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This study investigates spatial cross-correlation models for two sets of vector intensity measures (IMs) considering the influence of regional site conditions. The first set of the vector IM consists of the peak ground acceleration, Arias intensity, and the peak ground velocity; the second set is for spectral accelerations at multiple periods. Geostatistics analyses are performed using 2686 strong-motion data from 11 recent earthquakes that occurred in California, Japan, Taiwan, and Mexico. The results indicate that the spatial cross correlations of the vector IMs are strongly influenced by the spatial distribution of regional site conditions, which can be quantified using RVS30, the correlation range of shear-wave velocity in the top 30 m. The linear model of coregionalization is proposed to construct a permissible spatial correlation model, and the short-range and long-range coregionalization matrices is specified to vary linearly with RVS30. The proposed model demonstrated excellent performance in quantifying the influence of regional site conditions on the spatial cross correlations for the vector IMs, meanwhile the model guarantees a positive-definite covariance matrix for any reasonable value of RVS30, a mathematical condition required for stochastic generation of the spatially correlated random fields. The spatial cross-correlation models proposed in this study can be conveniently used in regional-specific seismic risk analysis and loss estimation of spatially distributed infrastructure using vector IMs. [ABSTRACT FROM AUTHOR]

Dams have major impacts on river hydrology with a general tendency to decrease annual maximum flows and increase annual minimum flows. The analysis of 41 streamflow series in California, USA are examined, and the results show that, as expected, the mean values and variations of annual peak flows and maximum flows of different durations are reduced for almost all sites after dam use, and the larger the ratio of total reservoir capacity to pre-dam annual runoff, the larger the rate of peak flow reduction. However, the impacts on minimum flow are mixed. For five out of seven cases with long data records for periods before and after dam use, the average annual minimum flow as well as its variation increased, but for the other two cases, they decreased. No significant changes are detected for various extreme precipitation indices; therefore, dam construction is believed to be the major reason for flow regime changes. The probability distribution of extreme flows also changed, due to the impacts of dams. The Log-Pearson Type III (LP3) distribution is best for peak flow series and one-day maximum series at sites with or without the impact of dams; the three-parameter Weibull (W3) distribution is the best model for the seven-day minimum flow at sites with no or minor dam impacts, whereas at sites with major dam impacts, the best model is the generalized extreme value (GEV) model for the seven-day minimum flow. [ABSTRACT FROM AUTHOR]