Data-driven science provides new opportunities to serve the land grant mandate by addressing issues of today's society, and the unique challenges related to connecting with a multitude of diverse stakeholders around the region. At this time, the initiative is making high-quality climate data available that can be used in many agricultural applications. The precise N management recommendations are increasing farmer profitability related to corn production and greatly reducing environmental N losses.
impact statement issue
Agriculture is important to New York state and the nation, and 37,000 farms produce a diverse array of food products, and bioenergy. Agriculture occupies much of the best lands in the state and is often in close proximity to urban areas. It is the main contributor to water quality degradation and an important component of the greenhouse gas problem as a source (and sometimes a sink) of the major greenhouse gases carbon dioxide, nitrous oxide, and methane. The value of U.S. agriculture is increasing at a rate of $200 billion per year, and pressures are expanding on the soil resource base to provide food, bioenergy, and environmental services under conditions of increased water scarcity and vulnerability from climate change.
impact statement response
The initiative has created an integrated approach that includes climate modeling, crop, soil, and environmental sciences, and economic risk analysis for precision agriculture. High-resolution climate data (4 km grid) for the Northeast became available in 2007 through a CAC-based web service, and are accessible to any stakeholder.
The PNM computer model is applied to precisely estimate nitrogen needs for corn production and develop N loss risk indices. Soil hyperspectral sensing methods have been developed for rapid soil assessment and databases are developed to mine the data and develop digital libraries.
Weed-crop competition models and economic decision models are being developed, and climate data sets are mined. Researchers also studied the greenhouse gas implications of nitrogen fertilizer application and are performing data-intensive simulations to upscale these results for statewide analysis of nitrous oxide impacts.
impact statement summary
The Cornell Computational Agriculture Initiative (CCAI) is a partnership between the Cornell Center for Advanced Computing (CAC) and Cornell's College of Agriculture and Life Sciences (CALS).
The initiative focuses on using CAC's computational infrastructure and expertise to apply high-performance computing (HPC) technologies to agricultural and environmental problems.
This initiative is unique in the United States. Cornell University is providing important leadership by making data-driven scientific HPC tools available to external stakeholders for better management of agricultural and environmental systems.
