IMO insures against over-irrigation when water is abundant and manages crop stress for quality, economics or expanded production when water is limited.
CALCULATE IRRIGATION STRATEGIES IMO calculates field-specific irrigation strategies chosen by the irrigator: when to irrigate, how much to apply, set times. Irrigation strategies based on quantitative field measurements typically fall into two categories: Full and Partial. IMO runs both:
Full irrigation: 100% ET replacement using scientific irrigation scheduling (soil moisture+ET+water balance calculation). Many irrigation scheduling companies and an increasing number of irrigation sensor and hardware companies provide some version or partial version of SIS. Follow this link to a description of SIS.
Partial irrigation strategies: less than 100% ET replacement. Based on SIS, these are far more technical management strategies that involve exact irrigation timing to manage crop stress. Follow these links to research, evaluations and discussions of different partial irrigation strategies: DI; RDI; PRD.
This example is for almonds. The grower was limited to 32 inches (62% ET) for the season: forward_irrigation_schedule_2015_example.pdf. Schedules include anticipated irrigation dates and amounts. These are subject to some variation as the season progresses or as requested by the irrigator. In the Mediterranean climate of the PNW and California, schedules tend to vary with precipitation events in the Spring and become more stable later in the season. An irrigation plot for 32 inches is shown on the second page.
These four examples: imo_four_strategies_for_the_same_field.pdf include full irrigation and partial irrigation strategies plotted for the above field. They show how different irrigation strategies demand different irrigation patterns to target different irrigation objectives.
TARGETING, TRACKING, ADJUSTING
A partial irrigation strategy for alfalfa (motion graphic): madison_farm_2010_12_3_singlefield_m043_uncorrected.avi. In this case you can see how IMO adjusts the irrigation schedule to account for the rain events earlier in the season. It also shows where the grower decided to modify the irrigation plan towards the end of the season, reducing irrigation to apply the saved water on another field (this shows up near the end when the refill target drops below the original target).
how applied water will translate into ET to better target each irrigation throughout the season
IRRIGATOR CHOOSES / CONFIRMS THE STRATEGY
The irrigator determines their management goals and chooses a specific amount of water to apply. IMO is best when it quantifies what an irrigator already knows about their fields, making it possible to run the site-specific strategies they've learned with less effort.
IMO calculates a strategy and then targets and tracks the water application to match the strategy over the irrigation season.
The irrigator will always have the final call on a strategy and confirms its accuracy. There's no replacing boots on the ground.
You can't manage what you don't measure
Garbage in = garbage out
IMO's full precision requires a more detailed level of field data than conventional irrigation management. The risks of using IMO come from the quality of the field data. It can be run with loose tolerances if the goal is full irrigation. Data quality and measurement frequency are essential for partial irrigation.
Good soil moisture data and timely water application data for each irrigation event are critical. Water quality measurements are important in some soils. Telemetry and data loggers in the field are not necessary, but they make things much more efficient and reduce the potential for recording errors. The better the measurements the more accurate IMO's guidance system.
Uncertainty increases significantly when running irrigation strategies using less than 50% of full ET replacement.
ERROR CHECKING We have methods to reduce risk and capture errors that arise when field data are off or unavailable. This includes trapping bad Kc values. The initial calibration of IMO for a specific field identifies many errors and flags potential problems. But agriculture is a complex open system and not for the feint of heart. Automated data and good cultural practices go a long way. There is always uncertainty.