The Next Generation Attenuation Relationships for Central & Eastern North-America (NGA-East) Geotechnical Working Group (GWG) has presented models for site amplification in Central and Eastern North America that represent a significant change from past practice, which was based on models developed for active tectonic regions. The GWG models are ergodic in their formulation, meaning that they produce an average level of amplification conditional on VS30 and other the site parameters. We illustrate the application of these models to four sites in Texas, South Carolina, Mississippi, and New York City, and compare results with site-specific ground response analyses. The results indicate that substantial advantage is possible when ergodic models conditioned only on VS30 are supplemented with a modular term that produces a peak at one or more site natural periods ( Tnat). The article demonstrates features and limitations of the GWG models for sites in Central and Eastern North America and provides useful recommendations for coupling ergodic and non-ergodic (site-specific) modeling as part of seismic hazard studies.

In recent years, global optimization algorithms are used in many engineering applications. Calibration of certain parameters at conceptualization of hydrological models is one example of these. An important issue in interpreting the effects of climate change on the basin depends on selecting an appropriate hydrological model. Not only climate change impact assessment studies, but also many water resources planning studies refer to such modeling applications. In order to obtain reliable results from these hydrological models, calibration phase of the models needs to be done well. Hence, global optimization methods are utilized in the calibration process. In this chapter, the differential evolution algorithm (DEA), which has rare application in the hydrological modeling literature, was explained. As an application, the use of the DEA algorithm in the hydrological model calibration phase was mentioned. DYNWBM, a lumped model with five parameters, was selected as the hydrological model. The calibration and then validation period performances of the DEA based DYNWBM model were tested and also compared with other global optimization algorithms. According to the results derived from the study, hydrological model appropriately reflects the rainfall-runoff relation of basin for both periods.