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 Cropping Systems and Water Quality Research: Columbia, MO
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ARS Home Midwest Area Columbia, Missouri Cropping Systems and Water Quality Research Research





- Sudduth, Kenneth - Ken
- 2023
- 2022
- Publications
- Water Availability and Watershed Management (211)
- Sustainable Agricultural Systems Research (216)

Research Project: Improving Irrigated Crop Management System for Humid and Sub-humid Climates **Location:
                            Cropping Systems and Water Quality Research** 2022 Annual Report **Objectives**
                                

Objective 1: Optimize production systems for irrigated cotton, corn, soybean, and rice to improve crop water productivity under variable weather and soil conditions. 
1A: Develop improved methods for determining the appropriate values of field capacity for use in irrigation scheduling. 
1B: Develop a database of crop canopy sensing data for calculating crop coefficient in fields with uniform soil to serve as baseline for determining site-specific crop coefficients. 

Objective 2: Evaluate and/or develop site-specific best management irrigation practices based on localized soil and environmental conditions to optimize crop production while minimizing water usage. 
2A: Evaluate the potential for use of the ARSPivot program for variable-rate irrigation management in the sub-humid U.S. Mid-South. 
2B: Document the spatial variability of crop water coefficient and other crop and soil properties in a field and how they interact to affect crop water productivity. **Approach**
                                

Our team will address impediments to the overall goal of improving performance, profitability, and sustainability of irrigated agriculture in humid and sub-humid climates. We will develop and refine tools to improve irrigation scheduling and develop improved methods for determining appropriate values for a specific soil’s field capacity, information which is essential for optimal water management. Building on our previous research and as part of a multi-location, multi-disciplinary team, we will investigate how best to achieve site-specific irrigation management through use of the ARSPivot computer program to manage mechanized irrigation systems, and observations of soil and crop variability within the field. **Progress Report**
                                

This is the first report for this new project which began in February 2022 and continues research from the previous project, 5070-13610-007-000D, “Improving Irrigation Management and Water Quality for Humid and Sub-humid Climates”. Please see the report for the previous project for additional information. This project includes objectives from ARS scientists and University of Missouri (MU) scientists through a Non-assistance Cooperative Agreement collaboration. 
Objective 1: (1) Collected canopy spectral reflectance and height data multiple times during the growing season to develop a database of crop canopy sensing data for calculating crop coefficient in fields with uniform soil and management to serve as baseline for determining site-specific crop coefficients. (2) Initiated a crop rotation study including corn, cotton, soybean and peanut to address how to better design cropping systems to fit the climate of the Upper Mississippi Delta. 
Through a collaboration with the University of Missouri: (1) Maintained three real-time weather stations at research facilities in southeast Missouri with free web access to the information as part of the Missouri Mesonet statewide network of weather stations (mesonet.missouri.edu). (2) Conducted studies to improve management practices for producing furrow irrigated rice. (3) Investigated the relationship between soil water status and herbicide effectiveness using variable rate irrigation. (4) Investigated sources and transport pathways of nitrate in Big Oak Tree State Park and surrounding agricultural areas through determining the annual and seasonal variations in total surface and groundwater inputs and nitrate loads within the park area, determining nitrate concentrations and transport pathways within the wetland areas in the park, and determining the water table fluctuations in the adjacent croplands and pathways of nitrates. 
Objective 2: (1) Collected canopy spectral reflectance and height data multiple times during the growing season with ground-based mobile sensors and using a cooperator-operated unmanned aerial vehicle (UAV) to observe differences between two cotton varieties in a highly variable field to improve understanding the variability of cotton crop coefficient. **Accomplishments**


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