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Abstract

In many regions of the world, irrigation is vital to food security and agricultural productivity. Prudent management of irrigation systems becomes paramount under a probable scenario of rising climatic variability and population growth, which would necessitate increased irrigation. This thesis seeks to extend a mathematical model for irrigation schemes, by Vico and Porporato, to include the influence of weather forecast data on irrigation schedules. We then propose a novel irrigation strategy which minimizes irrigation volume throughout the growing season using forecast information.

This thesis employs a life-cycle assessment (LCA) methodology to evaluate the environmental impact of different irrigation strategies. Using LCA, we can include both the upstream and downstream environmental impacts of each irrigation strategy in our analysis. The profitability of each method is examined alongside its environmental impact. Ultimately, we observe that while profitability comes at a cost in terms of environmental impact, an irrigation strategy which incorporates three days of weather forecast data may optimally balance both interests.