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Full-Text Articles in Physical Sciences and Mathematics
Machine Learning Predicts Reach-Scale Channel Types From Coarse-Scale Geospatial Data In A Large River Basin, Hervé Guillon, Colin F. Byrne, Belize A. Lane, Samuel Sandoval Solis, Gregory B. Pasternack
Machine Learning Predicts Reach-Scale Channel Types From Coarse-Scale Geospatial Data In A Large River Basin, Hervé Guillon, Colin F. Byrne, Belize A. Lane, Samuel Sandoval Solis, Gregory B. Pasternack
Publications
Hydrologic and geomorphic classifications have gained traction in response to the increasing need for basin-wide water resources management. Regardless of the selected classification scheme, an open scientific challenge is how to extend information from limited field sites to classify tens of thousands to millions of channel reaches across a basin. To address this spatial scaling challenge, this study leverages machine learning to predict reach-scale geomorphic channel types using publicly available geospatial data. A bottom-up machine learning approach selects the most accurate and stable model among∼20,000 combinations of 287 coarse geospatial predictors, preprocessing methods, and algorithms in a three-tiered framework to …
A Performance Comparison Of Machine Learning Algorithms For Arced Labyrinth Spillways, Fernando Salazar, Brian M. Crookston
A Performance Comparison Of Machine Learning Algorithms For Arced Labyrinth Spillways, Fernando Salazar, Brian M. Crookston
Publications
Labyrinth weirs provide an economic option for flow control structures in a variety of applications, including as spillways at dams. The cycles of labyrinth weirs are typically placed in a linear configuration. However, numerous projects place labyrinth cycles along an arc to take advantage of reservoir conditions and dam alignment, and to reduce construction costs such as narrowing the spillway chute. Practitioners must optimize more than 10 geometric variables when developing a head–discharge relationship. This is typically done using the following tools: empirical relationships, numerical modeling, and physical modeling. This study applied a new tool, machine learning, to the analysis …