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Effects of a changing climate on agricultural system productivity are poorly understood, and likely to be met with as yet undefined agricultural adaptations by farmers and associated business and governmental entities. The continued vitality of agricultural systems depends on economic conditions that support farmers’ livelihoods. Exploring the long-term effects of adaptations requires modeling agricultural and economic conditions to engage stakeholders upon whom the burden of any adaptation will rest. Here, we use a new freeware model FEWCalc (Food-Energy-Water Calculator) to project farm incomes based on climate, crop selection, irrigation practices, water availability, and economic adaptation of adding renewable energy production. Thus, FEWCalc addresses United Nations Global Sustainability Goals No Hunger and Affordable and Clean Energy. Here, future climate scenario impacts on crop production and farm incomes are simulated when current agricultural practices continue so that no agricultural adaptations are enabled. The model Decision Support System for Agrotechnology Transfer (DSSAT) with added arid-region dynamics is used to simulate agricultural dynamics. Demonstrations at a site in the midwest USA with 2008–2017 historical data and two 2018–2098 RCP climate scenarios provide an initial quantification of increased agricultural challenges under climate change, such as reduced crop yields and increased financial losses. Results show how this finding is largely driven by increasing temperatures and changed distribution of precipitation throughout the year. Without effective technological advances and operational and policy changes, the simulations show how rural areas could increasingly depend economically on local renewable energy, while agricultural production from arid regions declines by 50% or more.
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A Pathway for Sustainable Agriculture
Expanding populations, the impacts of climate change, availability of arable land, and availability of water for irrigation collectively strain the agricultural system. To keep pace and adapt to these challenges, food producers may adopt unsustainable practices that may ultimately intensify the strain. What is a course of technological evolution and adoption that can break this cycle? In this paper we explore a set of technologies and food production scenarios with a new, reduced-order model. First the model is developed. The model combines limitations in the sustainable water supply, agricultural productivity as a function of intensification, and rising food demands. Model inputs are derived from the literature and historical records. Monte Carlo simulation runs of the model are used to explore the potential of existing and future technologies to bring us ever closer to a more sustainable future instead of ever farther. This is the concept of a moving sustainability horizon (the year in the future where sustainability can be achieved with current technological progress if demand remains constant). The sustainability gap is the number of years between the present and the sustainability horizon. As demand increases, the sustainability horizon moves farther into the future. As technology improves and productivity increases, the sustainability horizon is closer to the present. Sustainability, therefore, is achieved when the sustainability horizon collides with the present, closing the sustainability gap to zero. We find one pathway for water management technology adoption and innovation that closes the sustainability gap within the reduced-order model’s outputs. In this scenario, micro-irrigation adoption, minimal climate change impacts, reduced food waste, and additional transformative innovations such as smart greenhouses and agrivoltaic systems are collectively needed. The model shows that, in the absence of these changes, and continuing along our current course, the productivity of the agricultural system would become insufficient in the decade following 2050.
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- Award ID(s):
- 1712530
- PAR ID:
- 10223520
- Date Published:
- Journal Name:
- Sustainability
- Volume:
- 13
- Issue:
- 8
- ISSN:
- 2071-1050
- Page Range / eLocation ID:
- 4328
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/su13084328
