Zhang et al. (2026) Comparing four irrigation scheduling methods on maize growth, yield, and water productivity

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-06-24
• Authors: Hao Zhang, Kendall DeJonge, Liwang Ma, Kevin Yemoto, Ross Steward, Tyler Pokoski, Jon Altenhofen
• DOI: 10.1016/j.agwat.2026.110566

Research Groups

• Water Management and Systems Research Unit, Fort Collins, CO 80526, USA
• Rangeland Resources & Systems Research Unit, Fort Collins, CO 80526, USA
• Northern Water, Berthoud, CO 80513, USA

Short Summary

This study evaluated four irrigation scheduling methods for maize growth, yield, and water productivity under full and deficit irrigation conditions in semi-arid regions. The results showed that the RZWQM2 model-assimilated method (RZRS) consistently achieved higher yield and water productivity than soil-water-based methods under deficit irrigation.

Objective

• To compare the performance of four irrigation scheduling methods for maize growth, yield, and water productivity under full and deficit irrigation conditions in semi-arid regions.
• To evaluate the effectiveness of the RZWQM2 model-assimilated method (RZRS) in managing water stress and optimizing crop growth.

Study Configuration

• Spatial Scale: Field-scale experiment at the USDA-ARS Limited Irrigation Research Farm, Greeley, Colorado, USA.
• Temporal Scale: Three-year study from 2022 to 2024 during the maize growing season.

Methodology and Data

• Models used: Root Zone Water Quality Model (RZWQM2), FAO56 crop-coefficient method, and two soil water balance approaches (SWB1 and SWB2).
• Data sources: Soil moisture measurements, plant data collection, UAV-based imagery, and weather data from the Colorado Agricultural Meteorological Network (CoAgMet).

Main Results

• The RZWQM2 model-assimilated method (RZRS) consistently achieved higher yield and water productivity than soil-water-based methods under deficit irrigation.
• The FAO56 crop-coefficient method performed similarly to SWB1 under full irrigation, but was less effective under deficit irrigation conditions.
• Soil water balance approaches (SWB1 and SWB2) were less accurate in predicting crop growth and water use compared to the RZWQM2 model-assimilated method.

Contributions

• This study provides new insights into the effectiveness of different irrigation scheduling methods for maize growth, yield, and water productivity under semi-arid conditions.
• The results highlight the potential benefits of using process-based crop models like RZWQM2 in managing water stress and optimizing crop growth.

Funding

• USDA-ARS (United States Department of Agriculture-Agricultural Research Service)
• Colorado Water Conservation Board
• National Science Foundation

Citation

@article{Zhang2026Comparing,
  author = {Zhang, Hao and DeJonge, Kendall and Ma, Liwang and Yemoto, Kevin and Steward, Ross and Pokoski, Tyler and Altenhofen, Jon},
  title = {Comparing four irrigation scheduling methods on maize growth, yield, and water productivity},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110566},
  url = {https://doi.org/10.1016/j.agwat.2026.110566}
}