Investigating time series variations of total precipitable water (TPW) vapor is of great importance in meteorology and hydrology. The objective of this study is to use two nonparametric tests including Mann–Kendall and Sen’s slope estimator to investigate the annual and seasonal trend of TPW changes using two remote sensing datasets and a ground dataset in western Iran. The daily near-infrared product of TPW from Moderate Resolution Imaging Spectroradiometer (MODIS), MOD05, and a daily TPW extracted from a developed regional TPW MODIS algorithm were considered as remote sensing data. The remote sensing estimations were utilized in six climatic zones, including hyperarid, arid, semiarid, semihumid, humid, and hyperhumid. For the ground data, the daily TPW was prepared from five radiosonde stations. At a significance level of 0.05, in the annual trend, MOD05 results showed a significant increase in the hyperarid, semiarid, semihumid, and hyperhumid climates, and regional MODIS TPW algorithm results showed a significant increase in all six climates. In the seasonal trend of spring in the Ahvaz radiosonde station, as well as in the seasonal trend of summer of MOD05 results in the hyperarid, arid, semihumid, and humid climates, there was a significant increase. Regional MODIS TPW algorithm results demonstrated a significant increase trend in all six climates in the spring and summer. Generally, the results proved the TPW incremental trend in the study area.