Publication Date
9-9-2024
Abstract
In this assignment, students will apply traditional and AI-assisted Muskingum routing methods to real-world discharge data from the USGS over a 10-day period. The goal is to compare these approaches, enhancing skills in hydrological modeling and data analysis crucial for water resources engineering.
Course Level
Intermediate Undergrads
Student Learning Outcomes
Critical Inquiry and Analysis, Quantitative Reasoning, Intercultural Knowledge and Skills
Recommended Citation
Vida Atashi. "Comparative Analysis of Muskingum Routing: Traditional vs. AI-Assisted Methods" (2024). AI Assignment Library. 63.
https://commons.und.edu/ai-assignment-library/63
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.