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Remotely sensed data is an important tool for precision crop management. Satellite imaging systems and related-hand held instruments are frequently proposed for detection of crop stress caused by water, soil compaction and lack of nutrients, etc. This study was conducted to investigate how Bermuda grass reflectance changes with the onset of water stress. Four different irrigation treatments were examined: 100% (I 1 ), 75% (I 2 ), 50% (I 3 ) and 25% (I 4 ) of the evaporation measured in the Class A Pan. A non-irrigated plot was used as a control treatment (I 5 ). Spectral reflectance data were collected using a hand-held spectroradiometer which measured in the blue, green, red and near-infrared. Soil water content was monitored by a neutron probe. Water-stressed Bermuda grass (treatments I 4 and I 5 ) had lower spectral reflectance in near-infrared and higher reflectance in red wavebands than the other A07029;treatments. The results were statistically tested using one-way analysis of variance and Duncan's multiple range test. Highly significant relationships were found between different irrigation treatments and near infrared wavelengths (P <0.01, R 2 =0.94) and between the irrigation treatments and the normalised difference vegetation index (NDVI) (P < 0.01, R 2 = 0.80). Results indicate that different water stress on Bermuda grass could be determined by using spectral reflectance, especially NDVI and near-infrared reflectance regions. Analysis of experimental data indicated that it is possible to use remotely sensed data to develop maps of water stress conditions of Bermuda grass (Cynodon dactylon).