The aim of this study was to develop methodologies and experimental procedures to determine textile parameters required in numerical approaches of heat and mass transfer through textiles. Privileging techniques usually available in textile/clothing laboratories, experimental approaches were defined that allow to estimate all required parameters, while taking into consideration water presence in the fibres and hence the effect of fibres hygroscopic properties. Numerical models usually require values of textile thickness, fibre fraction, and tortuosity, as well as knowledge of the boundary conditions, e.g. convective heat and mass transfer coefficients. To calculate these parameters, thickness, weight, and volume of textile samples were measured, whereas convective and textile evaporative resistances were determined by indirect measurements. Results were obtained for four distinct textile samples (made of wool, cotton, and a mixture of materials), of different hydrophilic nature. When the obtained parameters were incorporated in a numerical model and numerical predictions of temperature and humidity were compared with experimental data obtained during measurements of fabric evaporative resistance, it was shown that the predictions were accurate; this lends support to the developed methods and approaches. Since an uncertainty in the measured parameters can compromise the accuracy of numerical predictions, a sensitivity analysis was conducted to study the influence of deviations in the model input parameters and of assumptions regarding water presence in the fibres, on the predictions of heat and mass transfer rates. The results show that a deviation in textile weight and thickness as well as the assumption of no water retained in fibres during their characterisation, have a significant effect on the predicted heat transfer and water distribution over time. Moreover, a deviation in the total evaporative resistance, convective evaporative resistance, and sorption rate factor has great influence on the heat flux obtained in the initial period of testing. (C) 2014 Elsevier Ltd. All rights reserved.