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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Adaptive Cropping Systems Laboratory » Research » Research Project #440864

Research Project: Improved Models of Cover Crop Processes and Sustainable Crop Production

Location: Adaptive Cropping Systems Laboratory

Project Number: 8042-12000-043-001-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 15, 2021
End Date: Sep 14, 2026

Objective:
Improved modeling of biomass accumulation and nitrogen dynamics in cover crops, and modeling the effects of cover crop residues on water, temperature and nitrogen dynamics in soils. The objectives of this project are to develop and improve models cover crop processes and to evaluate the effects of cover crops on soil nitrogen, temperature and water dynamics in corn and soybean systems. Amended Objectives for amendment 2: 1. Develop and validate a simulation model for cereal rye as a cover crop 2. Evaluate the effects of cover crops on soil nitrogen, temperature and water dynamics in corn and soybean systems 3. Add soil model of phosphorus and ion species/oxygen dynamics to 2DSOIL 4. Evaluate the effects of a winter cover crop on water availability and yield of a following maize cash crop

Approach:
Adaptive Crops Systems Laboratory (ACSL) and University of Maryland (UMD) scientists will evaluate the models RYESIM, MAIZSIM, and GLYCIM to simulate the dynamics of cover crop mulches and effects of cover crops on water and nitrogen availability in the following cash crop. Data from experiments by the Precision Sustainable Agriculture group, UMD, ACSL, and the literature will be used to test and improve these models. Amended for amendment 2: Work with ACSL and UMD scientists to evaluate the models RYESIM, MAIZSIM, and GLYCIM to simulate the dynamics of cover crop mulches and effects of cover crops on water and nitrogen availability in the following cash crop. Further modify the soil model 2DSOIL to simulate the ion species in soil and effects on oxygen contents and root growth. Data from experiments by the Precision Sustainable Agriculture group, UMD, ACSL, and the literature will be used to test and improve these models.