Although the change of floods in global scale is still hard to make a certain conclusion, the increasing trend of socioeconomic losses from floods is in high confidence (IPCC WGIIAR5-Chap3). The risk of floods seems to link with numerous factors such as the exposure of population and assets to flood-prone regions, the development of a certain area and the situation of public infrastructures. The flood itself and some influence factors are difficult to make quantitative measurement, however, losses from floods are more easily calculated in comparison with above items. Kundzewicz et al., 2013 indicates that natural disasters related with extreme weather contribute to increasing economic losses. Figure1 clearly shows the upward trends of total and insured losses from floods during 1980 to 2012.
Considering the contribution of population growth, IPCC SREX analyzes the average physical exposure to river flooding in 60°N~60°S regions with catchments larger than 1000 km2 (areas limited by models). From Figure2, we can find that Asia is the most severe suffering area and affected population of Asia is distinctly larger than other areas. However, Africa has the most rapid growth rate of influenced people, which grows nearly 3.28 times by 2030 than in 1970. Europe and North America have first and second lowest growth rates of average physical exposures among all these regions, whose growth rates are 0.13 and 0.86 respectively. Moreover, Europe and North America are the only two areas whose growth rates under 1. Developing regions seem to suffer more losses than developed regions.
Above are all in global scale, IPCC SREX has further study in regional scale, choosing Europe as the research object. Figure3 illustrates that Northern and Southern Central Europe have obvious increasing in both expected affected people and economic damage. However, not all areas in Europe have an upward trend of flood risk, some parts of North Europe expected to suffer less during 2071~2100 than before.
Models always have some limitations which lead to uncertainty of projection of exposed population towards floods. Hirabayashi et al., 2013 tried to use a number of models to make a projection and put all of them together to make a comparison. Although different models have different growth rates of flood exposure, all of them increase by 2100.
The ensemble means of the historical simulations (thick black line)
and the future simulations for each scenario (coloured thick lines).
Not only some certain regions, but also the globe seem to have much losses in the future. The flood may be hard to control, but we can take measures to reduce damage such as relocating people in severe flood-prone regions, improving monitoring and post-disaster reconstruction systems and raising public awareness. I believe the more we do, the less damage we would suffer.
This is really interesting - especially that the flood risk in Scandanavia is expected to decrease for 2071 - 2100. I wonder if this is to do with post-glacial isostatic rebound? Either still rebounding from the last ice age, or from further reductions in ice with current climate change. So these countries are relatively higher and less likely to suffer from flooding. Not sure if these models even include isostatic adjustment though : ). Are there any other suggestions for why flood risk could be decreasing in northern Europe?
ReplyDeleteHi, Breffni, I am really happy that you are interested in my blog and sorry for late reply. I am afraid that these models might not include isostatic adjustment. These models are general climate models widely used for climate change projection or weather forecast, either General Circulation Model (GCM) or Atmosphere-Ocean General Circulation Model (AOGCM). Although the climate scenarios (A2, B2) they chose focus on regional levels, but they are also generalized, that means not specialized enough in a certain region research. All these models have limitations.
DeleteThe idea you mentioned about post-glacial isostatic rebound is really interesting. I have no idea about it due to limited reading. I am quite glad if you can recommend any related article to me. The decreasing flood risk in northern Europe might be affected by warmer winters which leads to shorter snow seasons. It seems to decrease the strength of spring snowmelt which is one of reasons that would cause a flood.
Great post! Using the information on infrastructure damage is an interesting way to get a proxy measurement of flooding severity. I'm curious though, were varying insurance levels (percentage of property insured) and number of properties affected controlled for? These could be confounding factors when examining damage over time.
ReplyDeleteHi, Rob! I am very glad you like my post and sorry for late reply. I agree with you that there are lots of confounding factors that influence the flood damage losses. The loss data mentioned above in the article are normalized records which consider the need to control changeable exposure value and inherent vulnerability. However, it did not indicate what detailed considered elements contained in the data. After seeing your comments, I looked up references(http://journals.ametsoc.org/doi/pdf/10.1175/2010BAMS3092.1) of this article and found the data are often corrected for changes in insurance portfolios(number of policyholders) and in insurance states(cover and deductibles). Therefore, they may consider what you mentioned, although the data still might not be accurate due to the data over long time and different regions.
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