CHINA FLOOD PROTECTION GATE FULL

For example, Deng et al. (2015)Īnalyzed the FPL of Taihu Lake levees to inform flood risk management. The existingįew studies of China's FPLs, to our best knowledge, are only about a specificįlood control facility and at local scales. Reliable flood risk assessment and challenges risk management. However, little information is available about China's FPLs, which hampers Increase social vulnerability in the countryside (Cheng et al., 2018). Li, 2017), which selectively leaves the vulnerable population behind and may Moreover, the urbanization process witnesses anĮnormous migration from the countryside to cities (Li et al., 2018 Liu and

CHINA FLOOD PROTECTION GATE FULL

Increased by 26 430 km 2, i.e., 542 %, from 1992 toĢ015, a process which is still in full swing and thus likely to exacerbateįlood risk in the future. For instance, Du et al. (2018) found that urban lands in the floodplain Longer-term, due to climate change (Alfieri et al., 2017 Winsemius et al.,Ģ018). Rapidly due to socioeconomic dynamics (Du et al., 2018) and, in the Of USD 34 billion per year (Du et al., 2019). Between 19, floods in China on averageĪffected 149 million people, led to 2165 deaths, and caused economic damage Therefore, FPL study is also a key to understand the integratedĬhina is one of the countries that experience the most serious floods and theįastest urbanization.

Local social vulnerability (Birkmann et al., 2016 Gu et al., 2018). The low FPLs may coincide with a concentration of vulnerable people, e.g., theĮlders and children, increasing the severity of the human consequences ofįloods (i.e., more likely fatalities), and more in general exacerbating the Human and financial resources and therefore imply a lower capacity of flood On the other hand, low FPLs generally mean limited Sense of security and lowering risk awareness, which boosts floodplainĭevelopment and population growth and can, in turn, cause catastrophicĬonsequences once a low-probability flood happens (Di Baldassarre et al.,Ģ015 Haer et al., 2020). However, high FPLs can have a “levee effect”: creating a From a cost–benefit view, high FPLs are moreĮconomically attractive in areas with a high density of population and economy High FPLs reduce the frequency of floods in flood-prone areas and decreaseįlood risk (Ward et al., 2013). Protection policy documents, in addition to FPL estimates based on flood risk Scussolini et al. (2016) developed FLOPROS (FLOod PROtection Standards), a global database ofįPLs based on information included in protection design documents and in Hallegatte et al. (2013) createdĪn FPL dataset for coastal cities by combining design information ofįlood defenses and expert estimates to improve coastal flood riskĪssessment. Jongman et al. (2014) estimated the FPLs in major European river basins byĪssuming that high-risk areas have high FPLs. Necessity of quantifying FPLs has increased in recent years. Risk assessment, which also depends critically on flood protection information With an increasing focus on large-scale flood Of flood risk, making its quantification a prerequisite to reliable riskĪssessment (Ward et al., 2013). Protected against flooding (Scussolini et al., 2016).

These results imply that to reduce social vulnerability andĭecrease potential casualties, investment in flood risk management shouldĪlso consider the demographic characteristics of the exposed population.įlood protection level (FPL) is the degree to which a flood-prone location is Share (52.3 %) of the exposed vulnerable population (children andĮlders), higher than their share (44.9 %) of the exposed

However,Ĭounties with low FPLs (return period of <50 years) host a disproportionate Majority (55.1 %) of the total exposed population. Relatively high FPLs (return period of ≥50 years) are seen inĢ82 or only 12.6 % of the evaluated 2237 counties, which host a

The FPLs are significantly higher than previously estimated in theįLOPROS (FLOod PROtection Standards) global dataset, suggesting that Chinese flood risk was probably The policy-based FPLs could be a valuable proxy for designed FPLs inĬhina. (90.1 %) it is very close to the designed FPLs. (53.2 %) of the 171 validation counties, and in 154 counties The new dataset corresponds to local flood protection designs in 91 National flood policies, this paper develops a dataset of likely FPLs forĬhina and investigates the protection granted to different demographic Based on the flood-protection prescriptions contained in the However, flood protection levels (FPLs) across theĬountry are mostly unknown, hampering the present assertive efforts on flood China is one of the most flood-prone countries, and development withinįloodplains is intensive.

China flood protection gate