Assessing the economic impact (Deliberto):

To understand the economic effectiveness of Climate Smart Agriculture (CSA) practices, we will create a computer model to simulate farm profitability under different conditions and risks. By comparing the costs and profitability of alternative CSA practices, we can estimate the compensation needed to adopt these practices and evaluate the impact of US agricultural policies. Using IMPLAN, an economic model, we will assess the economic consequences of climate change on rice production, considering both state and local levels. Additionally, we will evaluate the sustainability of rice farming by using the SAFA framework and collecting data through interviews, observations, and scientific literature review to analyze sustainability across political, environmental, economic, and social dimensions.

Assessing understanding and perceptions of growers regarding CSA (Schafer):

We will study how farmers interact with others and the support they receive in their current farming practices. We will interview different people involved in farming, such as landowners, government agencies, and agricultural associations, to understand their opinions and the challenges they face. We will also conduct a survey to gather more information about farmers' interests and concerns regarding new farming technologies. By combining interviews and surveys, we hope to learn more about the factors that influence farmers' decisions and how to better support them in adopting sustainable farming practices.

• Social Capital and Farmers' Willingness to Adopt Countryside Stewardship Schemes
• Measuring Social Networks’ Effects on Agricultural Technology Adoption
• https://www.frontiersin.org/articles/10.3389/fpsyg.2022.876912/full
• Changes in Agricultural Extension and Implications for Farmer Adoption of New Practices
• Barriers to the Adoption of Sustainable Agriculture on Rented Land: An Examination of Contesting Social Fields*
• The DSSAT crop modeling ecosystem, in Advances in crop modelling for a sustainable agriculture

Assessing environmental impacts on rice production (Karthikeyan):

• We will use computer models to study how rice plants grow and produce yield under different environmental and management conditions. These models can predict how much rice a farm can produce by considering factors like soil, weather, and farming practices. By using these models, we can identify the best management practices to increase rice production and adapt to changes in the climate, considering both economic and environmental benefits.
• Hoogenboom, G., C. Porter, V. Shelia, K. Boote, U. Singh, J. White, L. Hunt, R. Ogoshi, J. Lizaso, J. Koo, S. Asseng, A. Singels, L. Moreno, and J. Jones. Decision support system for agrotechnology transfer (DSSAT) Version 4.7.5 (https://DSSAT.net) DSSAT Foundation, Gainesville, Florida, USA. 2019.
• Jones, J.W., G. Hoogenboom, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, and J.T. Ritchie, 2003, The DSSAT cropping system model. European Journal of Agronomy. 18 (3-4):235-265.
• DSSAT. https://dssat.net/csm-ceres-rice/. 2021.

Expected outcomes:

This research component will provide a clear picture of the impact of climate change on economic sustainability of rice farming and identify the factors to be considered to facilitate adoption of sustainable farming practices. The modeling research will predict the phenological response of rice under the changing climatic and crop management condition and will provide the growers with the choice of crop, cultivar, and management practices to improve economic and environmental sustainability.