Understanding spatio-temporal variability of soil moisture measurement with aquaflex and time domain reflectrometry

For management of agricultural water, accurate soil moisture (SM) determination is an essential component. Two objectives of this study were: (1) to understand spatio-temporal variability of volumetric SM measurements using multiple length TDR probes and aquaflex sensor; and (2) to couple TDR and aquaflex SM readings to improve soil moisture estimation in non-weighing lysimeters. TDR probes with 200, 500 and 900 mm lengths were installed vertically adjacent to the aquaflex and lysimeters for monitoring volumetric SM contents without disturbing natural water fluxes in the lysimeters. Both TDR and aquaflex responded to simulated wetting and drying events, with varying SM measurements observed both vertically and horizontally, due to variations in soil types at different locations. The amplitude of the daily fluctuations in SM measurements were noticeably higher for 200 and 500 mm TDR and aquaflex sensors. However, 900 mm TDR showed only minor fluctuations in average SM values indicating pasture water uptakes dominates in the top 500 mm soil profile. This indicates the importance of multiple length TDR to assess root water uptake for improving irrigation management. Twenty Lysimeters and an aquaflex located about 125 m away from the lysimeters within different soils were utilized to derive a relationship between crop coefficient of pasture (Kc) and plant canopy (h). When same aquaflex soil moisture values were used in the water budget equations for 20 lysimeters data, coefficient of determination (R2) for Kc – h relationship was 0.43, which increased to 0.66 when aquaflex SM values were adjusted for each lysimeter using corresponding TDR readings. For rotational grazing systems, Kc derived from the improved Kc – h relationship would save “on average” 10% irrigation compared to when Kc derived from the original Kc – h relationship. This implies improved monitoring of SM at different locations in the farm is essential to improve the water budget for quantifying actual irrigation requirements