OMB Individually Reported

Harmful Algal Bloom prediction and detection system for Williams Fork Reservoir [2024 INV#WO0000000184339]

Low riskExact public inventory row

Description

We have used remote sensing products to detect harmful algal blooms throughout the Upper Colorado Basin. However, there have been multiple algal blooms in the Williams Fork Reservoir that have remained undetected.

Detailed example

potential drivers (wind, nutrients, cloud cover) to potentially predict (based on antecedent conditions) when and where new blooms will occur

AI / analytics pattern

Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.

Automation level / stage

a) Pre-deployment – The use case is in a development or acquisition status.

Expected benefit

leverage field data collected with satellite overpasses to tease out what may be causing this discrepancy. We want to leverage AI/ML to see if we can build a new or improve existing models to boost the signal in this high-altitude reservoir

Controls / human review

ATO: No; PIA: Not published