PRObability of Streamflow PERmanence (PROSPER models) [2024 INV#WO0000000109074]
Description
predictions of reliable surface flow in streams at regional scales to inform land and water resource decisions related to water availability.
Detailed example
prediction of the annual probability of a stream reach having year round surface flow.
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
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
more accurate estimates of water availability for more efficient use of field verification efforts, expected increased success of restoration or species conservations projects.
Controls / human review
ATO: No; PIA: Not published
Data needed
flow/no flow field observations and publicly available gridded spatial datasets to describe climate and physiography