Constrained Optimisation of Agricultural Water Management with Parameter-Sensitive Objectives

Abstract

Increasing human populations and the impact of climate changes has meant that food security is increasingly an important issue. One of the main factors is the availability of water for agricultural purposes. Recently, models have been proposed for agricultural water management which aim to maximise crop yield (i.e., farm and regional profitability) while minimising the effect that this has on the environment. It is exploration of this that is the subject of this paper. As a refinement of a model that the authors have previously developed we investigate methods of more tightly controlling flow releases back to the environment. These include reformulating the objectives, and the addition of constraints to the model. Using the well-known Non-dominated Sorting Genetic Algorithm-II (NSGA-II) across a range of climate scenarios,, we find solutions (i.e, crop selection and planting area allocations) that minimise environmental flow deficits without significant detrimental to crop yield or profit.