Canopy temperature is generally accepted as an indirect but rapid, accurate, and large-scale indicator of crop water status and is, therefore, proposed to monitor irrigation needs. Crop Water Stress Index (CWSI) is the most widely used among the existing thermal-based indicators, and its links with water stress have been demonstrated. When calculating CWSI using the empirical approach, the differential between canopy and air temperature is normalized by two thresholds, also known as baselines. The Non-water stress baseline (NWSB) in the empirical approach is calculated as the relationship between T_c–T_a (°C) and the vapor pressured deficit (VPD, kPa) for well-irrigated crops. The baselines display different slopes depending on the species, which have a significant impact on the computed CWSI. This study analyzed the resulting errors on CWSI due to the measurement errors of critical inputs needed for its calculation. Six crop species were selected according to their NWSB with slopes that range from − 0.5 to − 3 °C·kPa⁻¹ and used for this analysis, assuming measurement errors ranging 0.2–1 °C for T_a, 0.25–2 °C for T_c, and 5–10% for relative humidity (RH). It was concluded that the effects observed on CWSI are heavily dependent on the slope of the NWSB and therefore vary across species. The calculation was very sensitive to the bias in air and canopy temperature. These errors were maximal as the slope of the NWSB was less steep. When the VPD ranged from 2 to 6.6 kPa, an error of 1 °C in measuring the air temperature affected CWSI between 28 and 83% in orange, which is the species displaying the minimum slope (− 0.5 °C kPa⁻¹). On the contrary, crops with steeper baseline slopes such as squash (− 3 °C kPa⁻¹) showed errors ranging between 2 and 8% for the same VPD interval. This differences among the different crops species considered in this study may be related to the contrasting coupling of the species to the atmosphere, that determines the influence of vapor pressure on the transpiration rate. This study highlights the importance of reliable climatic data and the need for accurate calibrated thermal sensors to calculate CWSI accurately.