Anticipatory actions are increasingly being taken before an extreme flood event to reduce the impacts on lives and livelihoods. Local contextualized information is required to support real-time local decisions on where and when to act and what anticipatory actions to take. This study defines an impact-based, early-warning trigger system that integra-tes flood forecasts with livelihood information, such as crop calendars, to target anticipatory actions better. We demon-strate the application of this trigger system using a flood case study from the Katakwi District in Uganda. First, we integrate information on the local crop cycles with the flood forecasts to define the impact-based trigger system. Second, we verify the impact-based system using historical flood impact information and then compare it with the existing hazard -based system in the context of humanitarian decisions. Study findings show that the impact-based trigger system has an improved probability of flood detection compared with the hazard-based system. There are fewer missed events in the impact-based system, while the trigger dates are similar in both systems. In a humanitarian context, the two systems trigger anticipatory actions at the same time. However, the impact-based trigger system can be further investigated in a different context (e.g., for livelihood protection) to assess the value of the local information. The impact-based system could also be a valuable tool to validate the existing hazard-based system, which builds more confidence in its use in informing antici-patory actions. The study findings, therefore, should open avenues for further dialogue on what the impact-based trigger system could mean within the broader forecast-based action landscape toward building the resilience of at-risk communities.

Impact-Based Flood Early Warning for Rural Livelihoods in Uganda

Ficchi', Andrea;
2023-01-01

Abstract

Anticipatory actions are increasingly being taken before an extreme flood event to reduce the impacts on lives and livelihoods. Local contextualized information is required to support real-time local decisions on where and when to act and what anticipatory actions to take. This study defines an impact-based, early-warning trigger system that integra-tes flood forecasts with livelihood information, such as crop calendars, to target anticipatory actions better. We demon-strate the application of this trigger system using a flood case study from the Katakwi District in Uganda. First, we integrate information on the local crop cycles with the flood forecasts to define the impact-based trigger system. Second, we verify the impact-based system using historical flood impact information and then compare it with the existing hazard -based system in the context of humanitarian decisions. Study findings show that the impact-based trigger system has an improved probability of flood detection compared with the hazard-based system. There are fewer missed events in the impact-based system, while the trigger dates are similar in both systems. In a humanitarian context, the two systems trigger anticipatory actions at the same time. However, the impact-based trigger system can be further investigated in a different context (e.g., for livelihood protection) to assess the value of the local information. The impact-based system could also be a valuable tool to validate the existing hazard-based system, which builds more confidence in its use in informing antici-patory actions. The study findings, therefore, should open avenues for further dialogue on what the impact-based trigger system could mean within the broader forecast-based action landscape toward building the resilience of at-risk communities.
2023
Adaptation
Community
Decision-making
Emergency preparedness
Flood events
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1259739
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