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Good practice Imported

SAADAAL — Somalia's AI-Enhanced Early Warning Platform for Drought and Flood, Run With SODMA and Southwest State

Somalia · Baidoa · See the Somalia profile

Evidence: Descriptive / self-reported Top 93% 27/100 · Ask Evidence Copilot about this practice

SAADAAL ("forecast" in Somali) is an AI-enhanced early-warning platform for drought and flood, piloted across seven river stations in Somalia's Southwest State, with federal agency SODMA and the state ministry trained as partners since April 2024.

7 stations
River-monitoring stations covered by the pilot in Southwest State
124,150 people
People affected by the 2024 Gu rainy-season floods nationally (national context figure, not SAADAAL's specific coverage) (2024 Gu rainy season)
SAADAAL — Somalia's AI-Enhanced Early Warning Platform for Drought and Flood, Run With SODMA and Southwest State

Details

Maturity
Pilot
Promoter
Shaqodoon Organization / Somali Resilience Programme (SomREP), with Southwest State Ministry of Humanitarian Affairs & Disaster Management and the Somali Disaster Management Agency (SODMA)
Period
April 2024–present
Keywords
disaster early warning, drought, flooding, generative AI, humanitarian anticipatory action

Context

SAADAAL, Somali for 'forecast,' is an early-warning platform for drought and flooding built and operated by the NGO Shaqodoon under the CARE/World Vision-led Somali Resilience Programme (SomREP), covering seven river-monitoring points in Somalia's Southwest State, including the Afgoye and Qansaax Dheere districts.

Objectives

The platform combines real-time weather data with historical rainfall and flood records from FSNAU, FAO-SWALIM and Open-Meteo, plus locally owned water-level sensors and automated weather stations, using a generative-AI layer to produce simplified reports and dashboard insights for disaster-management staff, then pushing alerts through the IMAQAL Voice Broadcast Platform to reach people with low literacy or no smartphone.

Activities

On 24 April 2024, Shaqodoon and SomREP trained staff from the Southwest State Ministry of Humanitarian Affairs and Disaster Management on the AI-enhanced system, with the federal Somali Disaster Management Agency (SODMA) named as a formal stakeholder using the platform's outputs, and independent technology press corroborated the government partners and technical mechanism.

Results

The platform remains a pilot limited to Southwest State and has not scaled nationally; no quantified performance data — warnings issued, lead time achieved, people reached, or accuracy against actual flood or drought events — has been published, and funding for continuation beyond the current programme cycle is not disclosed.

Implementation
Indicative cost
Low (< €50k)
Time to results
Medium (1–3 years)
Staffing & skills
Shaqodoon Organization, Somali Resilience Programme (SomREP, CARE/World Vision-led), Southwest State Ministry of Humanitarian Affairs & Disaster Management, Somali Disaster Management Agency (SODMA)

Conditions for success

  • Integration with the existing IMAQAL Voice Broadcast Platform across multiple telecom operators to reach low-literacy/no-smartphone users
  • Formal training of state ministry and federal agency staff (24 April 2024)
  • Combining local sensor data with established datasets (FSNAU, FAO-SWALIM, Open-Meteo)

Common failure modes

  • No quantified performance data (warnings issued, lead time, accuracy) published
  • Not scaled beyond Southwest State
  • Continuation funding beyond the current programme cycle not disclosed
  • NGO-operated rather than government-owned/built

Commonly funded by

Philanthropic / foundation funding

Indicative funding routes for practices of this type — always check each programme's current calls and eligibility rules.

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Data sources

Where this practice's information was retrieved from, and when.

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