Federal AI Intelligence
Menu
Snapshot · OMB 2025 inventory · processed Oct 11, 2026
DOE · DOE-659 · record R3515

Groundwater Modeling

Department of Energy · LM HQ - Office of Legacy Management (LM)

Overview

Development stage
DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation
Not high-impactSource: c) Not high-impact
Impact justification
This AI use case does not serve as a principal basis for decisions or actions with legal, material, and binding
Start date
2003-01-02 (day precision)Source: 2003-01-02T00:00:00
Withheld from public reporting
NoSource: a) No

Mission

Topic area
Energy and the Environment
Operational functions
No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Solves critical challenges in water modeling by providing forward-looking monitoring.

Expected benefits

Forward cast ground water behavior

System outputs

AI outputs is a ground water model and that model will be evaluated by humans.

Technology

AI classification
Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s)
LMGSS
Custom-developed code
No
Public source code
Not reported

Sourcing

How it was built
Purchased from vendorSource: a) Purchased from a vendor
Vendor (as reported)
PEST
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
Yes
Demographic features
k) None of the above
Training and evaluation data
Data is held back from the models to validate model outputs.
Federal Data Catalog
Not reported

Governance

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

Pre-deployment testingReported in placeSource: a) Yes
AI impact assessmentReported in progressSource: b) In-progress
Independent reviewReported in progressSource: d) In-progress
Ongoing monitoringReported in progressSource: b) Development of monitoring protocols is in-progress
Operator trainingReported in progressSource: b) Establishment of sufficient and periodic training is in-progress
Fail-safeReported in placeSource: a) Yes
Appeal processNot applicableSource: b) Not applicable
User and public consultationReported in placeSource: a) Direct usability testing

Potential impacts and how they were identified

Improved management of the remedy