The paucity of critical results in the field sciences is partly the result of ineffective data collection. Multiple samples must be collected to take advantage of the power of inferential statistics, but the number of samples needed may be minimized by using efficient sampling methods. This study shows that for gravel river bars characterized by the presence of several unevenly distributed facies, the grid technique for sample selection is one of the best and easiest to use in the field. A special combination of grid and random techniques, known as systematic unaligned sampling, performs slightly better, but site selection and navigation in the field are more complex. Random sampling performs less well than either of the other methods. If the sampling question requires estimation of a statistic to represent the entire area or volume, rather than estimates of the variability within and between different zones of the area or volume, then the use of composite sampling further reduces the sampling effort required. A few replications of these composite samples will provide an estimate of the mean and standard deviation of a population statistic which can be used to construct confidence limits about the estimated statistic.