Biomass to biofuel supply chain is subject to several potential disruptions such as flood, drought, pest attack, and equipment failure. These disruptions must be considered while designing the supply chain; especially if capital cost intensive components such as regional biomass pre-processing depots (RBPD) are to be implemented. This work develops a supply chain design optimization model that incorporates the possibility of such disruptions at the design stage. The objective function is the sum of the total cost incurred during the non-disruption and disruption scenarios weighted by their respective probability of occurrence. This also quantifies the expected disruption cost (EDC) on the operation of the supply chain. The decision variables are the locations and capacities of RBPDs and biorefinery, as well as the biomass flow across the supply chain. The model was applied to two separate case studies, namely, procurement of corn stover from farms arranged in a generic grid pattern, and procurement of corn stover, switch grass, and Miscanthus for a region of thirteen counties in Southern Illinois. The simulation results showed that the consideration of resiliency in design reduced the EDC of supply chain by up to 38% by optimizing the RBPD locations. The results were shown to depend on the intensity and nature of disruptions. This was especially true for feedstock with higher yield such as Miscanthus. Local parameters such as yield and biomass price also affected the optimal results. Moreover, the presence of RBPDs was shown to increase supply chain resiliency. (C) 2016 Elsevier Ltd. All rights reserved.