论文标题

可持续农业经济增长和环境改善的综合建模方法:加拿大,希腊和爱尔兰的例子

Integrated modelling approaches for sustainable agri-economic growth and environmental improvement: Examples from Canada, Greece, and Ireland

论文作者

Garcia, Jorge A., Alamanos, Angelos

论文摘要

复杂的农业问题涉及许多国家,因为经济动机越来越高,与此同时,非理性资源使用和排放的后果变得越来越明显。在这项工作中,我们研究了三个最常见的农业问题,并通过优化技术对其进行建模,展示了将目标共同评估作为系统并提供总体最佳解决方案的方法。研究的问题是指:i)一个水泡区,由于灌溉过度抽水而具有过度开发的地面和地下水资源(希腊中部),ii)一个水含水量的区域,其水质降低问题是由农业造成的,由农业造成的水质恶化(加拿大南部,加拿大,加拿大),iii及其基于较高的农作用量的质量,质量质量的质量,该地区的质量是质量的,质量是质量的。排放(中部爱尔兰)。已开发和应用线性,非线性和目标编程优化技术,以最大程度地提高农民福利,对环境资源的使用量较低,并控制污染物的排放。与现有文献和实践相比,提出的方法及其解决方案是每个案例研究的新颖应用。此外,它们为面临类似问题的大多数国家提供了有用的见解,它们很容易适用,并在Python等公共工具中开发和解决。

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.

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