As infrastructure develops and adoption of smart water meters increases, new techniques are needed to validate and learn from the large datasets they produce. Patterns of leading digits (i.e., first non-zero digits, 1 through 9) can support this task. This study examines leading digits in hourly smart meter readings from a western U.S. water utility with over 5,000 customer connections. Benford analysis, power law analysis, and leading-digit-frequency analysis all indicate that the readings tend toward values that start with 1. The findings suggest that readings from smart water meters - and, by extension, water use by individual customers - could be expected to follow a particular nonuniform pattern of leading digits and that deviation from the pattern may indicate data errors or abnormal water use. Applications are suggested for validating water use data, comparing multiple datasets, checking projections, and assessing meter performance. Additional work is needed to further explore the beneficial uses of leading-digit patterns and other data signatures in water use data from diverse datasets.