How can a toolkit increase resilience to natural disasters in the Caribbean?

With funding from the Caribbean Development Bank, IMC is developing guidelines to help the 19 Caribbean countries to incorporate climate change adaptation into road network planning, construction, budgeting and decision-making strategies.

Monday 09 April 2018, Jonathan Essex

As hurricanes Irma and Maria have recently shown, the Caribbean is more and more vulnerable to natural hazards, which are heightened by the impacts of climate change. Suffice to say that 2017 was recorded as the most active season since 2005.

Only infrastructure that is resilient to natural disasters, including roads, can prevent climate change from jeopardising the investments these countries have made over the last few years. Historically, though, investment plans have not prioritised the resilience of existing roads, let alone their maintenance, which has resulted in both economic and human losses.

With funding from the Caribbean Development Bank, IMC is systematically analysing the region’s climate vulnerability and assessing risks to the transport sector in two countries, Guyana and Saint Lucia. In partnership with Acclimatise and Mona GeoInformatics Institute, we have developed a methodology and toolkit for identifying and prioritising investment to improve transport network resilience.

This will inform the guidelines that we are preparing to help the 19 Caribbean countries to incorporate climate change adaptation into road network planning, construction, budgeting and decision-making strategies.

The recommendations also aim to limit damage to existing transport infrastructure. This ranges from physical improvements in the most vulnerable locations, such as changing the design of drainage systems or increasing culvert sizes to reduce damage caused by flash floods, through to prioritisation of maintenance works before choosing to improve existing infrastructure.

Mapping the exposure of roads to climate-related shocks

We have built a prototype model in Saint Lucia, which we are testing, and will be further proven in Guyana. Our ultimate goal is to develop a toolkit and a wider approach which can be applied across all the 19 Caribbean countries by the project completion later this year.

To build the model, we mapped transport assets such as roads and bridges, and collected information on the natural hazards that could affect them. This considered both what has occurred in the past and what is anticipated in the future, including how disasters are impacted by climate change.

We have also mapped the importance of different roads, both economically and in terms of social vulnerability. This is vital, as research has shown that children, those with disability, women and the elderly are hit the hardest by disasters. Moreover, they are often less well equipped to cope with them.

These aspects, together with an evaluation of alternative routes, allows us to see, for example, which roads have a greatest socio-economic impact if they are damaged, so investments can be targeted to maximise resilience. For the first time, we are combining all this data into a central geospatial database.

Buildings damaged by Hurricane Irma in Sint Maarten on 7 September 2017. Photo courtesy of the Netherlands Ministry of Defense.
Buildings damaged by Hurricane Irma in Sint Maarten on 7 September 2017. Photo courtesy of the Netherlands Ministry of Defence.

We are developing the toolkit in a participatory way, including meetings with local communities, which allow them to share details about historic disaster events and help us to prioritise the major issues that affect them.

Six primary challenges

The scale of this assignment and its ambition has led us to address many challenges:

  1. A comprehensive approach. This is, to our knowledge, the first time that a systematic mapping of infrastructure, exposure and vulnerability is conducted. Rather than using a simplified analysis of susceptibility, we brought actual risk data together into a single platform. This allows us to build a more expert decision-making tool to target and prioritise investment.
  2. Link the global to the local. A significant amount of data is required at a local level if the model is to be useful. For example, exact culvert locations are required for the mapped tool to provide usable information. Similarly, to evaluate the importance of a road, we need to map population and census data, schools, hospitals, bus routes and emergency shelters. In contrast, climate data draws on and interpolates data from global scenarios and maps this to meteorological stations, often sparsely distributed.
  3. Not a crystal ball. Climate change predictions increase not just its risks but also its uncertainty as future climate depends on the extent to which we cut our emissions and how different aspects interact. As a result, critical projections, such as future rainfall and sea level rise, vary significantly, especially in the longer term. Even so, the likelihood of more extreme events can be estimated and the toolkit can help to make better decisions and secure future investments.
  4. Perfect is the enemy of good. Getting the data right could turn out to be too ambitious. Our aim has been to use existing data, avoiding either assumptions on the one hand, or the need for extensive remodelling on the other. In some cases, we decided it is better to simplify the approach so that we can work with the data already available in these countries. Accurate climatic data is based on complex (generally global or regional) climate modelling. This should be utilised, to the extent that it exists but cannot be substituted for. Similarly, if the actual condition of all 19,000 road culverts on Saint Lucia is not recorded by local engineers, it is not possible to use this approach to determine where maintenance works should be prioritised. This is also reflected in our approach to social vulnerability modelling which has first considered what data is recorded in the national census of each country.
  5. A good handshake. The focus of the toolkit is on achieving a good ‘handshake’ so that climate impact is better understood on the ground. The approach we adopted has brought together two distinct fields of data: that relating to physical infrastructure assets and that pertaining to climate-related hazard events and models. This will allow the toolkit to be used, as far as local capacity allows, to improve what happens locally.

Bearing these points in mind, the toolkit aims to be methodologically sound while practically useful to guide decisions around current and future investments. By balancing vulnerability of different infrastructure assets and transport routes with their social and economic importance, this approach should help Caribbean governments to prioritise investments with limited budgets and reduce the vulnerability of infrastructure and communities to climate change.

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