Impingement is the process of entrapment of fish on intake screens at power plants, a process that generally results in mortality. Minimizing adverse effects due to impingement is an objective of ^§316(b) of the U.S. Clean Water Act. To obtain an estimate of the extent of impingement on the Ohio River and to examine factors that may be controlled to minimize it, power companies initiated an innovative collaborative sampling program. Ten companies, encompassing 15 plants collaborated with the Electric Power Research Institute in developing the experimental design, implementing sampling over a two-year period (2005-2007), and analyzing the data. The design was developed using model-based small area estimation. The fundamental concept of the model-based approach is that prediction of the variable of interest (impingement) can be improved by including information in the model that comes from outside of the target population (e.g., impingement data from neighboring plants). This method assumes all plants have similar seasonal trends an assumption confirmed with historical data. Based on historical patterns, the high impingement season (July-January) was partitioned into 14 periods of 14 days and the low impingement season (February-June) had six 28-day periods. A 24 hour sample was collected at each plant during each period. All information was pooled to estimate the model parameters (coefficients in the equation) and variance terms. Combining data across plants increased sample size per period and allowed better estimates of seasonal trends and the impingement estimates. Confidence intervals are based on a parametric bootstrap procedure. This presentation will review the experimental design, data analysis, problems encountered and overall utility of the approach. Actual results, including seasonal and monthly estimates of impingement at each plant and measures of variability will be reviewed.

Keywords: Impingement; Sampling Design; Model-based Estimation; Fisheries ecology

Biography: Doug Dixon is a Technical Executive at the Electric Power Research Institute and manager of its Fish Protection Research Program. He has over 40 years of expereince in environmental impacrt assessment and power plant studies. He received a PhD in Marine Fisheries Science from the College of William & Mary, Virginia Insitute of Marine Science and BA in Zoology from the State University of New York at Geneseo.