Vulnerability

China faces significant disaster risk levels, ranked 67 out of 191 countries by the 2019 Inform Risk Index. This ranking is driven strongly by the exposure component of risk. China has very high exposure to flooding (ranked jointly 13th), including, riverine, flash, and coastal, and very high exposure to tropical cyclones and their associated hazards (ranked 6th). Drought exposure is proportionately lower, but still significant (ranked jointly 55th). Disaster risk in China is also elevated by its moderate levels of social vulnerability. China’s net risk score is significantly offset by its strong coping capacity.

This section provides a summary of key natural hazards and their associated socioeconomic impacts in a given country. And it allows quick evaluation of most vulnerable areas through the spatial comparison of natural hazard data with development data, thereby identifying exposed livelihoods and natural systems.

Natural Hazard Statistics

The charts provide overview of the most frequent natural disaster in a given country and understand the impacts of those disasters on human populations.

Metadata

Climate change is now recognized to have a significant impact on disaster management efforts and pose a significant threat to the efforts to meet the growing needs of the most vulnerable populations. The demands of disaster risk management are such that concise, clear, and reliable information is crucial. The information presented here offers insight into the frequency, impact and occurrence of natural hazards.

Natural Hazard / Development Nexus

Understanding natural hazard occurrence as well as historical climate conditions, in relation to development contexts, is critical to understanding a country’s historical vulnerability. This tool allows the visualization of different natural hazards or historical climate conditions with socio-economic and development datasets. Select the Development Context and either a Natural Hazard or Climate Condition and overlay horizontally by sliding the toggle left or right to gain a broader sense of historically vulnerable areas.


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Data presented under Historical Climate Conditions are reanalysis products derived from ERA5-Land data. ERA5-Land is a global land-surface dataset at 9 km resolution, consistent with atmospheric data from the ERA5 reanalysis from 1950 onward. Climate reanalyses combine past observations with models to generate consistent time series of multiple climate variables. They provide a comprehensive description of the observed climate as it has evolved during recent decades, on 3D grids at sub-daily intervals. 

This data has been collected, aggregated and processed by the Climate Resilience Cluster of the European Space Agency’s (ESA) Earth Observation for Sustainable Development (EO4SD) initiative.

Key Vulnerabilities
  • China is regularly among the top three nations most affected by disasters every year, in terms of disaster frequency, lives lost, and economic damages. According to CRED (2017), in 2016 72 million people were affected, 1,335 lives were lost and $45 billion in economic damages were caused.
  • Major floods can affect several millions of people in China. Over 50 million people were affected by single events in 2007, 2010, 2011, and 2016. UNISDR (2014) estimate the average annual loss from floods at $18 billion, with major implications for agricultural production and hence food security.
  • Droughts affect a significant part of the population in China, with on average one major drought affected area and 25 million people affected per year.
  • China faces a significant increase in the population exposed to fluvial flooding, with an additional 27-35 million people affected every year by 2035-2044 as a result of climate change (assuming a constant population). This represents more than a doubling of the 1971-2004 median estimate of the exposed population, which stood at 24 million.
  • Changes in the probability of extreme drought are most significant in the northern and western regions of China, which are also projected to experience greater general warming. |Agricultural losses to drought have been increasing in recent decades, with rates of loss to drought highest in north and northeastern China, reaching 14-18% of yield in some provinces. This trend may continue as the probability of drought is projected to increase to around 20-36% depending on the emissions pathway.
  • An increase in the frequency and intensity of heatwaves has been documented in recent decades. This trend is expected to continue, with median annual heatwave probability reaching 5-22% by 2080-2099 depending on emissions pathway. A particularly serious future heat wave threat has been projected in the area of the North China Plain, where climate change is expected to interact with local irrigation practices to result in heatwaves which will present a risk to life for laborers working outdoors.
  • The increasing risk presented by natural hazards, characterized by diverse hazards and cross-sectoral impacts across large geographies challenges China’s governance structures around DRM. Capacity building in institutions to allow integration, community participation and balancing of cross-sectoral needs, including for ecosystems, is urgently required.
  • The Asian Development Bank reviewed China’s DRM context in 2015 a key finding of the review was to identify a lack of integration between laws and policies covering different aspects of disaster risk management and different disaster types. This has led to wasted resources and redundant infrastructure.
  • The risk that climate change will exacerbate the frequency and intensity of extreme events in China demands a transition from a reactive approach to management to risk reduction through better physical and organizational planning.
  • Water resources are integral to China’s economy and public well-being, due to high water dependence of both the agricultural and manufacturing industries. Key recommendations for reducing disaster risk include a transition to integrated river basin planning and wider participation in planning and intervention design.