Measuring soil moisture content (SMC) in mining waste rock is important for assessing and modelling hydrological processes which influence pollutant release. Here, an experimental setup containing mining waste rock is established to compare the performance of 4 Arduino capacitance moisture sensors to one single Time Domain Reflectometry (TDR) sensor. Furthermore, the performance of these sensors is evaluated in both sieved and unsieved mining waste rock. Fitted calibration curves are provided for both the TDR- and Arduino-sensors individually and in combination. These calibration curves are evaluated using the RMSE and R 2 of each curve and compared between sensors and soil texture. It is concluded that using more capacitance sensors significantly improves the fit statistics of the calibration curves and that using at least 4 capacitance sensors can enhance calibration curve fitting. For both the TDR and capacitance sensors, the calibration curves in sieved soil provided the best fit, meaning that soil specific calibration of sensors is recommended. On a sensor individual basis, the temporal precision of the TDR sensor was superior to each individual capacitance sensor. Use of 4 or more Arduino capacitance sensors may especially be justified in circumstances where the spatial variability of SMC is addressed by executing a large number of measurements. Here, the feasibility of the Arduino sensor system means that the use of these low-cost sensors, despite their reduced temporal precision, can be upscaled at relatively small costs.