Monitoring Crop Evapotranspiration and Crop Coefficients over an Almond and Pistachio Orchard Throughout Remote Sensing

Abstract

In California, water is a perennial concern. As competition for water resources increases due to growth in population, California's tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (K cb ), or potential crop water use. The soil water evaporation coefficient (K e ) was measured from microlysimeters. The water stress coefficient (K s ) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ψ stem ). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum K cb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an R 2 ≥ 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm·day −1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions.

Characterizing Crop Water Use Dynamics in the Central Valley of California Using Landsat-Derived Evapotranspiration

“…Almonds and pistachios are two high-value crops that have a reputation of being drought tolerant [37]. Previous studies have suggested that California needs 173,000 ha-m annually for almond and pistachio production [37]. The results of this study show the actual water use of almonds and pistachios to be closer to an annual average of 380,000 ha-m in raw water use and 250,000 ha-m in net irrigation once precipitation has been removed.…”

“…Almonds and pistachios are two high-value crops that have a reputation of being drought tolerant [37]. Previous studies have suggested that California needs 173,000 ha-m annually for almond and pistachio production [37].…”

Phenological Dynamics Characterization of Alignment Trees with Sentinel-2 Imagery: A Vegetation Indices Time Series Reconstruction Methodology Adapted to Urban Areas

“…Finally, this methodology is generic and appears as applicable on any large-enough group of mono-species urban vegetation, the main limitation being the resolution of the satellite used in the study. The phenology of mono-species grouped trees located in non-urban environments where mixed pixel problems can appear, such as in orchards [75,76] or woodlands/savannas [77][78][79], might be also studied with the proposed methodology.…”

UAV Multispectral Imagery Combined with the FAO-56 Dual Approach for Maize Evapotranspiration Mapping in the North China Plain

“…For decades, satellite remote sensing images have been the main data sources to integrate the FAO-56 for the estimation of crop ET. For example, Bellvert et al [19] used a dataset of the vegetation index (NDVI) derived from Landsat-8 to facilitate the estimation of the Kcb, and potential crop water use. However, the low spatial and temporal resolution of satellite data limits its further application in estimating ET within the field scale.…”