Minimizing instrumentation requirement for estimating crop water stress index and transpiration of maize

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Year Published: 2013
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Author: Saleh Taghvaeian, José L. Chávez, Walter C. Bausch, Kendall C. DeJonge, and Thomas J. Trout
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Research was conducted in northern Colorado in 2011 to estimate the crop water stress index (CWSI) and actual transpiration (T a) of maize under a range of irrigation regimes. The main goal was to obtain these parameters with minimum instrumentation and measurements. The results confirmed that empirical baselines required for CWSI calculation are transferable within regions with similar climatic conditions, eliminating the need to develop them for each irrigation scheme. This means that maize CWSI can be determined using only two instruments: an infrared thermometer and an air temperature/relative humidity sensor. Reference evapotranspiration data obtained from a modified atmometer were similar to those estimated at a standard weather station, suggesting that maize T a can be calculated based on CWSI and by adding one additional instrument: a modified atmometer. Estimated CWSI during four hourly periods centered on solar noon was largest during the 2 h after solar noon. Hence, this time window is recommended for once-a-day data acquisition if the goal is to capture maximum stress level. Maize T a based on CWSI during the first hourly period (10:00–11:00) was closest to T a estimates from a widely used crop coefficient model. Thus, this time window is recommended if the goal is to monitor maize water use. Average CWSI over the 2 h after solar noon and during the study period (early August to late September, 2011) was 0.19, 0.57, and 0.20 for plots under full, low-frequency deficit, and high-frequency deficit irrigation regimes, respectively. During the same period (50 days), total maize T a based on the 10:00–11:00 CWSI was 218, 141, and 208 mm for the same treatments, respectively. These values were within 3 % of the results of the crop coefficient approach.

Pages: 53–65
URL: https://link.springer.com/article/10.1007/s00271-013-0415-z
Volume: 32
Number: 1
Journal: Irrigation Science
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DOI: https://doi.org/10.1007/s00271-013-0415-z
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Root Mean Square Deviation; Deficit Irrigation; Canopy Temperature; Full Irrigation; Crop Water Stress Index

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