Reflectance-based crop coefficients REDUX: For operational evapotranspiration estimates in the age of high producing hybrid varieties

Abstract

Methodologies based on earth observation remote sensing allow for a precise estimation of actual water requirements for irrigated crops across large areas. In spite of the many number of experiments using or analyzing the relationship between the basal crop coefficient (K cb) and the soil adjusted vegetation index (SAVI) for maize, the development of new maize hybrid varieties with modifications related to canopy architecture suggest a possible change of the leaf area index (LAI) for maximum K cb and its relationship with the SAVI or other vegetation indices. In addition, we noted a lack of analysis of these relationships for cultivated soybean. The objective of this paper is to analyze the K cb , SAVI and LAI relationships in maize and soybean based on the non-linear relationships proposed by Choudhury et al. (1994). In addition, we propose a modification of the Choudhury et al. (1994) approach based on field-based experimental evidence of a minimum K cb greater than 0. For sites with limited field data, we also analyze the utility of a simple linear regression based on the K cb and SAVI values for bare soil and maximum K cb values. The resulting K cb-SAVI relationships are assimilated into a remote sensing based soil water balance model. The results of the model are analyzed in terms of irrigation requirements and crop evapotranspiration (ETa) for 11 growing seasons in two fields cultivated with irrigated and rain-fed maize and soybean in eastern Nebraska. Comparisons of measured and modelled ETa values indicate a good agreement, with RMSE lower than 0.7 mm d-1 for weekly averaged values. The comparison of actual irrigation applied and irrigation requirements indicate the central pivot systems could not supply adequate water in some growing seasons with higher demands.

Evaluation of variable rate irrigation using a remote-sensing-based model

“…In 2016, the recently-derived K cbrf relationships of Campos et al (2017) were used for both soybean and maize crops (Barker et al, 2018). These relationships were developed using eddy covariance flux data from fields near the Mead site (Campos et al, 2017). During irrigation scheduling, the average daily growing degree days from the previous 20 years was used in forecasting.…”

“…The K cbrf values were limited to not exceed 0.96 or be less than 0.15 prior to fitting the K cb curves, based on the K cb of Allen and Wright (2002). In 2016, the recently-derived K cbrf relationships of Campos et al (2017) were used for both soybean and maize crops (Barker et al, 2018). These relationships were developed using eddy covariance flux data from fields near the Mead site (Campos et al, 2017).…”

Irrigation Performance Assessment in Table Grape Using the Reflectance-Based Crop Coefficient

“…Melton et al [27] proposed the use of a generalized relationship for real-time and operational purposes that enables its applications to crop-specific relationships a posteriori when information about crop architecture is available. In agreement with this line of thinking, several authors [17,28,29] concluded that some relationships developed for different crops are valid for the assessment of ETc in different crops and areas. Therefore, the relationship used in this work was the Kcb-NDVI relationship developed by Campos et al [13] in an irrigated vineyard managed in vertical shoot-positioned trellises (Equation (3)) in the West of Spain (semi-arid area).…”

“…The differences in the maximum values of NDVI or Kcb obtained in the different experiments, as well as the multiannual variability described in this work, reinforce the necessity of feasible approaches based on field data to describe the actual crop coefficient (in situ) and the water requirements for the crop analyzed. In the same vein, the proposed approach could provide valuable information for the assessment of irrigation necessities as proposed in previous experiments [10,17,29]. In addition, the availability of satellite images and the accessibility of using the most recent developments [14] allow operative applications, as presented in this study.…”

“…This value was not included in the NIWR since the irrigation frequency and doses must be considered unknown in real-time applications, providing irrigation advice a week ahead. In addition, several authors were alerted about the partitioning between crop transpiration and soil evaporation based on the FAO-56 approach since the Kcb-NDVI relationship already includes a residual soil evaporation [29], and the depth of the evaporative soil layer could be overestimated [26].…”