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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #393923

Research Project: Improving the Sustainability of Irrigated Farming Systems in Semi-Arid Regions

Location: Water Management and Systems Research

Title: Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment

item NAKABUYE, HOPE - University Of Nebraska
item RUDNICK, DARAN - University Of Nebraska
item DeJonge, Kendall
item LO, TSZ - Mississippi State University
item HEEREN, DEREK - University Of Nebraska
item QIAO, XIN - University Of Nebraska
item FRANZ, TRENTON - University Of Nebraska
item KATIMBO, ABIA - University Of Nebraska
item DUAN, JIAMING - University Of Nebraska

Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/19/2022
Publication Date: 9/26/2022
Citation: Nakabuye, H.N., Rudnick, D., DeJonge, K.C., Lo, T.H., Heeren, D., Qiao, X., Franz, T.E., Katimbo, A., Duan, J. 2022. Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment. Agricultural Water Management. 279. Article e107957.

Interpretive Summary: Various techniques are used to prescribe irrigation amount and timing, and recently a technique developed by USDA-ARS staff, called Degrees Above Non-Stressed (DANS) canopy temperature, has been used to quantify water stress and thus irrigation required. The technique is dependent upon a non-stressed canopy temperature (Tcns), which can be found by observation but in this study was determined from weather station data using a multilinear regression model. The DANS model was then used in an irrigation scheduling experiment, in comparison with soil moisture and evapotranspiration based scheduling methods. This study advances the techniques of temperature-based irrigation scheduling, which have potential in spatial and variable-rate irrigation systems.

Technical Abstract: Irrigation scheduling methods have been used to determine the timing and amount of water applied to crops. Scheduling techniques can include measurement of soil water content, quantification of crop water use, and monitoring of crop physiological response to water stress. The aim of this study was to evaluate the performance of a simplified crop canopy temperature measurement (CTM) method as a technique to schedule irrigation for maize. Specifically, the Degrees Above Non-Stressed (DANS) index, which suggests water stress when canopy temperature exceeds the non-stressed canopy temperature (Tcns), was determined by estimating Tcns from a weather based multilinear regression model. The modeled Tcns had a strong correlation with observed Tcns with a pooled R2 values of 0.94 across the 2018, 2019, and 2020 growing seasons. This DANS index was also highly correlated with the conventionally used Crop Water Stress Index (CWSI) with R2 values of 0.67, 0.59, and 0.76 in 2018, 2019, and 2020, respectively. Furthermore, DANS had a strong linear relationship with soil water depletion above 60% in the 0.60 m soil profile with an R2 of 0.78. The CTM method was also compared to more commonly used scheduling methods namely: soil moisture monitoring (SMM) and crop evapotranspiration modeling (ETM). Grain yield was significantly lower for the CTM method than for the ETM method in 2018 and 2020 but not in 2019. No significant differences were observed in Irrigation Water Productivity (IWP) in 2018; however, all treatments were significantly different with the CTM method having the greatest IWP in 2020. For attempting to trigger full irrigation with the CTM method, a fixed DANS threshold of 0.5°C was found to be more appropriate than the literature value of 1.0°C, but consideration of crop growth stage would further improve scheduling. Ultimately, the reactive nature of the CTM method and the inevitable uncertainty of modeled Tcns suggest that the CTM method may be more suited to deficit than full irrigation.