DOI · DOI-0136 · record R2623

Refining Flood Risk Predictions in Hawai?i with Generative Machine Learning

Department of the Interior · USGS

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

While global climate models (GCMs) offer climate projections, their coarse spatial resolution does not allow regional characteristics to be captured accurately, which are details crucial for managing risks related to climate hazards like floods, droughts, and heatwaves.

Expected benefits

Recent breakthroughs in generative artificial intelligence (AI) with neural networks offer new possibilities for for statistical downscaling.

System outputs

This project will use these generative AI advancements to create high-resolution (1km) daily and sub-daily precipitation maps for the Hawaiian Islands and use these maps to quantify the risk of flooding events.

Technology

AI classification: Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
System name(s): Not reported
Custom-developed code: No
Public source code: Not yet available

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: No
Demographic features: k) None of the above
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported