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To combat China’s water crisis tremendous research efforts are undertaken aiming at the improvement of water management in cotton production, which is the major consumer of the scarce water resources in arid Northwestern China. In recent years extensive field experiment based research strongly enhanced the theoretical knowledge of optimal water management in cotton production. However, farmers’ actual irrigation water productivity remains low. To fill the critical void the present study aims at increasing the understanding of Chinese cotton farmers’ actual irrigation water management. The northwestern Chinese Aksu-Tarim Region was selected as a hot-spot of water scarcity in China, where around 60% of total sown crop land are cultivated with cotton. The increasing overuse of scarce surface water resources for irrigation not only leads to severe ecological degradation, but also increases competition among water users triggering the expansion of groundwater exploitation. Based on primary survey data of 228 cotton producing farm households we firstly analyze the production factors determining farmers’ yield and irrigation water productivity (IWP). Apart from soil salinity and unbalanced fertilization, which negatively affect yield and IWP, especially the applied irrigation method (drip vs. flood irrigation) and installation of a groundwater well were identified as major determinants. Secondly, we apply logistic regression to evaluate which household and farm characteristics determine the irrigation method and installation of groundwater well. We find that farm size, crop types and cropping intensity determine the use of drip irrigation. We furthermore find that the installation of well is largely related to marginalization, with farm families of ethnic minorities, remote farms and lower educated families being more likely to install wells. The findings of our study can help policymakers in devising strategies for improving irrigation water productivity, while reducing groundwater degradation in the study region and similar arid production regions in the world. (C) 2017 Elsevier B.V. All rights reserved.