The knowledge of temporal variability of soil hydraulic properties (SHPs) in agricultural fields can help in reliable assessment of crop water requirement, thus improving irrigation water usage efficiency. The Fokker–Planck equation (FPE) and its modified forms are popularly used to describe temporal variation in SHPs. These models consider statistical description of soil pore size distribution (PSD) as a probability density function to estimate SHP evolution with time. In this study, we compare four different models to describe the temporal evolution of PSD and SHPs for multiple datasets across the world with different soil types, tillage conditions and crop cover. Further, field experiments were carried out at an experimental agricultural field at IIT Kanpur for rice crops, and the performance of these models was also evaluated for Indian conditions. It is observed that existing models have low accuracy for small pore radii values, and the prediction ability of these models is more affected by soil type rather than tillage conditions. More observations can improve the performance of FPE-based numerical and analytical models. The POWER Model is the least accurate because of its inherent power law assumption of PSD, which results in incorrect values for low pore radii. The FPE analytical model can be reliably used for predicting PSD and SHP evolution at most of the field sites.