Developing a regional damage function to quickly estimate direct economic losses(DELs) caused by heavy rain and floods is crucial for providing scientific supports in effective disaster response and risk reduction. Th...Developing a regional damage function to quickly estimate direct economic losses(DELs) caused by heavy rain and floods is crucial for providing scientific supports in effective disaster response and risk reduction. This study investigated the factors that influence regional rainfall-induced damage and developed a calibrated regional rainfall damage function(RDF) using data from the 2016 extreme rainfall event in Hebei Province, China. The analysis revealed that total precipitation, asset value exposure, per capita GDP, and historical geological disaster density at both the township and county levels significantly affect regional rainfall-induced damage. The coefficients of the calibrated RDF indicate that doubling the values of these factors leads to varying increases or decreases in rainfall-induced damage. Furthermore, the study demonstrated a spatial scale dependency in the coefficients of the RDF, with increased elasticity values for asset value exposure and per capita GDP at the county level compared to the township level. The findings emphasize the challenges of applying RDFs across multiple scales and highlight the importance of considering socioeconomic factors in assessing rainfall-induced damage. Despite the limitations and uncertainties of the RDF developed, this study contributes to our understanding of the relationship between physical and socioeconomic factors and rainfall-induced damage. Future research should prioritize enhancing exposure estimation and calibrating RDFs for various types of rainfall-induced disasters to improve model accuracy and performance.The study also acknowledges the variation in RDF performance across different physical environments, especially concerning geological disasters and slope stability.展开更多
Loss normalization is the prerequisite for understanding the effects of socioeconomic development,vulnerability, and climate changes on the economic losses from tropical cyclones. In China, limited studies have been d...Loss normalization is the prerequisite for understanding the effects of socioeconomic development,vulnerability, and climate changes on the economic losses from tropical cyclones. In China, limited studies have been done on loss normalization methods of damages caused by tropical cyclones, and most of them have adopted an administrative division-based approach to define the exposure levels. In this study, a hazard footprint-based normalization method was proposed to improve the spatial resolution of affected areas and the associated exposures to influential tropical cyclones in China. The meteorological records of precipitation and near-surface wind speed were used to identify the hazard footprint of each influential tropical cyclone. Provincial-level and national-level(total)economic loss normalization(PLN and TLN) were carried out based on the respective hazard footprints, covering loss records between 1999–2015 and 1983–2015, respectively.Socioeconomic factors—inflation, population, and wealth(GDP per capita)—were used to normalize the losses. A significant increasing trend was found in inflation-adjusted losses during 1983–2015, while no significant trend was found after normalization with the TLN method. The proposed hazard footprint-based method contributes to amore realistic estimation of the population and wealth affected by the influential tropical cyclones for the original year and the present scenario.展开更多
Tropical cyclone,a high energy destructive meteorological system with heavy rainfall and gale triggered massive landslides and windstorms,poses a significant threat to coastal areas.In this paper we have developed a T...Tropical cyclone,a high energy destructive meteorological system with heavy rainfall and gale triggered massive landslides and windstorms,poses a significant threat to coastal areas.In this paper we have developed a Tropical Cyclone Potential Impact Index （TCPI） based on the air mass trajectories,disaster information,intensity,duration,and frequency of tropical cyclones.We analyzed the spatial pattern and interannual variation of the TCPI over the period 1949-2009,and taking the Super Typhoon Saomai as an example have examined the relationship between the TCPI and direct economic losses,total rainfall,and maximum wind speed.The results reveal that China＇s TCPI appears to be a weak decreasing trend over the period,which is not significant overall,but significant in some periods.Over the past 20 years,the TCPI decreased in the southern China coastal provinces of Hainan,Guangdong and Guangxi,while it increased in the southeastern coastal provinces of Zhejiang,Fujian and Taiwan.The highest values of TCPI are mainly observed in Taiwan,Hainan,the coastal areas of Guangdong and Fujian and Zhejiang＇s southern coast.The TCPI has a good correlation （P=0.01） with direct economic loss,rainfall,and maximum wind speed.展开更多
基金funded by the National Key R&D Program of China(Grant No.2022YFC3004404)the Key Research and Development Project of Science and Technology Department of Hebei Province(No.21375410D and No.22375421D).
