Coordinate and support model intercomparison and ensemble effort for assessing farm management practices

DESCRIPTION:

Accurate assessment of agricultural management practices is crucial for informing management and policy decisions in U.S. agricultural and food production. In particular, better quantification of soil carbon is key to understanding soil fertility/soil health, while better quantification of nitrogen losses is essential for improving fertilizer use efficiency. However, existing quantifications on soil health outcomes are often highly uncertain due to significant spatial and temporal variability, limiting our ability to predict the impacts of management practices with confidence. To address this challenge and understand model uncertainties, assessing and advancing modeling processes and tools that account for the interactive effects of management and environmental factors are essential, as they help bridge the gaps left by insufficient field observations, overly generalized emission factor-based estimates, and the need to explore alternative systems that have not yet been implemented. This work will identify and engage with major model development groups to develop a collaborative platform. The work will also generate standardized model testing datasets across different scales, establish data sharing and processing protocols, produce model intercomparison and ensemble outputs, and produce tools for model users and policymakers. This concerted model intercomparison and improvement effort is anticipated to significantly advance the science of agroecosystem modeling, reduce model uncertainties, improve applicability and transferability, facilitate decision-making at multiple levels, and support stakeholders, especially U.S. farmers and ranchers, in achieving agricultural production goals.