Japanese technology for flood forecast in South Asia

Japanese technology for flood forecast in South Asia
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Highlights

A sophisticated flood forecast model developed by Japanese scientists will enhance early warnings and help mitigate the impact of climate change in the flood-ravaged trans-boundary river basins of India, Pakistan and even China.

Thimphu: A sophisticated flood forecast model developed by Japanese scientists will enhance early warnings and help mitigate the impact of climate change in the flood-ravaged trans-boundary river basins of India, Pakistan and even China.

Rainfall and snowfall data from the three countries located in the Indus and Mekong river basins will be fed into a software simulated hydrological model that will also crunch in satellite data for accurate predictions, according to Toshio Koike, a collaborator from Japan, in the Asian Water Cycle Initiative (AWCI) project.
The AWCI, a part of Global Earth Observation System of Systems (GEOSS) consortium, includes 18 Asian nations and is directed at improving water resource management through better understanding of the water cycle and to tackle water-related disasters.
"So far, we have looked at non-transboundary rivers. In November, we will start the project on at least two transboundary rivers - the Indus and the Mekong. We (Japanese scientists) have developed a hydrological (water cycle-based) model for prediction. For the project, we need to share the rainfall data between the countries," Koike told IANS here at the just-concluded APN Second Science-Policy Dialogue, South Asia on 'Global Climate Change: Reducing Risk and Increasing Resilience' here.
The meet was organised by Asia-Pacific Network (APN) for Global Change Research in collaboration with the Bhutanese National Environment Commission.
It engaged more than 65 scientists and policymakers in South Asia, especially from Bhutan, Bangladesh, India, Nepal, Pakistan and Sri Lanka.
Discussing water security issues, Koike explained the functioning of the model with regard to the Indus, which originates in the icy Tibetan tableland and has nine tributaries - Beas, Chenab, Jhelum, Ravi, Sutlej, Gomal, Kabul, Swat and Kurram.
Its drainage basin stretches from Afghanistan through China, India, and Pakistan.
The scientist highlighted two problems in the Indus basin.
"One is the flood in the east part of the river, including (parts of) India and Punjab in Pakistan. The other concern is the upper Indus, where the snow and glacial melt is really critical in water resource management and flood control in Pakistan," explained Koike, director, International Centre for Water Hazard and Risk Management (ICHARM).
In fact, from 1950 to 2010, 21 major floods in Pakistan's Indus river basin killed 8,887 people, affected 109,822 villages and caused a cumulative direct economic loss of about $19 billion, according to a 2013 Asian Development Bank report.
"Floods are a major problem. Floods struck the country in 2011, 2012 as well," said Naseer Khan Kashani, Director General of Pakistan's Environmental Protection Agency.
The IPCC (Intergovernmental Panel on Climate Change) assessment report five (AR5) says that in South Asia, the frequency of heavy precipitation events is increasing, while light rain events are decreasing.
Also, as per the Working Group II of the IPCC AR5, floods and droughts are likely to increase in India.
In the light of such recent extreme events, Koike said, cooperation among nations in sharing data is necessary for developing a comprehensive warning system.
"Pakistan has already submitted a part of the upper Indus data and we have developed a very sophisticated glacial and snow melt distributive model. We will show the model's performance to India and China and also discuss what improvements can be expected," said the professor in Tokyo university's department of civil engineering..
"To increase the accuracy, we need to share the data in China, India and Pakistan. So we need the required information from other countries," Koike added.
The AWCI features the Water Cycle Integrator (WCI) as a means to combine observational data with data from numerical weather prediction models, geographical information and socio-economic data and then translate this data into usable information.
It has been applied to simulate and predict soil moisture, ground water, inundation, drought, snow and glacial melt, vegetation growth and even rice production in various Asian river basins.
IANS
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