Wildfires can be a source of vulnerability for power systems operations. These events can especially affect the operation of distribution systems. They can interrupt energy supply, increase costs, and decrease grid resilience. Numerous approaches can be executed to prevent them. In this dissertation, it is considered the relationship between operative actions and the probability of wildfire disruption. This type of study has not been properly evaluated in technical and scientific literature. By not recognizing this aspect, the operation of power systems may be impaired. Properly modeling this dependency could lower wildfire disruption and loss of load. Considering this, a two-stage distributionally robust optimization problem with decision-dependent uncertainty is developed to consider distribution system multiperiod operation. The first stage determines the optimal switching actions and line investments, and the second stage evaluates the worst-case expected operation cost. It is designed a decision-dependent uncertainty framework where the line failure probabilities are a function (dependent) of its power flow levels. An iterative method is proposed to solve this model and an out-of-sample analysis is developed to validate it through different case studies. Results showed that, by neglecting the uncertainty dependency on operative decisions, there could be a higher expected loss of load and a higher operational cost. By considering this new approach when operating power lines, the grid s resilience could be improved and wildfire consequences can be mitigated with less costly actions.