  Complex agricultural problems concern many countries, as the economic motives
are increasingly higher, and at the same time the consequences from the
irrational resources use and emissions are becoming more evident. In this work
we study three of the most common agricultural problems and model them through
optimization techniques, showing ways to assess conflicting objectives together
as a system and provide overall optimum solutions. The studied problems refer
to: i) a water-scarce area with overexploited surface and groundwater resources
due to over-pumping for irrigation (Central Greece), ii) a water-abundant area
with issues of water quality deterioration caused by agriculture (Southern
Ontario, Canada), iii) and a case of intensified agriculture based on animal
farming that causes issues of water, soil quality degradation, and increased
greenhouse gases emissions (Central Ireland). Linear, non-linear, and Goal
Programming optimization techniques have been developed and applied for each
case to maximize farmers welfare, make a less intensive use of environmental
resources, and control the emission of pollutants. The proposed approaches and
their solutions are novel applications for each case-study, compared to the
existing literature and practice. Furthermore, they provide useful insights for
most countries facing similar problems, they are easily applicable, and
developed and solved in publicly available tools such as Python.
