The spatial distribution of cotton yields in the Khorezm region exhibits larger differences than those indicated in statistics on a district scale. However, the yield distribution within districts and farms, and possible factors correlating with this pattern, are unclear. Here, we map and characterize the detailed spatial variation of cotton yield at a pixel size of 250 m and analyse relationships between cotton yield, environmental factors, hydrological infrastructure, and water management in Khorezm for the year 2002. A remote-sensing based yield modelling approach was employed using satellite data of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and the MODerate resolution Imaging Spectroradiometer (MODIS). Regional GIS maps were developed for environmental factors such as soil texture and groundwater table, hydrological infrastructure (distance of water use associations to irrigation inlets, ­irrigation channel density, and seasonal actual evapotranspiration). Well-pronounced relationships were found between cotton yield and the factors soil texture, irrigation infrastructure and seasonal evapotranspiration, while the correlation was weaker between cotton yield and groundwater table. These correlations were spatially analyzed and interpreted to identify areas suitable for cotton cultivation. Soil zones with lower cotton yield and areas with an irrigation infrastructure less suitable for cotton were spatially demarcated; for these areas, alternative land use strategies are suggested. Overall, this study suggests that improved surface and groundwater management should be targeted to specific sites within certain soil zones, and needs to be delivered timely according to crop requirements. These are key regional management strategies for improving cotton yield on a regional scale in Khorezm. We demonstrated that information on where and when water management improvements should take place can be suitably provided for larger areas with a remote sensing approach. The remote sensing-based monitoring system allows evaluating area-wide indicators for irrigation performance on different scales. The information thus gained can then be delivered to local water users associations for their adaptation.