Abstract: Less attention was paid to the extremely heavy rainfall disaster chain in semiarid regions in the previous researches. Under climate change, the frequency and intensity of extremely heavy rainfall in semiarid areas in China was in an obvious increase trend in recent decades. It is important to develop a methodology of rapid assessment of damage and loss (RADL) in an extremely heavy rainfall so as to enhance the capability of preventing the disasters in semiarid areas. In this paper, a method was developed to assess the damage and loss in an extremely heavy rainfall disaster chain, especially in flash flood and debris flow disaster chains based on multisource data and information, including the realtime precipitation, inundated area derived from remote sensing image interpretation results, social and economic information of the study area, etc. Three points should be emphasized in the framework of this method: ① The assessment unit of the RADL was the combination of watershed unit and GRID unit, in which the watershed unit included the secondlevel watersheds in the study area, and the spatial resolution of GRID unit was decided by the social and economic information (e.g. population density); ② The home vulnerability curve was an important factor to implement the RADL. In this paper, a home vulnerability matrix was established based on the realtime filed survey of disaster information collectors at village scale due to the lack of vulnerability curve at that time; ③ From the perspective of final damage and loss in the extremely heavy rainfall disaster chain (including flash flood and debris flow), the method was a comprehensive framework to implement the RADL. The study results could provide a scientific basis for the establishment of rapid assessment system of physical damage and loss induced by flood and debris flow disasters.

Key words: font-size: 10.5pt, mso-bidi-font-family: 宋体, mso-font-kerning: 1.0pt, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, extremely heavy rainfall')">mso-bidi-language: AR-SA" lang="EN-US">extremely heavy rainfall, flash flood, disaster chain, rapid assessment, semiarid region, Minxian County