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dc.contributor.authorPhetheet, Jirapat
dc.contributor.authorHill, Mary C.
dc.contributor.authorBarron, Robert W.
dc.contributor.authorGray, Benjamin Jerome
dc.contributor.authorWu, Hongyu
dc.contributor.authorAmanor-Boadu, Vincent
dc.contributor.authorHeger, Wade
dc.contributor.authorKisekka, Isaya
dc.contributor.authorGolden, Bill
dc.contributor.authorRossi, Matthew W.
dc.date.accessioned2022-11-21T19:19:46Z
dc.date.available2022-11-21T19:19:46Z
dc.date.issued2021-10
dc.identifier.citationJirapat Phetheet, Mary C. Hill, Robert W. Barron, Benjamin Jerome Gray, Hongyu Wu, Vincent Amanor-Boadu, Wade Heger, Isaya Kisekka, Bill Golden, and Maththew W. Rossi. 2021. Relating agriculture, energy, and water decisions to farm incomes and climate projections using two freeware programs, FEWCalc and DSSAT. Agricultural Systems 193: 1-14.en_US
dc.identifier.urihttp://hdl.handle.net/1808/33689
dc.description.abstractContext: The larger scale perspective of Integrated Assessment (IA) and smaller scale perspective of Impacts, Adaptation, and Vulnerability (IAV) need to be bridged to design long-term solutions to agricultural problems that threaten agricultural production, rural economic viability, and global food supplies. FEWCalc (Food-Energy-Water Calculator) is a new freeware, agent-based model with the novel ability to project farm incomes based on crop selection, irrigation practices, groundwater availability, renewable energy investment, and historical and projected environmental conditions. FEWCalc is used to analyze the interrelated food, energy, water, and climate systems of Finney County, Kansas to evaluate consequences of choices currently available to farmers and resource managers.

Objective: This article aims to evaluate local farmer choices of crops and renewable energy investment in the face of water resource limitations and global climate change. Metrics of the analysis include agricultural and renewable-energy production, farm income, and water availability and quality. The intended audience includes farmers, resource managers, and scientists focusing on food, energy, and water systems.

Methods: Data derived from publicly available sources are used to support user-specified FEWCalc input values. DSSAT (Decision Support System for Agrotechnology Transfer) with added arid-region dynamics is used to obtain simulated crop production and irrigation water demand for FEWCalc. Here, FEWCalc is used to simulate agricultural and energy production and farm income based on continuation of recent ranges of crop prices, farm expenses, and crop insurance; continuation of recent renewable-energy economics and government incentives; one of four climate scenarios, including General Circulation Model projections for Representative Concentration Pathway 8.5; and groundwater-supported irrigation and its limitations.

Results and Conclusions: A 50-year (2018-2067) climate and groundwater availability projection process indicates possible trends of future crop yield, water utility, and farm income. The simulation during more wet years produces high crop production and slower depletion of groundwater, as expected. However, surprisingly, the simulations suggest that only the Drier Future scenario is commercially profitable, and this is because of reduced expenses for dryland farming. Although simulated income losses due to low crop production are ameliorated by the energy sector income and crop insurance, the simulation under climate change still produces the worst annual total income.

Significance: FEWCalc addresses scientific, communication, and educational gaps between global- and local-scale FEW research communities and local stakeholders, affected by food, energy, water systems and their interactions by relating near-term choices to near- and long-term consequences. This analysis is needed to craft a more advantageous future.
en_US
dc.publisherAgricultural Systemsen_US
dc.relation.isversionofhttps://www.sciencedirect.com/science/article/pii/S0308521X2100175Xen_US
dc.titleRelating agriculture, energy, and water decisions to farm incomes and climate projections using two freeware programs, FEWCalc and DSSATen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.agsy.2021.103222en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-5878-2856en_US
dc.identifier.orcidhttps://orcid.org/0000-0001-8021-5885en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-4226-7489en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-2460-7777en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-1846-5191en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.rights.accessrightsopenAccessen_US


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