Using Rainfall‐Induced Groundwater Temperature Response to Estimate Lateral Flow Velocity

This study introduces a novel heat tracing method for estimating lateral groundwater flow velocity induced and sustained by heavy rainfall events in lowland areas, leveraging the distinct temperature difference between rainfall and groundwater. The method is motivated by the observation that the rainfall‐induced groundwater temperature signal dissipates along the flow path. To explain the observed temperature anomaly and then estimate the lateral flow velocity, we develop a semi‐analytical model for heat transport in the aquifer, accounting for conduction losses to adjacent layers. Our findings reveal that interactions between the aquifer, vadose zone, and bedrock significantly influence the temperature signal, thereby affecting velocity estimation. Inaccuracies in measured aquifer properties, such as thickness, porosity, and thermal conductivity of surrounding layers, increase the uncertainty of velocity estimates. However, variations in aquifer thermal conductivity have a minimal effect on the method's overall accuracy. When estimating multiple parameters, velocity estimates tend to be less reliable, especially if aquifer porosity remains uncertain. This is due to the challenges of simultaneously inverting both velocity and porosity. Overall, this work underscores the potential of using heat as a tracer for assessing lateral groundwater flow following rainfall, offering a practical, low‐cost solution applicable in a wide range of settings. Plain Language Summary This study presents a new method of estimating the velocity of groundwater flowing in lowland hillslope areas, particularly during heavy rainfall. The method uses the difference in temperature between rainwater and groundwater to track the groundwater's flow. By analyzing observed temperature changes based on a semi‐analytical approach, we can estimate how fast the groundwater moves. Our findings reveal that interactions between the shallow aquifer, unsaturated soil zone, and bedrock significantly influence the temperature signal, impacting velocity estimation. Inaccuracies in measured aquifer properties, such as thickness, porosity, and surrounding layers' thermal conductivity, can adversely impact velocity estimations. Nevertheless, thermal conductivity of the aquifer layer itself doesn't noticeably affect the accuracy of this method. It is challenging in getting accurate velocity estimations when trying to estimate multiple parameters at once, especially when the aquifer porosity remains uncer