Getting ahead of disaster risks with climate-smart technology

Getting ahead of disaster risks with climate-smart technology

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Climate-smart technology to enhance flood and drought resilience
disaster
Distribution of flood inundation duration with >0.5-m depth calculated by the RRI model in Mundeni Aru River Basin, Sri Lanka with Gauged-R data for the period: (a) from October 2011 to March 2012; (b) from October 2012 to March 2013; and (c) from October 2013 to March 2014

Extreme weather events, made more severe and frequent by climate change, are fast becoming the new normal worldwide. These disasters kill more people and damage more property today than terrorism.

According to EM-DAT – the Emergency Events Database of the Centre for Research on the Epidemiology of Disasters (CRED) – floods and droughts affect about 3 billion people each year. Poor communities are especially vulnerable because of their limited capacity to cope. This not only worsens social inequality but also places a massive financial burden on the state. The predicament is especially grave in South Asia, where an estimated 750 million people are exposed to various climate hazards, with floods posing the greatest threat, according to an IWMI Research Report.

To provide tools that help predict and plan for extreme weather, the International Water Management Institute (IWMI) and its partners have developed flood inundation models through a recently completed 3-year study in Sri Lanka. The models generate information that offers early warning of floods and can thus help reduce loss of life and property damage. Using the rainfall-runoff inundation (RRI) model in the country’s Mundeni Aru River Basin, a team of researchers led by Giriraj Amarnath (leader of IWMI’s Water Risks Research Group) calculated the depth and extent of flooding that could follow from heavy rainfall.

Climate-smart technology
Drought indices as part of the South Asia Drought Monitoring System (SADMS) for the Gujarat State, India.

Sri Lanka has seen a steady rise in the frequency of floods over the past two decades. From 2000 to 2013, about 25 megafloods affected more than five million people and caused damaged with an estimated value of more than USD 580 million. In the past 3 years, the southwest monsoon has brought floods, landslides and strong winds, resulting in a high death toll and extensive property damage. According to Sri Lanka’s national strategy for climate change adaptation, published by its Ministry of Environment and Renewable Energy, “droughts and unpredictable rainfall regimes already experienced in the Dry Zone are expected to become more prolonged and unpredictable.”

In addition to assessing flood potential, the models can help guide the design of new reservoirs with sufficient capacity to contain river water and runoff from heavy rains. This water can then be released for agriculture at times of water scarcity and drought. IWMI is piloting a similar technique in northern India that infiltrates excess water from irrigation canals into aquifers during the rainy season for use to irrigate crops in the dry season.

The RRI model overcomes a key limitation of the satellite images generally used for flood mapping, which are sometimes unavailable due to cloud cover or the satellite’s orbital period. Although the model is not new, this is the first time it has been used to analyze flood and water storage potential in South Asia. Funded by Japan’s Ministry of Agriculture, Forestry, and Fishery (MAFF), the study contributed to the CGIAR Research Program on Water, Land and Ecosystems (WLE), with support from CGIAR Fund donors.

The project also developed a procedure to evaluate the overall risk of water-related disasters. Using publicly available socio-economic indicators, researchers determined risk potential in 179 countries, providing information needed to devise index-based flood insurance schemes supported by CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). The Sendai Framework for Disaster Risk Reduction recognizes such insurance as an important means of managing the financial impact of disasters on governments and communities.

In addition, the project developed the larger scale Catchment-based Macro-scale Floodplain model (CaMa-Flood model) to assess flood hazards in South Asian countries with more extensive basin systems. Researchers tested this model in the basins of the Ganges and Godavari Rivers in India to determine its effectiveness for early flood warning. An experimental early flood warning system for the region will be launched in early 2019.

The project strengthened the capacity of decision-makers responsible for flood response in countries of South and Southeast Asia through knowledge and data sharing, and a web-based information system. A workshop held in Laos also contributed importantly to this end.

Under a new MAFF-supported project, “Drought Monitoring and Forecasting to Enhance Agriculture Resilience and Improve Food Security in South Asia,” IWMI researchers and partners will develop an innovative drought monitoring and forecasting system for the region. Building on recent advances, the system will support the development of strategies to enhance long-term drought resilience. The project team will work closely with national agencies to improve the coordination of national drought policies with community efforts to reduce the risks to crops and livestock.

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