AI system
- System
-
FloodAI machine-learning flood-forecasting service
- Model
-
Not assessed
- Release
-
Not assessed
- Application developer
-
Northumbria University with project partners
- Role
-
Not assessed
- Configuration
-
Not assessed
- Inputs and outputs
-
Not assessed
- Autonomy
-
Not assessed
- Workflow
-
The project covers six catchments and combines university research with council, Arup, Isle Utilities, and Environment Agency participation. Training sources include Met Office, Environment Agency, and hydrological-model data.
- Human oversight
-
Not assessed
- Relation to AI
-
Machine-learning models combine environmental and hydrological data to support flash-flood forecasting. At publication, the service was at alpha stage. No warning, response, or avoided harm is attributed to operational use.
- AI contribution
-
Not assessed
Benefits
- Outcome identifiers
-
Not assessed
- Benefit
-
Northumberland describes an alpha-stage flood-forecasting service for six catchments. No issued warning or avoided flood impact is reported.
- Category
-
Reduced Risk
- Status
-
Intended benefit
- Beneficiary groups
-
Society. Organizations.
- Beneficiaries
-
Not assessed
- Reach
-
Not assessed
- Distribution and access
-
Not assessed
- Duration
-
Not assessed
- Expected?
-
Yes
- Costs and harms
-
Not assessed
Measurement
- Studies
-
Not assessed
- Study design
-
Not assessed
- Measurement
-
Not assessed
- Setting and sample
-
Not assessed
- Measures
-
Not assessed
- Comparison
-
Not assessed
- Results
-
Not assessed
- Additional value from AI
-
Not assessed
- Limitations
-
Not assessed
- Denominators
-
Not assessed
- Materials for replication
-
Not assessed
Money
- Kind of value
-
Not assessed
- Amount
-
Not assessed
- Currency and prices
-
Not assessed
- Period and unit
-
Not assessed
- Realization
-
Not assessed
- Recipients and payers
-
Not assessed
- Gross or net
-
Not assessed
- Included costs
-
Not assessed
- Comparison
-
Not assessed
- Method
-
Not assessed
- Return and payback
-
Not assessed
People and places
- Participants
-
Developer: Northumbria University with project partners. Operator: Northumberland County Council.
- Jurisdictions
-
Benefit:
United Kingdom. - Ownership and control
-
Not assessed
- Dependencies
-
Not assessed
- Cross-border connections
-
Not assessed
- Geopolitical implications
-
Not assessed
Follow-up
- Conditions for replication
-
The conditions needed to reproduce the benefit are unspecified.
- Replication attempts
-
Not assessed
- Later findings
-
Not assessed
- Availability
-
Not assessed
- Institutional decision
-
Not assessed
- Grounds
-
Not assessed
- Action and result
-
Not assessed
- Success criterion
-
Not assessed
Evidence
- Source numbers
-
AIBD-0555-source-0001
- Citations
-
Numbered references below.
- Language
-
Not assessed
- Source relationships
-
Operator
- Original evidence
-
Not assessed
- Access and versions
-
Not assessed
- Supported findings
-
Not assessed
- Evidence links
-
Not assessed
- Evidence strength
-
Not assessed
- Missing evidence
-
Not assessed
Grades
- Assessed benefits
-
Society. Organizations.
- Depth
-
Not assessed
- Reasons
-
Society: Improved flood resilience is the aim, but no warning or changed flood outcome is reported. Organizations: Improved forecasting is intended. Operational gains are unreported.
- Observed or intended
-
Intended benefit
- Rubric
-
Not assessed
- Assessor and date
-
Not assessed
- Alternative assessments
-
Not assessed
- Fill
-
The deployer's account
Entry details
- Kind
-
Not assessed
- Related entries
-
Not assessed
- Field
-
Flood forecasting and resilience.
- Purpose
-
Develop forecasts for flash-flood-prone catchments that lack suitable warning coverage.
- Dates
-
Source published: 17 June 2025. Updated: 22 October 2026.
- Stage
-
Not assessed
- Version
-
SHA-256: 589c36be629b…
References
- Other identifiers
-
LGA AI case-study bank. LGA-019.
- Category mappings
-
Not assessed
- Brief
-
Not assessed
- Revisions
-
1 revisions. Latest: 22 October 2026.