Asia
Asia is home to a quarter of the world's population. As a region, it is particularly vulnerable to flooding. Variations in circulation, monsoon, and extreme weather events in an area with large floodplains, coastal areas and high population densities have seen catastrophic losses. Flooding in 2017 affected 43 million people, killing at least 1200. World Resources Institute estimate flooding to cost Asia $215 billion each year by 2030.
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Bangkok
Bangkok is now home to more than 10 million people. But as the capital keeps on growing, flooding in Thailand’s capital, impedes the development of the city and brings challenges to the well-being of its citizens.
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Bhopal
According to statistics, 12% of India's land is prone to floods. A UN global assessment report on disaster risk, released in 2015, says India's average annual economic loss due to floods is estimated to be more than $7 billion. Bhopal is one of three cities in India we’ve identified at high risk.
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Chennai
According to statistics, 12% of India's land is prone to floods. A UN global assessment report on disaster risk, released in 2015, says India's average annual economic loss due to floods is estimated to be more than $7 billion. Chennai is one of three cities in India we’ve identified at high risk.
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Ho Chi Minh City
Ho Chi Minh City ranks among the top 10 cities globally most likely to be severely affected by climate change. The average rainfall for the region is 1,800 millimetres, with ICEM predicting a sea level rise of 0.5cm/year by 2050 As the impact of climate change intensifies, Ho Chi Minh City's flooding problems are likely to get worse. A joint report by the Ministry of Agriculture and Rural Development and the World Bank estimated total damages to economy of 5000 billion VND in 2013.
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Kochi
According to statistics, 12% of India's land is prone to floods. A UN global assessment report on disaster risk, released in 2015, says India's average annual economic loss due to floods is estimated to be more than $7 billion. Kochi is one of three cities in India we’ve identified at high risk.
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Kuching
Kuching is situated in one of the most vulnerable regions for flood disaster, with average rainfall at almost 4 metres per year. A combination of natural conditions and rapid urbanisation is exacerbating flooding. Climate change compounds the problem and has resulted in extreme flood events becoming more frequent. With over 10 incidents exceeding 100-year return periods between 2003 and 2012. Flooding in 2007 resulted in economic losses of USD$605 million (MYR 2,400 million). More recently in February 2018 over 5,500 people were evacuated due to flooding.
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Lahore
The World Bank estimates Pakistan has suffered losses in excess of USD$18 billion (PKR 2,080 billion) because of natural disasters in the ten years between 2005 and 2015. Classified as a megacity, Lahore will see a flood extent in 2015 of 12.7 km2 expected to grow by over 400% to 51.7 km2 by 2060. Flooding in 2014 resulted in almost 300 deaths, approximately 100,000 homes damaged, and 2.47 million people directly affected due to inundation or displacement.
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Manila
Flooding in Manila in August 2016 almost brought the economy to a standstill. Financial markets closed, transportation suffered severe disruption and factories were closed. The Department of Agriculture estimates the damage to crops could be as high as USD$ 49.5 million (PHP2.6 billion). Home and car damage is expected to reach USD$ 57.1 million (PHP3 billion) worth of claims. National Disaster Risk Reduction and Management Council estimates that 1.7 million people were affected by the flooding.
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Palembang
The mostly low land city of Palembang is divided by the Musi River. Palembang has expanded rapidly especially since the year 2000. Average rainfall annually is 2.6 metres. During its wettest months, the city's lowlands are frequently inundated by torrential rains. The number of flooding events increased from 18 in 2007 to 46 in 2012, with an increase in inundation height and duration. With no sea level rise, Palembang mean annual losses are expected to run at US$418 million (IDR5,900,000 million). With a 20cm rise, this figure is expected to raise US$4,764 million (IDR 66,700,000 million).
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
Yangon
Both datasets contain fluvial and pluvial undefended data.
Standard data contains 3 layers for return periods of 20, 50 and 100 years.
Extended data contains 10 layers. Everything in standard data, and return periods for 5, 10, 75, 200, 250, 500, 1000 years.
