Oklahoma Water

Resources Center

Data Analytics for Water Resources - CIVE 5010

School of Civil and Environmental Engineering, Oklahoma State University

 

Class meetings: M/W 8 - 9:15 a.m.

Classroom: Advanced Tech Research Center, Room 121

 

Instructor: Gabriel Perez, Ph.D.

 

Course Description:

The growing availability of large-scale datasets—from rain gauges, radar networks, and satellite products to global climate models—requires practitioners and researchers to master workflows that efficiently collect, pre-process, analyze, and extract actionable insights from these data sources. This course introduces students to modern data analytics techniques with direct applications in water resources engineering and hydrological sciences. The course emphasizes hands-on implementation using Python, with a focus on creating reproducible and scientifically sound workflows tailored to hydrologic systems. Students will work with diverse datasets—including radar rainfall, satellite evapotranspiration, streamflow time series, and climate projections—and develop workflows that span data preprocessing, statistical analysis, signal decomposition, uncertainty quantification, and inference. Particular emphasis will be placed on interpreting results in light of sampling error, epistemic uncertainty, and natural variability, and on communicating analytical findings transparently in both scientific and applied contexts.

 

For more information, email Dr. Perez at gabriel.perez_mesa@okstate.edu.