Rapid Population Growth in Chinese Floodplains from 1990 to 2015

Fang, Yongqiang; Du, Shiqiang; Scussolini, Paolo; Wen, Jiahong; He, Chunyang; Huang, Qingxu; Gao, Jun

doi:10.3390/ijerph15081602

Cited by 27 publications

(24 citation statements)

References 40 publications

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“…The results derived from the above analyses align with the findings in previous studies. Fang et al (2018) reported that China's population living in floodplains increased at an annual rate of 1.3% from 1990 to 2015, which was faster than in other regions of the country. Our analyses also yield a similar annual growth rate of approximately 1.2% in the flood hazard areas from 1995 to 2015 (Table 2).…”

Section: Discussionmentioning

confidence: 99%

“…Sajjad et al (2018) predicted that the number of people exposed will double in China's coastal areas that are under current sea level rise by 2100, reaching a total of 10 million. Fang et al (2018) and Du et al (2018) conducted research to investigate the changes of population and built-up land in China's flood-prone areas. Miao et al (2018) identified the provinces south of the Yellow River as the regions with relatively higher population vulnerability to landslides.…”

Section: Introductionmentioning

confidence: 99%

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Changes of Population, Built-up Land, and Cropland Exposure to Natural Hazards in China from 1995 to 2015

Chen

Xie

2019

Int J Disaster Risk Sci

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By using the latest China population grid and land-use data, we assess the changing exposure of China's population and land uses to the hazards of storm surges, droughts, earthquakes, floods, and landslides from 1995 to 2015. We found that the single-hazard areas and the multihazard areas covered 43% and 26% of China's territory, respectively. Population grew faster in the hazard-prone areas than in the non-hazard areas. Built-up area expanded more rapidly in the areas prone to earthquakes and landslides. Cropland changed rapidly in many hazard-prone areas. The hazard-prone areas affected by floods featured the highest cropland loss rates, while the areas prone to earthquakes and landslides featured the highest cropland growth rates. We detected areas with significant exposure changes by using hot spot analysis. It was found that population and built-up land in the Pearl River Basin were increasingly exposed to storm surges, floods, and landslides. The Haihe River Basin and Huaihe River Basin also showed a consistent increase of population and built-up land exposure to droughts and earthquakes. These findings can provide a foundation for the design and implementation of protection and adaptation strategies to improve the resilience of Chinese society to natural hazards. Keywords China Á Exposure to natural hazards Á Population change Á Built-up land Á Cropland & Xiaocong Xu

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Changes of Population, Built-up Land, and Cropland Exposure to Natural Hazards in China from 1995 to 2015

Chen

Xie

2019

Int J Disaster Risk Sci

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“…However, efforts to restore and protect open water, such as lakes and ponds, deteriorated over time (Cheng and Li, 2015), and by 2015 there are still 406 polders in the main channels of Yangtze River and 133 polders in the Dongting-and Poyang lake regions, with a total population of 1.9 million (Ministry of Water Resources, 2015). Nationwide, the population living in floodplains increased by 1.1% per year over the period 1990-2015, which is much faster than the population increase outside floodplains (0.4% per year) (Fang et al, 2018).…”

Section: China's Response To the 1998 Floodmentioning

confidence: 92%

“…Flood management in China, and in particular in urban areas, could be better prepared for these trends. Urbanization in Chinese floodplains continues to increase, for example at rate of 20,600 km 2 /year over the period 1998 and 2015 (Du et al, 2018), and by 2050, it is expected that 80.0% of China's total population will live in cities, rising from 55.5% in 2015 (Population Division of United Nations, 2018)with an additional of 172.8 million people in floodplains (Fang et al, 2018). These numbers will probably be even higher due to the ending of the 'one-child' policy.…”

Section: Future Challenges To Flood Management In Chinamentioning

confidence: 99%

Brief communication: Rethinking the 1998 China flood to prepare for a nonstationary future

Du¹,

Cheng²,

Huang³

et al. 2019

Preprint

Self Cite

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Abstract. A mega-flood in 1998 caused tremendous losses in China, and triggered large investments in flood risk management (Bryan et al., 2018). However, rapid urbanization and climate change pose new challenges and it is time to rethink whether China is prepared for the next mega-flood. In China’s fast growing economy, with rapid urbanization, novel flood risk management approaches are required in addition to reinforcing structural protection, such as levees. These include a risk-based urban planning and a coordinated water governance system with public participation.

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“…Exposure can be defined as the depreciated or replacement value of the tangible physical assets in hazard-prone areas [3,4]. Flood risk under climate change and socioeconomic change is a great challenge for flood risk management [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China

Wang

et al. 2019

Sustainability

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Exposure is an integral part of any natural disaster risk assessment, and damage to buildings is one of the most important consequence of flood disasters. As such, estimates of the building stock and the values at risk can assist in flood risk management, including determining the damage extent and severity. Unfortunately, little information about building asset value, and especially its spatial distributions, is readily available in most countries. This is certainly true in China, given that the statistical data on building floor area (BFA) is collected by administrative entities (i.e. census level). To bridge the gap between census-level BFA data and geo-coded building asset value data, this article introduces a method for building asset value mapping, using Shanghai as an example. This method consists of a census-level BFA disaggregation (downscaling) by means of a building footprint map extracted from high-resolution remote sensing data, combined with LandScan population density grid data and a financial appraisal of building asset values. Validation with statistical data and field survey data confirms that the method can produce good results, but largely constrained by the resolution of the population density grid used. However, compared with other models with no disaggregation in flood exposure assessment that involves Shanghai, the building asset value mapping method used in this study has a comparative advantage, and it will provide a quick way to produce a building asset value map for regional flood risk assessments. We argue that a sound flood risk assessment should be based on a high-resolution-individual building-based-building asset value map because of the high spatial heterogeneity of flood hazards.Röthlisberger and colleagues [13] compared five building value models for flood risk analysis, and proposed that estimating exposed-building values should be based on individual buildings rather than on areas of land-use types. Higher quality exposure data is needed to perform validations of flood risk models [14].However, for flood risk analysis, quite often a spatial mismatch exists between hazard intensity data (e.g., inundation depth), which are frequently modelled on a high-resolution raster level, and exposure data, which are usually only available at coarse census units (e.g., counties) or aggregated land-use/land cover classes [14][15][16][17]. Flood risk assessments often invest much more in hazard modelling of water depths or inundation areas at a spatially explicit raster level [18,19], while only a limited number of studies have explicitly focused on the estimations of assets and their disaggregation to overcome the spatial mismatch between the quality of hazard and exposure data [20][21][22][23]. Meanwhile, the quality of the exposure data is one of the most important uncertainties in flood risk assessments [24][25][26][27]. Because of the high spatial resolution of water inundation depth estimation, which is mainly a function of topography [28,29], flood risk assessments are much more sensi...

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Rapid Population Growth in Chinese Floodplains from 1990 to 2015

Cited by 27 publications

References 40 publications

Changes of Population, Built-up Land, and Cropland Exposure to Natural Hazards in China from 1995 to 2015

Changes of Population, Built-up Land, and Cropland Exposure to Natural Hazards in China from 1995 to 2015

Brief communication: Rethinking the 1998 China flood to prepare for a nonstationary future

Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China

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