Development of Data-Driven Multi-Hazard Early Warning Systems (MHEWS)

Project Summary:

The objective of this multi-year programmatic ASA (PASA) is to help countries achieve a digital transformation that is green, resilient, inclusive, and data-driven by capitalizing on digital opportunities (enablers) while managing risks (safeguards). The objective will be achieved through two delivery mechanisms that will leverage the Korean partnerships and expertise:

• Relevant Knowledge including analytical research; events and conferences for exchange and policy dialogue; and capacity development
• Operations Support through know-how including advisory service; country diagnostics; technical assistance; and project engagements

The objective of this program is to help developing countries maximize the benefits of MHEWS through a data-driven approach that puts focus on the utilization of data from various available sources rather than exclusively relying on high-quality but limited data from existing EWS systems. Data-driven MHEWS can enable developing countries to identify disaster risks with varying degrees of accuracy even in areas with no EWS base. In turn, this will inform the successful implementation and mainstreaming of GRID, as well as highlight how data, digital technologies, and digital infrastructure can strengthen the resiliency of countries. This program is focused on enhancing the planning and implementation of EWS and MHEWS projects with a data-driven approach. A diagnostic tool will be developed based on global practices and lessons learned on EWS, including from GFDRR and others in the World Bank, as well as external organizations. This tool will support lending operations in systematically analyzing the current MHEWS situation in a country and identify opportunities for transforming the existing systems into more data-driven MHEWS by leveraging digital technologies and infrastructure.

List of Activities:

• Develop a diagnostic tool for data-driven MHEWS: the concept of data-driven MHEWS will be developed in collaboration with experts from international organizations, government, academia, and industry. The diagnostic tool will provide guidance to the countries adopting data-driven MHEWS in the current limited environment and also inform the design of strategic roadmaps for the future. To support the application of data-driven MHEWS on the ground, the diagnostic tool will be developed to evaluate the current maturity and suggest the recommended steps and strategies to be implemented.
• Pilot Application of developed Tool: The second activity applied the developed tool in two pilot countries and develops a strategic roadmap for improving the MHEWS in these two countries. This roadmap will consider various approaches to MHEWS, including both centralized and decentralized data collection and monitoring, as well as building on the existing EWS platforms and activities in each country.
• Capacity building and dissemination: The third activity focuses on knowledge sharing and awareness raising for the MHEWS and the diagnostic tool developed. A workshop will be held after the completion of the ASA to disseminate the findings from key deliverables such as conceptual model, diagnostic tool, and strategic roadmap. Virtual presentation will be provided in order to enhance capabilities of those who will engage with data-driven MHEWS.

Outcomes:

Output 1:

• Report on the potential diagnostic tool for data-driven MHEWS

Output 2:

• Short report on the status of data-driven MHEWS in pilot countries (Maldives, Sierra Leone)
• Strategic roadmap for pilot countries(Maldives, Sierra Leone) by deploying the diagnostic tool
• Refined Diagnostic Tool

Output 3:

• Global Knowledge Exchange event on data-driven MHEWS
• Training material developed for WB and public consumption

Outcomes:

• Increased resilience from disasters and climate changes by using data-driven approach
• Direct contributions to Bank lending projects (Digital Maldives Projec t(P177040), Digital Transformation Project (P177077)), follow-up actions to be taken by the Bank and client: new Bank lending, government investment, national policies, and regulation
• Improved benefits from EWS and MHEWS by complementing weak digital foundations and poor data resources with a data-driven approach.
• Enhanced awareness and adoption of a data-driven approach for critical and urgent disasters and climate change by WB staffs and stakeholders in developing countries

Collaboration with K-Partners and Others:

• The team will communicate with relevant DRM teams and GPs to improve the level and effectiveness of the outcome, communicate with the related CMUs for implementation of country-specific activities, and will also cooperate with KoDi to share the expertise
• The team will collaborate with Korean agencies such as National Information Society Agency and Korea, Korea Meteorological Institution(KMI) to get expert feedback and share knowledge regarding data-driven early warning systems, and will explore potential partnerships or inputs from organizations like World Meteorological Organization (WMO), Global Facility for Disaster Reduction and Recovery(GFDRR), and United Nations Disaster Risk Reduction (UNDRR)