Assignment name:

General FbF feasibility study on mudflow scenarios in Kyrgyzstan, Tajikistan, and Uzbekistan

Name of Client:

German Red Cross

Duration of assignment (months): 4

Start date (month/year): February 2023

Completion date (month/year): May 2023

Implementing partners, if any:

German Red Cross (GRC)

Red Crescent Society of Kyrgyzstan (RCSK)

Red Crescent Society of Tajikistan (RCST)

Red Crescent Society of Uzbekistan (RCSU)

Red Cross Red Crescent Climate Centre

Country: Kyrgyzstan, Tajikistan, and Uzbekistan

Role on the Assignment: Consultant

Description of Project:

The project involved an in-depth study and analysis of mudflows in Central Asia, with a focus on the development of an Early Warning System (EWS) using the Forecast-based Financing (FbF) mechanism. This study was conducted to explore the feasibility of implementing Forecast-based Financing (FbF) for mudflow hazards in Tajikistan, Kyrgyzstan, and Uzbekistan

Description of actual services provided by our staff within the assignment:

  • Conducted a thorough risk assessment to identify mudflows as the most hazardous natural events in Central Asia
  • Assessed the current forecasting methodologies for mudflows and proposed improvements.
  • Detailed examination of mudflow relevance in Kyrgyzstan, Tajikistan, and Uzbekistan.
  • Evaluated the applicability of existing financial instruments such as the FbF (Forecast-based Financing) mechanism to mudflow hazards.
  • Identified regions prone to mudflow events, such as the Ferghana Valley, Rasht Valley, and Zerafshan Valley
  • Analysed the potential impact of climate change on mudflow frequency in Central Asia
  • Recommended a pilot project in the Uzgen District of Kyrgyzstan to test the application of the FbF mechanism to mudflow hazards, indicating collaboration with relevant national meteorological and hydrological services.
  • Evaluated the vulnerability of settlements and infrastructure in mountainous areas to mudflow hazards.
  • Suggested the development of hardware and software-based early warning systems for mudflows in Central Asia to enhance forecast accuracy and preparedness

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