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The aim of this study was to estimate standard crop coefficients of surface and sub-surface drip-irrigated young almond trees under non-limiting soil water content conditions, based on measurements of the fraction of ground covered by the canopy (fc) and tree height (h) (A&P approach proposed by Allen and Pereira (2009)) and to improve the transferability of them to the productive sector once weather data (i.e. maximum and minimum air temperature (Tmax and Tmin, respectively), as well as dew point temperature (Tdew)) were adjusted to the reference conditions. A 4 year field experiment was carried out in a ~ 12.5 ha commercial young almond (Prunus dulcis (Mill.) D.A. Webb) orchard located in Hellín, (SE Spain). 'Penta' almond trees, grafted onto the GF-677 rootstock, were planted in 2018. Field measurements of fc and h were performed over four consecutive growing seasons from 2019 to 2022. In parallel, ETo computed by the nearest meteorological station, located at a non-reference weather site, was reduced around 6% after bringing weather data closer to the reference conditions, while actual crop evapotranspiration and its components (actual tree transpiration and soil evaporation) were estimated in each irrigation system through the so-called simplified two-source energy balance (STSEB) model in order to be used as a quality assessment of the A&P approach. The ratio between the former estimations and the ETo allowed to compute STSEB-based crop coefficients. No significant differences in effective canopy cover (fc eff) nor h were observed between the two irrigation systems, and thus the estimated Kcb values were the same for both drip-irrigation systems. fc eff values during mid-season stage ranged between 0.15 in 2019 and 0.62 in 2022, whereas average h values for this stage ranged between 2.36 and 3.80 m in 2019 and 2022, respectively. These values of fc eff and h resulted in average mid-season basal crop coefficients (Kcb-mid) of 0.28 in 2019, 0.39 in 2020, 0.61 in 2021 and 1.02 in 2022. Soil evaporation estimates through STSEB model were significantly different between the two irrigation systems, leading to differences in Ke being around 16% higher for DI than SDI. Moreover, the intra-annual Kc values moved in the same range for the initial, mid- and end-season crop growth stages, varying from 0.30 in 2019 to 1.01 in 2022, computed under standard conditions. Finally, the A&P approach was shown to be an especially interesting method for estimating Kcb values in almond fruit trees, being useful for refining Kcb and/or Kc for conditions of plant spacing, size and density that may differ from standard values. In this way, irrigation scheduling can be optimized regarding the almond tree architecture (i.e. fc eff and h), allowing to manage properly irrigation water to meet the tree water demands. 

Crop evapotranspiration (ETc) measurement is usually performed by sophisticated sensors that require high technical knowledge and that are not economically affordable for most end users. The objective of this work was to evaluate the performance of a novel LI-710 sensor for measuring ETc on a pistachio orchard. This simplified and easy-to-use sensor applies the Eddy Covariance (EC) method to measure water vapor flux between the surface and the atmosphere, however, it is cheaper and less complex than traditional EC heat flux system. The LI-710 sensor was installed together to an EC tower and the measurements provided by both methodologies were compared. Initial results evidenced a good agreement in terms of the evaluated meteorological variables, except for relative humidity, where higher discrepancies among sensors were observed. Regarding the sensible (H) and latent (LE) heat fluxes, the values measured by both methodologies were similar, with R2 values of 0.96 and 0.80; and RMSE values of 19 and 29 W m−2, respectively. These results suggest that LI-710 sensor can be a valid alternative to traditional EC systems for deriving ETc. However, LI-710 continues to have the fetch limitations presented in traditional methodologies, so future efforts should be paid to reduce this requirement increasing its usability in medium-small sized agricultural plots. 

The rapid growth in population, climate variability, and decreasing water resources necessitate innovative agricultural practices to ensure food security and resource conservation. This study investigates the effectiveness of various multispectral imagery from remote sensing (RS) platforms, Unmanned Aerial Systems (UAS), PlanetDove microsatellites, Sentinel-2, Landsat 8/9, and proximal MSR-5 in assessing crop biophysical characteristics (CBPCs) and actual crop evapotranspiration (ETa) for maize fields in northeastern Colorado. The research aims to evaluate the accuracy of vegetation indices (VIs) derived from these platforms in estimating key CBPCs, including leaf area index (LAI), crop height (Hc), and fractional vegetation cover (Fc), as well as ETa. Field experiments were conducted during 2022 at the USDA-ARS Limited Irrigation Research Farm in Greeley, Colorado, U.S.A., using different irrigation strategies. Surface reflectance data collected using a handled sensor and observed LAI, Hc, and Fc values, served as ground truth for validating RS estimates. The study applied various statistical analyses to compare the performance of different RS platforms and models. Results indicate that higher-resolution platforms, particularly UAS, provided higher accuracy in estimating VIs and CBPCs than satellite platforms. The study also highlights the influence of environmental conditions on the accuracy of RS models, with locally calibrated models outperforming those developed in dissimilar conditions. The findings underscore the potential of advanced RS technologies in enhancing precision agriculture practices and optimizing water resource management. 

Different methods exist to measure or estimate actual crop evapotranspiration (ETa). However, some methods require a large number of data input or strict field conditions. Remote sensing based ETa algorithms based on extreme thermal pixels (hot and cold) have limitations when required extreme pixels are not present in the acquired thermal infra-red imagery. In addition, satellite overpass frequency and spatial pixel resolution may be a limitation for some agricultural fields and micro-climates. Surface energy balance methods that use surface radiometric temperatures often fail to perform well under drought, limited irrigation, salt affected soils, or under sparse vegetation conditions. One option is to measure or estimate the crop/surface sensible heat flux through the aerodynamic temperature approach, then calculate the available energy and solve the energy balance for latent heat flux. Thus, this study presents different published algorithms that characterize the crop or field surface aerodynamic temperature and then applies them to different conditions for evaluation. Determining spatial ETa continuously has the potential to improve the irrigation water management decision making. The aerodynamic temperature approach was initially developed with good results as a function of surface radiometric temperature, air temperature, crop leaf area index, and wind speed or surface aerodynamic resistance. However, the inclusion of the crop fractional percent cover and of a new resistance term (turbulent-mixing row resistance) greatly improved the estimation of the sensible heat and latent heat fluxes, when evaluated with heat flux data derived from eddy covariance energy balance towers. Results also indicate that the aerodynamic method has transferability potential to different regions, crops, and irrigation methods than the conditions encountered in the method development.