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Interreplicate variability-the spread in output values among units of the same sensor subjected to essentially the same condition-can be a major source of uncertainty in sensor data. To investigate the interreplicate variability among eight electromagnetic soil moisture sensors through a field study, eight units of TDR315, CS616, CS655, HydraProbe2, EC5, 5TE, and Teros12 were installed at a depth of 0.30 m within 3 m of each other, whereas three units of AquaSpy Vector Probe were installed within 3 m of each other. The magnitude of interreplicate variability in volumetric water content (θ v) was generally similar between a static period near field capacity and a dynamic period of 85 consecutive days in the growing season. However, a wider range of variability was observed during the dynamic period primarily because interreplicate variability in θ v increased sharply whenever infiltrated rainfall reached the sensor depth. Interreplicate variability for most sensors was thus smaller if comparing digitalcommons.unl.edu

Crop nitrogen (N) status is known to affect crop water status and crop water use. To investigate further the N effects on soil water changes and on canopy temperature, three water levels × four N levels were imposed on two growing seasons of maize in west central Nebraska, USA. Soil water changes were measured using a neutron probe, whereas canopy temperature was measured using infrared thermometers on a ground-based mobile platform. At all water levels, soil water losses over monthlong intervals were generally greater as N levels increased. Given equal water levels, early afternoon canopy temperatures were usually lower with higher N levels, but no trend or even the opposite trend was occasionally observed. Jointly considering canopy reflectance and soil water depletion shows potential to explain much of the variation in estimated instantaneous water use among plots. However, determining the relative contributions of the canopy and soil factors on a particular day may require season-to-date knowledge of the crop. Further research on assimilating such sensor data for a combined stress coefficient would improve crop modeling and irrigation scheduling when variable water sufficiency and variable N sufficiency are simultaneously significant.

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