Caroline et al. (2026) Water productivity and irrigation water management practices: A study of the Arkansas Irrigation Yield 'Most Crop per Drop' Contest

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-08-07
• Authors: Eva Stephani Caroline, Qiuqiong Huang, Christopher G. Henry, Shahin Bahrami, Gertrude Dotse Bampoe
• DOI: 10.1016/j.agwat.2026.110679

Research Groups

• Department of Public Policy, University of Arkansas
• Department of Agricultural Economics and Agribusiness, University of Arkansas
• Department of Biological and Agricultural Engineering, University of Arkansas
• Rice Research and Extension Center, University of Arkansas
• Department of Environmental Dynamics, University of Arkansas
• Texas A&M University

Short Summary

This study evaluates the impact of Irrigation Water Management (IWM) practices on water productivity in corn, soybean, and rice fields under producer-managed conditions. The results show that some IWM practices are associated with higher water productivity, driven primarily by yield gains rather than reductions in applied irrigation water.

Objective

• To identify which IWM practices and combinations of practices are associated with higher water productivity (WP) under producer-managed field conditions.
• To compare irrigation application and crop yields between producer-managed fields and collaborative demonstration settings.

Study Configuration

• Spatial Scale: Field-level data from the Arkansas Irrigation Yield "Most Crop per Drop" Contest, covering eastern Arkansas.
• Temporal Scale: Data collected over six rounds of contests from 2018 to 2023.

Methodology and Data

• Models used: Seemingly Unrelated Regression (SUR) models were estimated to jointly model water productivity, crop yield, and applied irrigation.
• Data sources: Field-level data from the Arkansas Irrigation Yield Contest, supplemented by data from the 2022 Arkansas Irrigated Producers Phone Survey.

Main Results

• In corn fields, combinations of CHS, Sensors, and Surge are associated with higher WP, driven primarily by yield gains rather than reductions in applied irrigation water.
• In soybean fields, combinations of CHS and Sensors are associated with higher WP through reduced irrigation application without yield penalties.
• In rice fields, results are less consistent, although SUR analysis provided some evidence that the MIRI/AWD combination was associated with higher WP.

Contributions

• This study contributes to the irrigation and water management literature by evaluating IWM practices using field-level data from producer-managed commercial farms.
• The study examines multiple IWM practices and practice combinations across corn, soybean, and rice, and compares the observed irrigation outcomes with those reported in previously published demonstration studies.

Funding

• This research was funded by the University of Arkansas Division of Agriculture (UADA) and the Environmental Quality Incentives Program.

Citation

@article{Caroline2026Water,
  author = {Caroline, Eva Stephani and Huang, Qiuqiong and Henry, Christopher G. and Bahrami, Shahin and Bampoe, Gertrude Dotse},
  title = {Water productivity and irrigation water management practices: A study of the Arkansas Irrigation Yield 'Most Crop per Drop' Contest},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110679},
  url = {https://doi.org/10.1016/j.agwat.2026.110679}
}