Enhancing Agricultural Water Management Through Soil Moisture Monitoring and Irrigation Scheduling

Author(s): Rawson, J.; Linhoss, A.; Tagert, M.; Sassenrath, G.; Kingery, W.

Increasing reliance of crop producers on water for irrigation coupled with expansion of irrigated acreage has resulted in the overdraft of the Mississippi River Valley alluvial aquifer (MRVA). As water resources continue to decline, there is an immediate need for more efficient water management and greater implementation of water conservation practices. Mississippi’s Natural Resource Conservation Service (NRCS) has been working with farmers to increase voluntary implementation of water conservation practices, but these systems often require financial input from the grower and take time to install and manage. The Mississippi Irrigation Scheduling Tool (MIST) uses a “checkbook” water balance calculation and offers producers a free online irrigation management tool that indicates a need for irrigation when the soil water available to the plant falls below the level needed for crop growth. The overall objective of this study has been to evaluate and refine data requirements and inputs needed to calibrate and validate of the model for testing on corn and soybean fields with differing management and soil types. Data collection has been ongoing since May of 2011. Watermark 200SS sensors and dataloggers have been used to continually measure and record soil moisture at six-inch depth increments to three feet at various sites throughout the growing season of each year. Soil water retention curves were generated for each field from detailed soil testing at each depth increment and used to convert soil tension data to actual soil water balance, which was then compared to the MIST-calculated soil water balance. In addition, comparisons were done between sets of soil moisture readings within the same field to characterize the precision of the measurements. Next Generation Radar’s (Nexrad) four-kilometer precipitation data were used along with farm irrigation data to calibrate the model for a soybean field under pivot irrigation and a cornfield under furrow irrigation.
Download the presentation

Go back


Past Conference Archive