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.
