Evaluation of Colorado Irrigation Scheduler (CIS) in a Furrow Irrigated Field Near Greeley, Colorado.

Improved irrigation application efficiency depends on irrigation scheduling that specifies when and how much to irrigate. Efficient irrigation means applying only enough water to meet the crop’s evapotranspiration (ET) requirement. Crop water requirements are the foundation of irrigation scheduling. Excessive irrigation could lead to negative impacts on soil, crops and the environment. A local irrigation-scheduling tool that keeps track of the soil water balance and required irrigation amounts throughout the growing season can help irrigators keep track of water requirements and make more efficient use of their limited water supplies. The objectives of this study were to: (1) field test and evaluate the accuracy of an irrigation scheduling spreadsheet tool for calculating soil water deficits (Dc) in a furrow-irrigated corn (Zea mays L) field located near Greeley, Colorado and (2) determine the effect of frequency of mid-season corrections of Dc on the accuracy of the irrigation scheduler. A corn crop was grown for three seasons (2010 - 2012) in rows spaced 76 cm apart using furrow irrigation. The field was located near Greeley, Colorado. Daily weather data from an automatic weather station located 143.9 m from the field were used to calculate ET and effective precipitation in the irrigation scheduler. The corn field test involved root zone soil water status monitoring using gravimetric measurements. The irrigation scheduling spreadsheet tool developed in Visual Basic for Applications was designed to calculate daily Dc by water balance of the managed root zone. The results showed a strong relationship between calculated and measured deficit where index of agreement (d) was almost near 0.5 for most years of this study, specifically when measurements of Soil Water Content (SWC) were inserted bi-weekly or once per month. Root-Mean-Square Error (RMSE) did not exceed 2.54 mm when using SWC once per season in 2011, while Relative Error of the Mean (%) recorded over-estimation at 145.85 % in 2010 and under-estimation at -89 in 2012. Also, the CIS showed that amounts of irrigation water used during the years of study could be reduced by 30 to 50% through use of CIS.