Hydroacoustic sampling can be an important technique for estimating fish entrainment rates at hydroelectric facilities applying for relicensing by the U.S. Federal Energy Regulatory Commission. Existing sampling procedures typically require daily monitoring of entrainment over at least one annual cycle. To investigate potential cost savings through the use of probability sampling, three data sets consisting of daily hydroacoustic estimates of entrainment for at least l year were reanalyzed to determine the effects of subsampling on the precision of seasonal and annual estimates of fish entrainment. The study sites were located in New York, Wisconsin, and South Carolina. When a stratified random sample of days within each month was used, a 50% subsample of days (i.e., 15 d/month) resulted in a sampling precision of approximately ±22.0% of the true value of annual entrainment at the New York site, ± 14.3% at Wisconsin, and ±9.6% at South Carolina, 95% of the time, Sampling 20 d/month resulted in a precision of ± 15.5%, ± 10.0%, and ±6.7%, respectively, 95% of the time, Substantial cost savings appear possible through the use of stratified random sampling designs that provide a level of precision sufficient for both management and relicensing decisions.

Abundance estimates of out‐migrating sockeye salmon Oncorhynchus nerka smolts are used to prepare preseason forecasts of adult returns and to set escapement goals. Here we describe a method for estimating smolt flux and abundance that uses side‐looking sonar. This method more efficiently covers the river cross section and is logistically easier to deploy than up‐looking sonar systems. To account for the skewed vertical distribution of smolts, we used a recently developed model for correcting echo integration bias associated with nonuniform target distribution. The correction is based on adjusting the integrated beam pattern for a given distribution of targets relative to the transverse cross section of the beam. We compared the results with estimates derived from video data and modeled the effect of three vertical distributions of smolts and three transducer pitch angles. The model estimated correction factors that ranged from 0.6 to 2.6. Correction factors were greater than 1 (which indicates negative bias in conventional echo integration) for smolt distributions skewed toward the edge of the beam and less than 1 (which indicates positive bias in conventional echo integration) for distributions skewed towards the center of the beam. For the scenarios modeled, the effect of the transducer pitch angle was small between the horizontal and −0.6° but increased nonlinearly as the angle increased. We conclude that, in the given application and at shallow transducer pitch angles, the bias in conventional echo integration is small and predictable enough to be corrected.