Practical Action: Digital resilience for vulnerable communities

Bangladesh’s low-lying delta landscape and dependence on major river systems make it one of the countries most exposed to climate hazards. Floods, cyclones, salinity intrusion, tidal surges and river erosion regularly affect vulnerable districts such as Faridpur, Feni, Khulna and Satkhira. While significant progress has been made in reducing disaster-related mortality, the underlying systems that support preparedness and response remain under strain.

Local communities often lack access to timely, impact-based and location-specific forecasts. Early warning systems are not yet sufficiently fast, inclusive or actionable, and local Disaster Management Committees face persistent capacity gaps. At the same time, households have limited access to financial tools that would enable them to act early or recover quickly after a shock. As a result, recurring and largely predictable climate events continue to cause avoidable losses, pushing families into cycles of debt, asset depletion and long-term livelihood insecurity. Without risk-informed institutional planning, stronger forecasting, governance and financial protection mechanisms, climate-exposed regions risk increasing damage and slowed socio-economic development.

Practical Action implements an integrated, community-centred approach to strengthen climate resilience in vulnerable districts. The project combines improved risk awareness, advanced forecasting technologies and innovative financial solutions.

It enhances local decision-making by generating high-quality climate risk data and translating it into risk maps, action plans and strengthened disaster governance structures. At the same time, AI- and machine learning-enabled forecasting models are upgraded to deliver hyper-local, impact-based forecasts. A multi-channel early warning system ensures rapid and inclusive dissemination, enabling timely anticipatory actions.

In parallel, the project pilots innovative disaster risk financing mechanisms through a dedicated subnational fund. Instruments such as parametric insurance, blended finance and anticipatory cash transfers support preparedness and recovery while strengthening community ownership and financial resilience.

By 2029, the project will strengthen the capacity of 20 local governments to use climate and risk data for informed decision-making and improved disaster preparedness. Through participatory risk mapping, local action planning and stronger disaster governance, communities will be better equipped to protect lives and livelihoods.

Using AI- and machine learning-enabled forecasting systems, the initiative will deliver hyper-local, impact-based cyclone and flood forecasts that support timely anticipatory action for 142,583 households (over 588,000 people). The project aims to improve early warning dissemination, reduce disaster losses and build stronger climate and financial resilience for vulnerable communities.

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