Hourly and Daily Single and Basal Evapotranspiration Crop Coefficients as a Function of Growing Degree Days, Days After Emergence, Leaf Area Index, Fractional Green Canopy Cover, and Plant Phenology for Soybean

doi:10.13031/trans.56.10219

Cited by 21 publications

(26 citation statements)

References 49 publications

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“…Description Soybean Faba bean Reference aveg (Eq.1) Regression intercept, vegetative phase -0.06 -0.06 Irmak et al (2013) bveg (Eq.1) Regression slope, vegetative phase 3.29 3.29 Irmak et al (2013) arep (Eq.1) Regression intercept, reproductive phase 0.71 0.71 Irmak et al (2013) brep (Eq.1) Regression slope, reproductive phase 1.31 1.31 Irmak et al (2013) fphuanthesis (Eq.1)…”

Section: Parametermentioning

confidence: 99%

Supplementary material to "Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS"

Ma¹,

Olin²,

Anthoni³

et al. 2021

Preprint

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Section: Parametermentioning

confidence: 99%

Supplementary material to "Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS"

Ma¹,

Olin²,

Anthoni³

et al. 2021

Preprint

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“…Crop coefficients for maize were computed based on Allen and Wright (2002). For soybean, the average daily value of the two single K cr relationships (2007 and 2008) of Irmak et al (2013) was used. These coefficients were originally developed for Clay Center, Nebraska, which is approximately 160 km southwest of the field.…”

Section: Evapotranspirationmentioning

confidence: 99%

Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery

Bhatti

Heeren

Barker

et al. 2020

Agricultural Water Management

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Variable Rate Irrigation (VRI) considers spatial variability in soil and plant characteristics to optimize irrigation management in agricultural fields. The advent of unmanned aircraft systems (UAS) creates an opportunity to utilize high-resolution (spatial and temporal) imagery into irrigation management due to decreasing costs, ease of operation, and reduction of regulatory constraints. This research aimed to evaluate the use of UAS data for VRI, and to quantify the potential of VRI in terms of relative crop and water response. Irrigation treatments were: (1) VRI using Landsat imagery (VRI-L), (2) VRI using UAS imagery (VRI-U), (3) uniform (U), and (4) rainfed (R). An updated remote-sensing-based evapotranspiration and water balance 1 B h a t t i e t a l . i n A g r i c u l t u r a l W a t e r M a n a g e m e n t 2 3 0 ( 2 0 2 0 ) 2 model, incorporating soil water measurements, was used to make prescriptions for the VRI treatments at a field site in eastern Nebraska. In 2017, the mean prescribed seasonal irrigation depth (I p ) for VRI-L was significantly greater (α=0.05) than the I p for U for soybean. In 2018, I p for soybean was greatest for VRI-U treatment followed by the U and VRI-L treatments, with all being significantly different from each other. No significant differences in I p for maize were observed in 2017 or 2018. In all cropyear combinations, the VRI and U treatments had significantly greater evapotranspiration (ET) than the R treatment. Yield differences among treatments were not significant (except for rainfed maize compared to VRI-L in 2017). For maize in 2017, IWUE for VRI-L was comparable to the U treatment. The UAS imagery was a better match for the scale of crop management than Landsat imagery, particularly for thermal data. The multispectral UAS data was successfully used in the crop coefficient ET model for real-time irrigation, but using UAS to determine accurate canopy temperatures for surface energy balance modeling remains a challenge.

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“…Thresholds of 40% to 50% of plant available soil water are often used for cotton (Hunsaker et al 2005;Farahani et al, 2008). Allen et al (1998) reported K c estimates for cotton, many cereal and other crops grown across the world; however, the applicability of those values in computing crop irrigation water requirements across soils, climates, and locations was found to introduce substantial errors in computed irrigation schedules (Howell et al, 2004;Farahani et al, 2008;Farg et al, 2012;Irmak et al, 2013;Payero and Irmak, 2013). For example, in a lysimetric study with cotton in a Mediterranean region of northern Syria, Farahani et al (2008) found the Allen et al (1998) tabulated values to be 24% greater than what they computed.…”

Section: Evapotranspiration-based Scheduling Toolsmentioning

confidence: 99%

Forty Years of Increasing Cotton’s Water Productivity and Why the Trend Will Continue

Barnes¹,

Campbell²,

Vellidis³

et al. 2020

Applied Engineering in Agriculture

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Highlights Over the last 40 years the amount of irrigation water used by cotton in the United States has decreased while yields have increased leading to a large increase in crop water productivity (CWP). Many factors have contributed to improved CWP, such as improvements in water delivery systems. Irrigation scheduling technologies have also contributed to improved CWP; however, farmer adoption of advanced scheduling technologies is still limited and there is significant room for improvement. Increased yields from improved cultivars without an increase in water requirements has also been important for CWP. Continued developments in sensor technologies and improved crop simulation models are two examples of future strategies that should allow the U.S. cotton industry to continue an upward trend in CWP. Abstract. Over the last 40 years the amount of irrigation water used by cotton in the United States has decreased while yields have increased. Factors contributing to higher water productivity and decreased irrigation water use include migration of cotton out of the far western U.S. states to the east where more water requirements are met by rainfall; improved irrigation delivery systems with considerable variation in types and adoption rates across the U.S.; improved irrigation scheduling tools; improved genetics and knowledge of cotton physiology, and improved crop models that can help evaluate new irrigation strategies rapidly and inexpensively. The considerable progress over the last 40 years along with the promise of emerging technologies suggest that this progress will continue. Keywords: Cotton, Crop water productivity, Irrigation, Sustainability, Water use efficiency.

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Hourly and Daily Single and Basal Evapotranspiration Crop Coefficients as a Function of Growing Degree Days, Days After Emergence, Leaf Area Index, Fractional Green Canopy Cover, and Plant Phenology for Soybean

Cited by 21 publications

References 49 publications

Supplementary material to "Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS"

Supplementary material to "Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS"

Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery

Forty Years of Increasing Cotton’s Water Productivity and Why the Trend Will Continue

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Hourly and Daily Single and Basal Evapotranspiration Crop Coefficients as a Function of Growing Degree Days, Days After Emergence, Leaf Area Index, Fractional Green Canopy Cover, and Plant Phenology for Soybean

Cited by 21 publications

References 49 publications

Supplementary material to &quot;Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS&quot;

Supplementary material to &quot;Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS&quot;

Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery

Forty Years of Increasing Cotton’s Water Productivity and Why the Trend Will Continue

Contact Info

Product

Resources

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Supplementary material to "Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS"

Supplementary material to "Modelling symbiotic biological nitrogen fixation in grain legumes globally by LPJ-GUESS"