CLIMATE-CHANGE AND THE DETECTION OF TRENDS IN ANNUAL RUNOFF

This study examines the statistical Likelihood of detecting a trend in annual runoff given an assumed change in mean annual runoff, the unde rlying year-to-year variability in runoff, and serial correlation of a nnual runoff. Means, standard deviations, and lag-1 serial correlation s of annual runoff were computed for 585 stream gages in the contermin ous United States, and these statistics were used to compute the proba bility of detecting a prescribed trend in annual runoff. Assuming a Li near 20% change in mean annual runoff over a 100 yr period and a signi ficance level of 95%, the average probability of detecting a significa nt trend was 28% among the 585 stream gages. The largest probability o f detecting a trend was in the northwestern U.S., the Great Lakes regi on, the northeastern U.S., the Appalachian Mountains, and parts of the northern Rocky Mountains. The smallest probability of trend detection was in the central and southwestern U.S., and in Florida. Low probabi lities of trend detection were associated with low ratios of mean annu al runoff to the standard deviation of annual runoff and with high lag -1 serial correlation in the data.