Computational design and optimization of infrastructure policy in water and agriculture

Abstract

Investments in infrastructure tend to be associated with high capital costs, creating a necessity for tools to prioritize and evaluate different infrastructure investment options. This thesis provides a survey of computational tools, and their applicability in fine-tuning infrastructure policy levers, prioritizing among different infrastructure investment options and finding optimal sizing parameters to achieve a certain objective. First, we explore the usability of Monti Carlo simulations to project future water demand in Saudi Arabia and then, we use the outcome as an input to a Mixed Integer Linear Program (MILP) that investigates the feasibility of seawater desalination for agricultural irrigation under different water costing schemes. Further, we use numerical simulations of partial differential equations to study the conflicting interests between agricultural and municipal water demands in groundwater aquifer withdrawals and lastly we evaluate the use of Photo Voltaic powered Electro Dialysis Reversal (PV-EDR) as a potential technology to desalinate brackish groundwater through a multidisciplinary system design and optimization approach.