Abstract: Soil water characteristic curves are crucial for studying soil water dynamics and guiding irrigation. However, current soil water characteristic curve measurement systems face challenges such as interchange errors between multiple sensor probes, high costs, difficulty in field measurements, or limited to fixed-point measurements. This study designs an in-situ scanning monitoring system for multi-depth soil water information in farmland based on the frequency domain dielectric method. The system utilizes volumetric water content and matric potential data from different soil depths to derive soil profile moisture characteristic curves. The scanning monitoring system comprises a dielectric tube sensor module (including two sensor modules for moisture and matric potential measurement), a main control module, a 4G module, a solar power module, and an Alibaba Cloud monitoring module. The volumetric water content and matric potential measurement tubes are vertically installed in the soil to be tested. The main control module directs the dielectric tube sensors to scan and monitor soil moisture and matric potential at various depths (5-60 cm, at 5 cm intervals). Data collected are stored locally on an SD card and simultaneously uploaded to the cloud platform for remote monitoring and collection. For system installation, small-diameter drill bits (25 mm for the volumetric water content tube, 85 mm for the matric potential tube) are used to bore holes for placing the measurement tubes into the soil. The system allows flexible modifications to the total measurement depth, sensor probe measurement intervals, and measurement cycles based on actual needs. The overall system has low power consumption, with standby power at 0.62 W and working power at 2.4 W. Each operational cycle lasts about 2 minutes, with an hourly power consumption of 0.68 W·h. The solar panel battery capacity is 3×10⁴ mAh with a rated voltage of 12 V, enabling long-term field monitoring under adequate sunlight conditions. The effective response radius of the sensors is determined by incrementally increasing the soil layer height until the sensor output stabilizes, which is 30 mm for the matric potential measurement tube. This value is used as the gypsum thickness for the matric potential tube. The sensors were calibrated for volumetric water content using soil samples with different water contents, achieving a calibration curve determination coefficient of 0.991. For soil matric potential calibration, a commercial matric potential sensor (TEROS-21) was used, resulting in a calibration curve determination coefficient of 0.989, indicating good consistency within the measurement range. Field trials of the system were conducted in a demonstration field of returning green winter wheat. The system measured a total depth of 60 cm, with intervals and cycles of 5 cm and 1 hour, respectively. Results from the field trials indicate that the system can accurately monitor dynamic changes in soil profile volumetric water content and matric potential within the winter wheat root zone. The soil profile moisture characteristic curve derived from these data shows that water consumption in the 0-20 cm layer is due to both root absorption and surface soil evaporation. The main root absorption area for winter wheat during the regreening period is at 25-45 cm, while the 50-60 cm layer, with fewer roots, maintains higher soil water content. These experimental results demonstrate that the system not only enables in-situ determination of soil profile moisture characteristic curves but also provides essential data and technical support for observing soil moisture changes in crop root zones, assessing soil water retention capacity, and guiding intelligent water-saving irrigation.