United States Department of Transportation
i
Informing Post-Disaster Restoration through Modeling Interdependent Agriculture and Transportation Networks
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2021-12-01
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[PDF-27.30 MB]
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Abstract:Prior research fails to capture how important details—including different transportation modes, sensitivity to time and decentralized geographic space, and the economic impacts for rural communities—impact how transportation should be used when a disruption has occurred and how to coordinate restoration activities across interdependent infrastructure systems. The authors address this research gap by modeling the operation and restoration of an interdependent set of transportation and agriculture networks. The authors present a mixed integer linear programming formulation which seeks to maximize the expected yield for a set of rice farms throughout the state of Arkansas under scenarios where the amount and timeliness of fertilizer delivery are affected by a disrupted transportation network. The authors validate the model using real data for a case study in Arkansas. This dataset includes the location and acreage of rice farms in Arkansas, fertilizer demand, and a multimodal transportation network comprised of road, rail, and waterway networks. For this dataset, the authors created disruption scenarios for different transportation modes with different severity, location, and duration. Using these data, the authors ran extensive computational experiments to deduce operational and restoration insights on the interdependence and resiliency of transportation and agriculture systems.
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