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This study aims to assess the impact of localized as well as open-field weather data on geospatial transpiration (T) for a modern apple orchard, mapped using energy balance modelling approach. Open-field weather data was collected from five stations and all-in-one weather sensors within 0–3 km from the orchard-center whereas in-orchard weather data was collected at 0.8 m and 1.8 m above ground level. Pertinent model also uses aerial multispectral and thermal infrared imagery data as standard inputs which were collected in five campaigns during the growing season. Significant deviations in solar radiation, wind speed, relative humidity, air temperature, and reference evapotranspiration (Coefficient of variation: 3–55%, Pearson linear correlation [r]: 0.7–1) was observed for open-field weather stations surrounded by different heterogeneous crops. Relatively low deviations were observed for standard open-field weather station (3 km from orchard-center) and the one outside the orchard (100 m from center). Proportional variation in T estimates were also observed with lowest deviation for weather inputs from nearest open-field station and the all-in-one weather sensor (r: 0.85–0.97, Root mean square difference: 3–13%). Deviations in T estimates were also observed for in-orchard weather data inputs from all-in-one weather sensors installed at different canopy heights (r: 0.6–0.98). The results suggest that crop mapping at high resolution and in-orchard weather data inputs could better estimate crop water use (T).
Washington State University, United States
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Download from Proceedings of IEEE 2021 International Workshop on Metrology for Agriculture and Forestry