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Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Applied Engineering in Agriculture. Vol. 17(6): 787–795 . (doi: 10.13031/2013.6848) @2001
Authors:   S. Irmak, D. Z. Haman
Keywords:   Granular matrix sensors, Performance, Soil matric potential, Soil water content, Irrigation scheduling, Optimization

The Watermark  granular matrix sensor (GMS) is relatively inexpensive and provides a continuous and indirect measurement of soil matric potential (SMP). By using five different calibration equations, the performance of model 200SS Watermark GMS for estimating SMP from the sensor resistance was evaluated for two different sandy soils (Dothan loamy fine sand and Astatula fine sand). The performance of the calibration equations was compared with the mercury manometertensiometer measured SMP. A simple optimization procedure was used to reparameterize existing calibration equations for estimating SMP from sensor resistance in two selected sandy soils. An approximate relationship between sensor resistance versus soil water content (SWC) was determined for the Dothan soil.

All calibration equations published to date significantly overestimated (less negative or wetter soil) SMP in both soils. The poor performance of the calibration equations was found to be more severe in the Astatula soil, which had a coarser texture than the Dothan soil. The SMP calibration equations developed in this study for the two soils showed high correlation between sensor resistance and mercury manometertensiometer measured SMP. A linear resistanceSMP relationship was observed within the ranges of approximately 10 to 80 kPa and 11.5 to 23 kPa for the Dothan and Astatula soils, respectively. The GMS did not respond to changes in SMP at potentials higher than approximately 10 and 11.5 kPa in the Dothan and Astatula soils, respectively. Optimization results showed that calibration equations with optimized parameters can successfully be used to estimate SMP for the soil in which the parameters were optimized. However, applying the same equation with the optimized parameters to estimate SMP in the other soil type resulted in poor SMP estimates. The Watermark GMS was calibrated to estimate SWC from the sensor resistance for Dothan soil between the SWC range of approximately 15 to 41.2% on volumetric basis. The relationship between SWC and GMS resistance was described by an exponential decay function.

It was concluded that the upper limits of the Watermark GMS (10 and 11.5 kPa) obtained in this study present a limitation of using Watermark GMS for irrigation scheduling in sandy soils where 10 kPa is often used as a point for triggering irrigations. However, the results showed that the GMS can be used to estimate SMP from sensor resistance at potentials lower than 10 and 11.5 kPa SMP in Dothan and Astatula sandy soils, respectively, by using the calibration equations developed in this study.

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