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The improvement of the macro-level accident situation in the Chinese construction industry is currently an urgent task for the government due to the high accident rate. This study intends to use improved principal component analysis to explore the accident situations in the Chinese construction industry from a multi-dimensional perspective, aiming at providing targeted direction on the improvement of the accident situation for the government. Six composite indicators that can quantify the accident situation are firstly selected based on a wide review of the literature and interviews with safety experts, with the original data collected from China institutions. The classical principal component analysis is then improved to examine the correlations between indicators, and further to evaluate accident situations in China provinces. Finally, the features of accident situations are explored and analyzed from a multi-dimensional perspective. The findings show that the improved principal component analysis can retain more dispersion degree information of the original data. Meanwhile, three principal components including the accident frequency, trend, and severity were extracted to quantify the accident situation, and a hierarchical indicator system for the comprehensive evaluation of the accident situation was constructed to deeper understand multi-dimensional characteristics of China’s accident situations. Furthermore, there exist great regional differences of accident situations in Chinese provinces. From the overall perspective, the accident situation shows a declining trend from the western backward region to the highly developed eastern coastal region. This study provides a multi-dimensional perspective for the government to formulate safety regulations and improve the accident situation.

Dams are vital for water resource utilization, and river diversion is key for dam construction safety. As sandy river basins are important exploitation areas that have special diversion features, the impact of sediment on the risk of river diversion during dam construction should be assessed. Diversion uncertainty is the origin of diversion risk, and sediment uncertainty changes the storage and discharge patterns of the diversion system. Two Gumbel-Hougaard (GH) copula functions are adopted to couple the random variables of flood and sediment, so that the sediment impacts on diversion storage and discharge can be obtained by the sampling of flood peaks. Based on variable coupling and sediment amendment, a method of Monte Carlo simulation (MCS) with a water balance calculation can quantitatively assess the risk of sandy river diversion, by evaluating the probability of upstream cofferdam overtopping. By introducing one diversion project on the Jing River in China with a clear water contrast, the risk values of dam construction diversion with or without sediment impacts can be obtained. Results show that the MCS method is feasible for diversion risk assessment; sediment has a negative impact on the risk of river diversion during dam construction, and this degradation effect is more evident for high-assurance diversion schemes.