Intensifying river floods could lead to regional production losses worldwide caused by global warming. This might not only hamper local economies around the globe – the effects might also propagate through the global network of trade and supply chains, a study now published in Nature Climate Change shows. It is the first to assess this effect for flooding on a global scale, using a newly developed dynamic economic model. It finds that economic flood damages in China, which could, without further adaption, increase by 80 percent within the next 20 years, might also affect EU and US industries. The US economy might be specifically vulnerable due to its unbalanced trade relation with China. Contrary to US president Trump’s current tariff sanctions, the study suggests that building stronger and thus more balanced trade relations might be a useful strategy to mitigate economic losses caused by intensifying weather extremes.
“Climate change will increase flood risks already in the next two decades – and this is not only a problem for millions of people but also for economies worldwide,” says Anders Levermann, project leader from the Potsdam Institute for Climate Impact Research (PIK) in Germany and the Lamont Doherty Earth Observatory, Columbia University in New York.
Without further adaption measures, climate change will likely increase economic losses worldwide due to fluvial floods by more than 15 percent accumulating to a total of about 600 billion US dollar within the next 20 years. While the bulk of this is independent of climate change, the rise is not. “Not only local industries will be affected by these climate impacts,” says Sven Willner, lead author of the study from PIK. “Through supply shortages, changes in demand and associated price signals, economic losses might be down-streamed along the global trade and supply network affecting other economies on a global scale – we were surprised about the size of this rather worrying effect.”
Read more at Potsdam Institute for Climate Impact Research (PIK)
Photo credit: Huangdan2060 via Wikimedia Commons
