No abstract

Under the background of global climate change and the rapid development of urbanization, the urban extreme precipitation events, urban rainstorm and flood disasters occur frequently, and flood disaster losses are serious.How to make decision support service is the key problem of emergency management of urban rainstorm and flood disasters. In consideration of the existing problems in the emergency management decision-making of urban rainstorm and flood disasters in China, this paper put forward the decision-making method of urban rainstorm and flood disasters emergency management based on similar cases analysis method. According to the evolution process of urban rainstorm and flood disasters, the attribute system of urban rainstorm and flood disasters was established. Entropy weight method was used to calculate the weights of problem attributes. The case-based reasoning method was used to calculate the similarities of problem attribute eigenvalues between the target case and the historical cases. According to the problem attribute weights and attribute similarities, the global similarity was determined. The case-based decision theory method was used to calculate the similarities between the target case and the historical cases. According to the comprehensive evaluation values of the alternative cases, the optimal alternative cases were determined. The methods proposed were further verified using typical urban rainstorm and flood disaster events in Xi'an city as an example. Results show that: the case-based reasoning method was used to obtain the highest similarity of historical case P3, the case-based decision theory method was used to obtain similar case set {P3, P4}. By comparing the calculation results of the case-based reasoning method and the case-based decision theory method, the case-based decision theory method is more suitable for the optimization of urban rainstorm and flood disaster emergency plans. The research results can provide scientific basis for emergency management of urban rainstorm and flood disasters.

The utilization of Regional Climate Methods (RCMs) to predict future regional climate is an important study under the changing environment. The primary objective of the paper is to correct the temperature and precipitation simulations for the period of 1980-2005 and 2026-2098 in the Wei River Basin (WRB), to evaluate the performance of RCMs for the period of 1980-2005, and further, to analyze the future changes of projected temperature and precipitation during 2026-2098. In this paper, the linear scaling method was used to correct the temperature simulations. Quantile mapping, local intensity scaling method and hybrid method were used to correct the precipitation simulations. The future changes of projected temperature and precipitation for the near-term (2026-2050), mid-term (2051-2075) and far-term , relative to the period of 1980-2005, were investigated under RCP 2.6 and RCP 8.5. Results indicate that:(1) The temperature biases were different spatial distributions, and the precipitation wet biases were detected in the WRB. After correction, HadGEM2-ES driven by RegCM4-4 had the best temperature reproducibility, and NCC-NorESM1-M driven by RegCM4-4 had the best precipitation reproducibility. (2) Under RCP 2.6, the projected annual, winter and spring temperature showed decreasing trends. The temperature was higher than that for the period of 1980-2005 except for the spring temperature decreases in the Beiluo River Basin. Under RCP 8.5, the temperature showed significantly increasing trends. The temperature for the near-term was similar to the period of 1980-2005, while the temperature increased significantly for the mid-term and far-term. (3) Under RCP 2.6, the precipitation had decreasing trends. Under RCP 8.5, precipitation trends were also spatially distributed. The relative deviation of winter precipitation was the largest. Relative to the period of 1980-2005, the light and moderate rain days showed little change for the period of 2026-2098, while the extreme rain days showed significantly increasing trends. (4) The results could be beneficial to the future climate projection, which provide references for the water resources management, the future hydrological process changes and attribution analysis in the WRB.