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The development of the economy and technology has attracted greater attention to regional seismic resistance, a key technology for which is the simulation of regional seismic ground motions. This study proposes a simple and highly operable method for the generation of regional seismic ground motions, which includes five steps. First, a seismic ground motion recorded at a seismic station is selected as the original ground motion. The original ground motion is then decomposed into eight sub-signals by wavelet packet transform (WPT). Next, the eight sub-signals are adjusted by the frequency attenuation model. The generated ground motion is then amplitude modulated by the peak ground acceleration (PGA) attenuation model. The frequency attenuation model and the PGA attenuation model are obtained by fitting seismic data from the 1999 Chi-Chi earthquake. Finally, the propagation of the ground motion is considered. The proposed method can provide a time history of seismic ground motions for any point in a region. To investigate the rationality and applicability of the proposed method, the characteristics of the generated seismic ground motions are compared with those of true seismic ground motions. The average error of the PGA of the generated ground motions and the true ground motions is 0.072g; thus, the proposed method is suitable for use in small-scale regions. Furthermore, 4-story and 15-story structures are used for structural response analysis. The story drift ratio error between the generated ground and true ground motions is found to be within an acceptable error range. The proposed method provides a new way to generate ground motions for regional seismic investigation. [ABSTRACT FROM AUTHOR]

The earthquake early warning (EEW) system is critical in mitigating the effects of seismic hazards by providing valuable response time. Damage to buildings can be determined based on peak ground acceleration (PGA). If PGA can be predicted in advance, the seismic risk of a building can be estimated. A novel method for predicting PGA using wavelet packet transform (WPT) and convolutional neural networks (CNN) is proposed. Early arrival waves generated by earthquakes are decomposed using WPT to produce a matrix of wavelet coefficients. This matrix serves as the input to the CNN model to predict the PGA. To achieve the best prediction performance, different setups were investigated, including the use of Daubechies Wavelet 4 (db4) and four-level decomposition. The results indicate that this configuration yields better prediction accuracy. P-waves of three-second duration are commonly used for EEW. Compared to the prediction results of a CNN model used to validate the method, the proposed method has a lower average error and better use of early arrival waves with shorter duration. Overall, the proposed method demonstrates the potential of WPT and CNN in EEW systems. The proposed approach can utilize shorter early arrival waves to predict PGA and gain more reaction time to get rid of seismic hazards. To estimate structural damage using the predicted PGA under an impending earthquake, a method is proposed to quickly determine structural damage based on the predicted PGA and fragility curves. It provides a method to estimate the potential structural damage caused by an impending earthquake. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of the hydrochemical evolution and spatial patterns of shallow groundwater systems is essential for water resource management and wetland ecological restoration. The Baiyangdian Wetland is one of the most concerning areas because of the development of the Xiong'an New Area. The spatial characteristics of groundwater hydrochemistry and potential controlling factors associated with hydrochemical evolution remain unclear. In this study, hydrogeochemistry together with the hierarchical cluster analysis were used to elucidate the hydrochemical processes and hydrological zoning patterns of shallow groundwater systems in the Baiyangdian Wetland, North China Plain. The results showed that hydrochemical compositions of shallow groundwater had considerable spatial variations, which was closely related to the inflow rivers hydrochemistry and the dynamics of groundwater–surface water interactions. A significant increase in SO42− concentration occurring at the cone of the depression was related to extensive pumping caused by anthropogenic activities. Anthropogenic activities were also a major factor controlling the spatial distribution patterns of shallow groundwater hydrochemistry. Ca2+, Mg2+, and SO42− in the wetland and shallow groundwater were primarily derived from carbonate and gypsum dissolution, while Na+ and Cl− originated from halite and silicate dissolution. Rock weathering predominated the geochemical evolution of shallow groundwater in conjunction with carbonate precipitation and cation exchange. The hydrochemistry of the shallow groundwater system presented distinct spatial zonation patterns that were classified into four clusters corresponding to seven subzones. In Zones I–IV, water‐rock interaction was the dominant factor controlling shallow groundwater chemistry, which was driven by the positive groundwater–surface water exchange. The coupled effects of anthropogenic activities and river infiltration and mixing caused the high levels of dissolved components in Zones V–VII. This study contributes to have a better understanding of the water cycle and hydraulic connections among different bodies, and will benefit the rational evaluation of hydrochemical evolution and wetland ecological restoration in the Baiyangdian Wetland. [ABSTRACT FROM AUTHOR]