This project investigated new techniques for improving seismic event locations derived from regional and local networks. The technqiues include a new approach to empirical travel-time calibration that simultaneously fits data from multiple stations and events, using a generalization of the kriging method, and predicts travel-time corrections for arbitrary event-station paths. We combined this calibration approach with grid-search event location to produce a prototype new multiple-event location method that allows the use of spatially well-distributed events and takes into account correlations between the travel-time corrections from proximate event-station paths. Preliminary tests with a high quality data set from Nevada Test Site explosions indicated that our new calibration/location method offers improvement over the conventional multiple-event location methods now in common use, and is applicable to more general event-station geometries than the conventional methods. The tests were limited, however, and further research is needed to fully evaluate, and improve, the approach. Our project also demonstrated the importance of using a realistic model for observational errors in an event location procedure. We took the initial steps in developing a new error model based on mixture-of-Gaussians probability distributions, which possess the properties necessary to characterize the complex arrival time error processes that can occur whenmore » picking low signal-to-noise arrivals. We investigated various inference methods for fitting these distributions to observed travel-time residuals, including a Markov Chain Monte Carlo technique for computing Bayesian estimates of the distribution parameters.« less