Laboratory Calibration and Performance Evaluation of LowCost Capacitive and Very LowCost Resistive Soil Moisture Sensors Soil volumetric water content (    V W C    ) is a vital parameter to understand several ecohydrological and environmental processes. Its costeffective measurement can potentially drive various technological tools to promote datadriven sustainable agriculture through supplemental irrigation solutions, the lack of which has contributed to severe agricultural distress, particularly for smallholder farmers. The cost of commercially available     V W C     sensors varies over four orders of magnitude. A laboratory study characterizing and testing sensors from this wide range of cost categories, which is a prerequisite to explore their applicability for irrigation management, has not been conducted. Within this context, two lowcost capacitive sensorsxe2x80x94SMEC300 and SM100xe2x80x94manufactured by Spectrum Technologies Inc. (Aurora, IL, USA), and two very lowcost resistive sensorsxe2x80x94the Soil Hygrometer Detection Module Soil Moisture Sensor (YL100) by Electronicfans and the Generic Soil Moisture Sensor Module (YL69) by KitsGuruxe2x80x94were tested for performance in laboratory conditions. Each sensor was calibrated in different repacked soils, and tested to evaluate accuracy, precision and sensitivity to variations in temperature and salinity. The capacitive sensors were additionally tested for their performance in liquids of known dielectric constants, and a comparative analysis of the calibration equations developed inhouse and provided by the manufacturer was carried out. The value for money of the sensors is reflected in their precision performance, i.e., the precision performance largely follows sensor costs. The other aspects of sensor performance do not necessarily follow sensor costs. The lowcost capacitive sensors were more accurate than manufacturer specifications, and could match the performance of the secondary standard sensor, after soil specific calibration. SMEC300 is accurate (    M A E    ,     R M S E    , and     R A E     of 2.12%, 2.88% and 0.28 respectively), precise, and performed well considering its price as well as multipurpose sensing capabilities. The lessexpensive SM100 sensor had a better accuracy (    M A E    ,     R M S E    , and     R A E     of 1.67%, 2.36% and 0.21 respectively) but poorer precision than the SMEC300. However, it was established as a robust, field ready, lowcost sensor due to its more consistent performance in soils (particularly the field soil) and superior performance in fluids. Both the capacitive sensors responded reasonably to variations in temperature and salinity conditions. Though the resistive sensors were less accurate and precise compared to the capacitive sensors, they performed well considering their cost category. The YL100 was more accurate (    M A E    ,     R M S E    , and     R A E     of 3.51%, 5.21% and 0.37 respectively) than YL69 (    M A E    ,     R M S E    , and     R A E     of 4.13%, 5.54%, and 0.41, respectively). However, YL69 outperformed YL100 in terms of precision, and response to temperature and salinity variations, to emerge as a more robust resistive sensor. These very lowcost sensors may be used in combination with more accurate sensors to better characterize the spatiotemporal variability of field scale soil moisture. The laboratory characterization conducted in this study is a prerequisite to estimate the effect of low and very lowcost sensor measurements on the efficiency of soil moisture based irrigation scheduling systems.

Estimation of water table depth using DUALEM2 system Abstract   Most of the agricultural fields are generally irrigated or drained uniformly without considering the spatial and temporal variation in water table depth (WTD). Investigating WTD is important for scheduling irrigation, drainage system designs and water balance models. The objective of this study was to develop a software interface to estimate the variations in WTD via electromagnetic induction (EMI) methods using frequencies of a DUALEM2 system. Two fields (Field 1: 45.38xc2xb0N, 63.23xc2xb0W and Field 2: 45.37xc2xb0N, 63.25xc2xb0W) were selected and thirty perforated observation wells were installed to calibrate the DUALEM2 for predicting WTD. Boundaries of the selected sites and location of the wells were marked using a real time kinematics global positioning system (RTKGPS). The user interface program was developed in Delphi 5.0 software and imported in a laptop computer to retrieve data from the DUALEM2 system. The horizontal coplanar (HCP) geometry, perpendicular coplanar (PRP) geometry and WTD were recorded simultaneously from each well before and after every significant rainfall for three consecutive days. Comprehensive surveys were conducted to measure apparent ground conductivity (ECa) with DUALEM2 and corresponding locations of the sampling points using Trimble Ag GPS 332. The regression model showed significant correlation between the HCP and WTD with coefficient of determination (R2xc2xa0xc2xa00.71) for field 1 and (R2xc2xa0xc2xa00.53) for field 2. Maps were generated in ArcGIS 10 software to examine the accuracy of predicted WTD in comparison with actual values. Results indicated that the DUALEM2 system was efficient in mapping variation rapidly and reliably in WTD in a nondestructive fashion rather than following conventional way of repeated well drilling for WTD determination. This information could be used for measuring the depletion of WTD during dry periods (droughts), sitespecific irrigation and drainage design with the aided advantage of labor and time savings in case of observing precision water management practices at large fields.