The rapid development of transportation electrification brings about the popularity of interconnected power-transportation systems (IPTS). However, the escalating frequency and uncertainty of natural hazards, such as typhoons, pose threats and potential damage to the operation of IPTS. Electric vehicles (EVs) can serve as mobile energy sources, whose proper scheduling in transportation networks can provide power support for the damaged power networks caused by natural hazards, thus enhancing the system’s resilience. This paper proposes a two-stage scenario-based scheduling framework using EVs for the restoration of an IPTS under natural hazard risks. In the first stage, EVs are pre-allocated and pre-charged at the charging stations to maximize their support potential against the predicted hazards; in the second stage, EVs are re-dispatched among different charging stations to help restore the power demands given the damaged IPTS topology. To address the real hazard scenarios and reduce the computational burden, a scenario generation approach indicating the real hazard’s impact on the IPTS is proposed followed by a scenario-reduction algorithm. Numerical experiments are conducted to validate the effectiveness of the proposed method based on the IEEE 33-bus distribution network and the Sioux Falls transportation network.