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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Rangeland Resources & Systems Research » Research » Publications at this Location » Publication #345967
Title: Biophysical system models advance agricultural research and technology: Some examples and further research needs

Author
item AHUJA, LAJPAT - Retired ARS Employee
item Ma, Liwang
item Anapalli, Saseendran

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 9/13/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Environmental concerns of the general public, droughts, and climate change effects require continual adaptation and optimization of agricultural systems through changes in cropping and management. Advancement of science and technology to achieve these changes requires cutting-edge field research, using a quantitative whole-system approach. Process-based models of agricultural systems integrated with field research provide such a framework. The models help; 1) quantify field research results in terms of the fundamental theory and concepts that are broadly applicable beyond the site specific empirical relationships, 2) predict experimental results from knowledge of the fundamental factors that determine the environment and plant growth under different climates, 3) extend the experimental results to longer term weather conditions beyond the limited duration of the field experiments and to other soil types and climates in the area outside the experimental plots, and 4) use extended results to develop broad-based precision management decision support tools or simple management guidelines for producers and other users, which may include linkage to economic and social considerations. As a result, the models are also continually improved and serve as an evolving theoretical backbone of complex agricultural system research and information transfer. We present here some simple examples of above applications based on our work pertaining to some critical resource areas for optimizing water quantity and water quality in dryland and irrigated agriculture. Importantly, these applications were made in collaboration with field research scientists at several locations. We also identify some key areas of further trans-disciplinary research, synthesis, and improvement of the modeling tools.