Time domain reflectometry (TDR) is an established method for the determination of apparent dielectric permittivity and water content in soils. Using current waveform interpretation procedures, signal attenuation and variation in dielectric media properties along the transmission line can significantly increase sampling error in estimating the time, t2, at which the pulse arrives at the end of the probe. Additionally, manual adjustment of waveform analysis parameters is frequently required in current software to accommodate changes in media properties when processing large time series of TDR measurements. Our objectives were to reevaluate conventional propagation time analysis and difficulties with these methods, introduce the AWIGF (adaptive waveform interpretation with Gaussian filtering) algorithm that circumvents these problems, and compare interpretation methods using waveforms obtained with different TDR instruments and under widely varying media properties. The AWIGF algorithm filters signal noise using Gaussian kernels with an adaptively estimated standard deviation based on the maximum gradient of the reflection at the termination of the probe. Two fitted parameters are required to scale the smoothing level for a given step pulse generator. Additionally, the maximum second derivative is used to evaluate t2. The AWIGF-determined t2 was compared with TACQ, a standard waveform interpretation algorithm. The strategies of AWIGF permitted the determination of t2 without parameter adjustment when the loss characteristics of the medium changed, such as with an increase in soil water content and bulk electrical conductivity. Using the new method, the sampling error of t2 was <0.06 ns across a wide range of medium properties and less than or equal to that obtained with TACQ. In strongly attenuated waveforms, the water content sampling error determined with AWIGF was 0.005 m3 m−3 compared with 0.038 m3 m−3 obtained using TACQ.