Comparison of sensor-based and weather-based irrigation scheduling

Authors: Sui, Ruixiu; Vories, Earl

Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/17/2020
Publication Date: 6/23/2020
Citation: Sui, R., Vories, E.D. 2020. Comparison of sensor-based and weather-based irrigation scheduling. Applied Engineering in Agriculture. 36(3):375-386. https://doi.org/10.13031/aea.13678.
DOI: https://doi.org/10.13031/aea.13678

Interpretive Summary: Soil properties and crop yield potential can vary considerably within a single field resulting in variability of water required for plant to grow. Variable rate irrigation (VRI) technology can site-specifically apply irrigation water at variable rates within a single field to account for the temporal and spatial variability in soil and plant characteristics. USDA ARS Scientists at Sustainable Water Management Research Unit at Stoneville, MS developed a VRI method and tested the method in Mississippi Delta for 5 crop-years. Results indicated the VRI management significantly reduced amount of irrigation water by 22% in corn and 11% in soybean. Adoption of VRI management method could improve irrigation water use efficiency in the Mid-Sou

Technical Abstract: Sensor-based irrigation scheduling methods (SBISM) use sensors to measure soil moisture and schedule irrigation events based on the soil-water status. With rapid development of soil moisture sensors, more producers have become interested in SBISM. Arkansas Irrigation Scheduler (AIS)is a weather-based irrigation scheduling tool that has been adopted in the Mid-South for many years. Field studies were installed in multiple locations of a soybean field (Mississippi) and a cotton field (Missouri). Soil water contents of the field were measured across the growing season. The AIS was installed in a computer and a nearby weather station was employed to obtain all data required. Number and time of irrigation events triggered by SBISM were compared with those scheduled by the AIS. Results showed the number and time of irrigation events scheduled using the SBISM were often different from those predicted by the values. While all of the sites were the Tiptonville silt loam mapping unit, many of the measurements appeared to come from sandliers soils. The AIS assumed more water entered the soil than the sensors indicated from both irrigations and rainfalls less than 25mm. Futhermore, the difference varied among sites, especially for rainfall large enough to cause runoff. The recommendations based on the watermark sensors agreed fairly well with the AIS in July after the data from the sandiest site was omitted; however, the later irrigations called for by the AIS were not indicated by the sensors. Both the sensor-based irrigation scheduling method and the AIS could be used as tools for irigation management in the Mid-South region, but extra attention to the effective portion of rainfall or irrigation would be needed in some years.