantial challenges. Relying on a single mode of transportation and fixed optimization parameters often fails to meet the dynamic needs of the emergency supply chain. Despite this, there has been limited application of robust optimization methods to manage the uncertainties inherent in multimodal transportation of emergency supplies. Further exploration is needed to determine the effectiveness of the collaborative platform for the emergency supply chain. Utilizing real-world data from the COVID-19 pandemic, our findings indicate that varying optimization weights significantly influence the selection of transportation modes. Notably, the implementation of a collaborative platform results in a cost increase of less than 0.3%, while simultaneously reducing delivery time by over 6.2%. Furthermore, our analysis reveals a positive correlation between the satisfaction of minimum requirements and the uncertainty of supply and demand. This research provides critical insights for enhancing the efficiency of emergency supply chains, particularly in the context of real-world crises like COVID-19. By offering a robust framework for multimodal transportation and collaborative platforms, the findings serve as a valuable resource for policymakers and emergency management agencies aiming to optimize resource allocation and improve response times during disasters.