Principal Investigator: Vasudha Sharma
Organization: University of Minnesota Extension, and Soil, Water and Climate
Award Amount: $123,506
Start Date: April 2019 | End Date: December 2021
Project ManagerJeppe Kjaersgaard (

Final Report in the Minnesota Digital Water Research Library: Evaluation and performance of different irrigation scheduling methods and their impact on corn production and nitrate leaching in central sands region of Minnesota  


The overall goal of this project was to promote the adoption of advanced irrigation scheduling tools, to reduce the negative impact of agriculture on groundwater quality and quantity. By adopting efficient irrigation management techniques studied in this project clean water goals of Minnesota can be achieved.



Irrigation scheduling is an important management tool for Minnesota irrigators. Irrigation scheduling enables irrigators to apply the right amount of water at the right time, thereby increasing irrigation efficiency and reducing the risk of nitrate-N leaching. Over-application of irrigation water increases energy, water and labor needs, and may cause nitrate-N leaching from the rooting zone. Similarly, under-application of water creates plant water stress, reduces yield and may leave leaching-prone, unutilized nitrate-N in the soil. Irrigation scheduling is challenging, and methods range from simple empirical methods to more advanced weather data-based methods. Accurate irrigation scheduling is critical to maximize water use efficiency and water productivity. With the availability of real-time meteorological information from agricultural weather stations and advent of crop water use estimation methods there is a need to evaluate current and emerging irrigation scheduling systems to provide irrigators with science-based information about scheduler performance.


The objectives:

  • Evaluate four different strategies for irrigation water management;
  • Develop an easy-to-use, simple and inexpensive tool for irrigation management on coarse-textured soil based on soil matric potential;

The project compared (1) in-field soil moisture monitoring using soil moisture sensors, (2) 100% crop evapotranspiration (ETa) replacement, (3) University of Minnesota checkbook method and, (4) crop growth model (EPIC) on corn yield and nitrate leaching. The project also provided education and outreach at field days, workshops, extension publications and presentations, and scientific journal articles.

Images,of a person in a farm field checking a sensor, and two people presenting outdoors under a tent at a field day event.wa

Key Findings

  • In terms of irrigation amounts, in all years, lowest irrigation was recommended by the irrigation management assistant (IMA) tool whereas highest irrigation was recommended by checkbook (CB) method in 2019 and 2020 and by EPIC crop growth model method in 2021. The reason for low or no irrigation recommendation in IMA might be due to how it estimates or interpolates precipitation in the model. It was observed that in the IMA tool, if the precipitation was not over written by the user, the interpolation method in the tool tends to overestimate the precipitation, thus lower irrigation recommendation. On average, CB and EPIC crop growth model method recommended 24% and 23% more irrigation as compared to SM method, respectively, whereas IMA methods recommended 62% lower irrigation.
  • The IMA method of irrigation scheduling, which was observed to have the lowest water application (Precipitation + Irrigation), also resulted in significantly lower seasonal crop evapotranspiration in all three years as compared to other irrigation scheduling methods. The daily crop evapotranspiration (ETc) was not significantly different between soil moisture monitoring, EPIC and checkbook method.
  • Corn grain yield was not significantly impacted by total irrigation water applied or the irrigation scheduling method used. Even the IMA method of irrigation scheduling resulted in the lowest total water applied in consistently, the corn yields were not significantly different than other treatments. The highest corn grain yield was obtained in CB in all years. This is mainly due to the fact that highest irrigation was applied in CB in all years resulting in higher yields.
  • Maximum in-season nitrate leaching occurred in summer months from June to August which coincides with the time of irrigation applied and high total water use. The IMA method of irrigation scheduling resulted in significantly lower Nitrate-N leaching without significantly impacting crop yield in all growing seasons. The highest nitrate leaching was observed under CB in 2019 and 2021 and in EPIC method in 2020. Overall, we found a positive linear relationship between irrigation and nitrate leaching. There was no significant difference in nitrate leaching between SM, CB and EPIC irrigation scheduling.
  • Nitrate leaching at the Westport site for the year 2019 was significantly lower than that at the same site for the year 2020, which suggests large variability of Nitrate leaching with climatic factors such as precipitation patterns along with irrigation scheduling methods used.
  • We compared the amount of N uptake taken up by crop at R1 and R6 corn growth stages. Nutrient and water uptake also have a positive relationship with corn yield, sufficient nutrient uptake increases the chances of obtaining ideal yields for crop. Although a blanket amount of fertilizer input was applied across all four irrigation scheduling methods, the irrigation treatments recommended irrigation amounts and timings differently. As expected, the irrigation scheduling treatments did not significantly impact N uptake of crop, which suggests that all the four irrigation scheduling methods were successful in enabling sufficient nitrogen uptake despite some of the methods had lower total water use as compared to others. Also, at physiological maturity, the N uptake across treatments was not significantly different from each other. In all years no significant differences were observed in N uptake between irrigation treatments. This might be due to the fact that ETc was not limited by water application. All irrigation treatments received enough water to maintain the ETc required for crop production thus N uptake was not significantly impacted.
  • Overall, our results indicated that IMA tool was under recommending the irrigation which was clear from the decrease in ETc and yield, however, in Minnesota where growing season precipitation is usually above or close to average rainfall such as in years like 2019 and 2020 when precipitation was enough to sustain the crop growth, IMA method for irrigation scheduling could have a potential in reducing the nitrate leaching without significantly reducing the yield.
  • Irrigation Trigger Points were derived from measured θv-NP and Ψm-WM data. The soil matric potential values (taken as positive) obtained from a watermark sensor were averaged on a daily basis and neutron probe measured volumetric water content on that particular day was assumed to reflect volumetric water content corresponding to the watermark soil matric potential. For watermark sensors the suggested range for irrigation trigger points is based upon 35% depletion of available water. Although it’s upon the decision of irrigation manager to select the maximum allowable depletion for their crop. The recommended irrigation trigger point when watermark sensors are used in the soils similar to the research site is 30-40 Kpa.

Next Steps

Through this study, we identified that IMA tool and EPIC crop growth models have the potential to efficiently recommend irrigation amounts and timing without significant time and cost investment on grower’s part. However, these tools need further research based modifications and updates to be used for Minnesota soils. Our next step is to improve the models in the IMA tool to predict the right irrigation timing and amount, and expand that tool to statewide coverage free of cost to growers.