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To figure out the driving factors of irrigation water demand and an effective way for relieving the sharp contradiction between the supply and demand of agriculture water resources in the Heihe River basin of Northwest China, a conventional method in estimating irrigation water demand was modified by incorporating the simulations of Soil and Water Assessment Tool (SWAT) model with its distributed hydrological response units (HRUs). Simultaneously, a new factor decomposition model for irrigation water demand was created using the extended Kaya identity. Moreover, the additive and multiplicative forms of the logarithmic mean Divisia index (LMDI) decomposition were used to quantify the variation of driving factors in irrigation water demand from 1985 to 2014. The results show that total irrigation water demand in this arid region had increased by 3.249 x 10(8) m(3) over the past 30 years. These contributions are arising from the following four driving factors - planting scale, planting pattern, climate change and water saving technology (e.g., drip irrigation, sprinkler irrigation, etc.) with respective contribution of irrigation water demand of 1.981 x 10(8) m(3), 0.933 x 10(8) m(3), 1.523 x 10(8) m(3) and 1.188 x 10(8) m(3). The corresponding average contribution rates of these driving factors are 60.96%, 28.72%, 46.86% and 36.53%, respectively. Although the effects of the four drivers on the irrigation water demand for various crops over three periods (i.e., 1985-1994; 1995-2004; 2005-2014) are inconsistent, both the planting scale and the cropping pattern increase the irrigation water demand. Water saving technologies as known have inhibited water demand, but climate change turns out to increase the demand and then inhibit it. Therefore, to reduce the irrigation water demand and develop a proper irrigation water planning in Heihe River basin, it is beneficial to regulate the scale of agricultural development, adjust the agriculture pattern by reducing the area planted with crops that consume relatively large amounts of water (i.e. spring corn and vegetables), identify agricultural water saving potential and decrease the impact of climate change. (C) 2018 Elsevier Ltd. All rights reserved.