5:15 PM - 7:15 PM
[AHW25-P10] Integration of an IoT-Based Temperature Monitoring System and Heat Transfer Model for Long-Term Infiltration Observation and Determination
Keywords:Irrigation Infiltration of Paddy Field, IoT-Based Temperature Monitoring System, Heat Transfer Model
The key to sustainable groundwater management lies in maintaining the balance between groundwater recharge and usage. Therefore, accurately quantifying groundwater recharge is a critical prior information for sustainable management. This study aims to investigate and monitor long-term groundwater recharge using heat transport as a tracer. To achieve this, a hybrid framework integrating software-based analysis and hardware-based monitoring is developed.
The entire observation system consists of five temperature sensors positioned at depths of 10, 25, 50, 75, and 100 cm below the surface. A remote transmission device is employed to transmit real-time data at 10-minute intervals. Solar panels and batteries provide the necessary power, enabling the monitoring system to operate continuously without external power support. For determining infiltrations, VFLUX, a Vertical Fluid Heat Transfer Solver, is proposed. VFLUX analyzes paired temperature signals at different depths. Due to the diurnal cycle, periodic temperature variations propagate downward with infiltration, causing a reduction in amplitude due to thermal diffusion. By analyzing the amplitude ratio between shallow and deep temperature signals, infiltration rates can be estimated. This study integrates VFLUX with observational data using Python, enabling infiltration rate updates every six hours.
The monitoring system was deployed in a paddy field in Changhua County, middle of Taiwan, to investigate infiltration rates at different rice growth stages. It was installed in early July 2023 and has been continuously operating for over 20 months, covering three rice cultivation cycles. During the early growth stage, rice seedlings are transplanted, and the field is irrigated to maintain a certain water depth, which supports root development and prevents cold stress (first-season rice). The estimated infiltration rate of the early growth stage, lasts approximately two weeks, is about 14 mm/day. If soil tillage is conducted before planting to loosen soil structure from the surface to 1 meter depth, short-term infiltration rates can increase significantly to 30 mm/day, approximately 2.1 times higher. However, as irrigation continues, the soil structure stabilizes, and the enhanced recharge effect lasts only about two weeks. After the tillering stage, infiltration rates decrease dramatically. Because excessive irrigation weakens plant growth, the appropriate irrigation volume aligns with the crop’s water demand, and after root water uptake, only a minimal amount of water infiltrates downward for recharge. Since the sensors are embedded in the soil, plowing and loosening the surrounding soil might damage the sensors. As a result, soil pores gradually become clogged by suspended particles in the irrigation water, leading to a continuous decline in soil infiltration capacity. Observations over a 20-month period indicate that the infiltration rate decreases by approximately 30% to 40% per year.
This study has successfully developed a long-term infiltration monitoring and estimation framework. Compared to the conventional water balance method, which evaluates infiltration rates based on inflow and outflow measurements in paddy fields, this system provides a micro-scale observation approach with higher spatiotemporal resolution. Additionally, beyond agricultural irrigation monitoring, this framework can also be applied to artificial recharge assessment. By analyzing the decline in infiltration rates over time, it can help determine the optimal timing for tilling and cleaning infiltration basins to restore infiltration capacity.
The entire observation system consists of five temperature sensors positioned at depths of 10, 25, 50, 75, and 100 cm below the surface. A remote transmission device is employed to transmit real-time data at 10-minute intervals. Solar panels and batteries provide the necessary power, enabling the monitoring system to operate continuously without external power support. For determining infiltrations, VFLUX, a Vertical Fluid Heat Transfer Solver, is proposed. VFLUX analyzes paired temperature signals at different depths. Due to the diurnal cycle, periodic temperature variations propagate downward with infiltration, causing a reduction in amplitude due to thermal diffusion. By analyzing the amplitude ratio between shallow and deep temperature signals, infiltration rates can be estimated. This study integrates VFLUX with observational data using Python, enabling infiltration rate updates every six hours.
The monitoring system was deployed in a paddy field in Changhua County, middle of Taiwan, to investigate infiltration rates at different rice growth stages. It was installed in early July 2023 and has been continuously operating for over 20 months, covering three rice cultivation cycles. During the early growth stage, rice seedlings are transplanted, and the field is irrigated to maintain a certain water depth, which supports root development and prevents cold stress (first-season rice). The estimated infiltration rate of the early growth stage, lasts approximately two weeks, is about 14 mm/day. If soil tillage is conducted before planting to loosen soil structure from the surface to 1 meter depth, short-term infiltration rates can increase significantly to 30 mm/day, approximately 2.1 times higher. However, as irrigation continues, the soil structure stabilizes, and the enhanced recharge effect lasts only about two weeks. After the tillering stage, infiltration rates decrease dramatically. Because excessive irrigation weakens plant growth, the appropriate irrigation volume aligns with the crop’s water demand, and after root water uptake, only a minimal amount of water infiltrates downward for recharge. Since the sensors are embedded in the soil, plowing and loosening the surrounding soil might damage the sensors. As a result, soil pores gradually become clogged by suspended particles in the irrigation water, leading to a continuous decline in soil infiltration capacity. Observations over a 20-month period indicate that the infiltration rate decreases by approximately 30% to 40% per year.
This study has successfully developed a long-term infiltration monitoring and estimation framework. Compared to the conventional water balance method, which evaluates infiltration rates based on inflow and outflow measurements in paddy fields, this system provides a micro-scale observation approach with higher spatiotemporal resolution. Additionally, beyond agricultural irrigation monitoring, this framework can also be applied to artificial recharge assessment. By analyzing the decline in infiltration rates over time, it can help determine the optimal timing for tilling and cleaning infiltration basins to restore infiltration capacity.