Sectoral climate services: Infrastructure

In light of these challenges, the application of EO data to identify climate change hot spots and to develop forecasting systems for extreme events can provide valuable evidence to decision-makers. It can help them to focus climate resilience and development efforts which protect vulnerable communities and their livelihoods, as well as the infrastructure (energy, water and transport) that supports socio-economic development. Climate change hot spots include semi-arid regions and deltas in Africa and Asia, and river catchments fed by glaciers and snowmelt in Central and South Asia, among others (De Souza et al, 2015).

EO data can be applied to identify hot spots and develop forecasting systems for a range of climate-driven hazards, including heat waves (especially in urban areas), flash floods, river floods, coastal flooding and erosion, soil erosion, landslides, mudflows, Glacial Lake Outburst Floods (GLOFS) and avalanches. Such systems have already been developed and applied in various geographies. The image on the top right demonstrates an output of such a hot spot analysis for Yemen, where flash floods and soil erosion significantly affect the livelihoods of smallholder farmers. The system was developed by a member of the Acclimatise team, Professor Rob Wilby (Wilby and Yu, 2013 a & b).

Input data

Forecasts and hot spots of flash flood risk can be produced using only public-domain datasets, which is highly useful in countries lacking robust in-situ datasets. The Yemeni example blended surface meteorological observations and soil survey data, remotely sensed (precipitation and vegetation) indices, topographic information, and geo-statistical techniques to produce hazard maps for flash flooding (and also soil erosion, water harvesting, and cropping potential). The input datasets were:

• Administrative and topographic information for Yemen, mapping the locations of governates, districts, major roads, cities and settlements (villages), provided by the Food and Agriculture Organization (FAO) and Ministry of Public Health and Population of Yemen.
• Land elevation: The Digital Elevation Model (DEM) at 30 m resolution was obtained from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM).
• Land cover: Global Land Cover (GLC) 2000 map from the Joint Research Centre (JRC) of the European Commission.
• Soil type obtained from the Digital Soil Map of the World (DSMW), a classification of soil units developed by the FAO
• Surface observations of meteorological data, namely precipitation and temperature
• Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis

The system in Yemen was used to produce a national atlas of flash flood risks (and other factors such as soil erosion potential). The resultant maps were used to identify hot spots of vulnerability – for instance, where flash flood risk coincides with settlements and the road network. The atlas was produced for present climate conditions and future scenarios.