文摘Developing a regional damage function to quickly estimate direct economic losses(DELs) caused by heavy rain and floods is crucial for providing scientific supports in effective disaster response and risk reduction. This study investigated the factors that influence regional rainfall-induced damage and developed a calibrated regional rainfall damage function(RDF) using data from the 2016 extreme rainfall event in Hebei Province, China. The analysis revealed that total precipitation, asset value exposure, per capita GDP, and historical geological disaster density at both the township and county levels significantly affect regional rainfall-induced damage. The coefficients of the calibrated RDF indicate that doubling the values of these factors leads to varying increases or decreases in rainfall-induced damage. Furthermore, the study demonstrated a spatial scale dependency in the coefficients of the RDF, with increased elasticity values for asset value exposure and per capita GDP at the county level compared to the township level. The findings emphasize the challenges of applying RDFs across multiple scales and highlight the importance of considering socioeconomic factors in assessing rainfall-induced damage. Despite the limitations and uncertainties of the RDF developed, this study contributes to our understanding of the relationship between physical and socioeconomic factors and rainfall-induced damage. Future research should prioritize enhancing exposure estimation and calibrating RDFs for various types of rainfall-induced disasters to improve model accuracy and performance.The study also acknowledges the variation in RDF performance across different physical environments, especially concerning geological disasters and slope stability.
基金supported by the National Basic Research Program of China(Grant No.2015CB452806)the National Natural Science Foundation of China(Grant No.41701103)
文摘Loss normalization is the prerequisite for understanding the effects of socioeconomic development,vulnerability, and climate changes on the economic losses from tropical cyclones. In China, limited studies have been done on loss normalization methods of damages caused by tropical cyclones, and most of them have adopted an administrative division-based approach to define the exposure levels. In this study, a hazard footprint-based normalization method was proposed to improve the spatial resolution of affected areas and the associated exposures to influential tropical cyclones in China. The meteorological records of precipitation and near-surface wind speed were used to identify the hazard footprint of each influential tropical cyclone. Provincial-level and national-level(total)economic loss normalization(PLN and TLN) were carried out based on the respective hazard footprints, covering loss records between 1999–2015 and 1983–2015, respectively.Socioeconomic factors—inflation, population, and wealth(GDP per capita)—were used to normalize the losses. A significant increasing trend was found in inflation-adjusted losses during 1983–2015, while no significant trend was found after normalization with the TLN method. The proposed hazard footprint-based method contributes to amore realistic estimation of the population and wealth affected by the influential tropical cyclones for the original year and the present scenario.
基金National Science & Technology Pillar Program during the 11th Five-Year Plan Period,No.2007BAC29B05No.2008BAK50B02
文摘Tropical cyclone,a high energy destructive meteorological system with heavy rainfall and gale triggered massive landslides and windstorms,poses a significant threat to coastal areas.In this paper we have developed a Tropical Cyclone Potential Impact Index （TCPI） based on the air mass trajectories,disaster information,intensity,duration,and frequency of tropical cyclones.We analyzed the spatial pattern and interannual variation of the TCPI over the period 1949-2009,and taking the Super Typhoon Saomai as an example have examined the relationship between the TCPI and direct economic losses,total rainfall,and maximum wind speed.The results reveal that China＇s TCPI appears to be a weak decreasing trend over the period,which is not significant overall,but significant in some periods.Over the past 20 years,the TCPI decreased in the southern China coastal provinces of Hainan,Guangdong and Guangxi,while it increased in the southeastern coastal provinces of Zhejiang,Fujian and Taiwan.The highest values of TCPI are mainly observed in Taiwan,Hainan,the coastal areas of Guangdong and Fujian and Zhejiang＇s southern coast.The TCPI has a good correlation （P=0.01） with direct economic loss,rainfall,and maximum wind speed.
