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ARS Home » Plains Area » El Reno, Oklahoma » Oklahoma and Central Plains Agricultural Research Center » Agroclimate and Hydraulics Research Unit » Research » Publications at this Location » Publication #421966
Research Project: Development of a Monitoring Network, Engineering Tools, and Guidelines for the Design, Analysis, and Rehabilitation of Embankment Dams, Hydraulic Structures, and Channels

Location: Agroclimate and Hydraulics Research Unit

Title: Machine learning applications in hydrology, with application to drought frequency, water quality, and flood forecasts

Author
item Livsey, Daniel

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/18/2025
Publication Date: 11/20/2025
Citation: Livsey, D.N. 2025. Machine learning applications in hydrology, with application to drought frequency, water quality, and flood forecasts. USDA Artificial Intelligence User Forum, November 19-21, 2024, College Station, TX Presentation.

Interpretive Summary:

Technical Abstract: Examples of machine learning applications in hydrology will be discussed. Case examples will include prediction of past drought conditions in the Southwestern United States, water quality impacts in the Great Barrier Reef, and lake level forecasting in the Central United States. Following case examples, a discussion on how to: a) reduce monitoring costs using machine learning algorithms and b) advance physical processes understanding from empirical approaches will be provided. USDA is an equal opportunity provider and employer.