Keywords

Shoaling, Forecasting, Navigation, Dredging, Optimization, Operational Behavior

Abstract

Navigation channels are the economic arteries of U.S. maritime trade, yet their efficiency and safety are continually threatened by sedimentation and the escalating costs of dredging. Traditional tools used by the U.S. Army Corps of Engineers (USACE) to forecast shoaling and estimate dredging needs often fall short of capturing the complex interplay between channel condition, vessel behavior, and maintenance decisions. This dissertation develops and integrates three complementary innovations to address this challenge. First, a Parametric Linear Regression Methodology (PLRM) is introduced to improve shoaling predictions by blending long-term and short-term sedimentation rates with tunable weighting factors. This method achieves forecasting accuracies exceeding 80–90% and has the potential to reduce costly Requests for Equitable Adjustment in dredging contracts. Second, a Volume to Dredge (V2D) metric is proposed to right-size dredging volumes based on vessel transit demands. By comparing actual dredged volumes with the material intersecting vessel footprints at defined clearance margins, V2D distinguishes whether a channel is over-, under-, or appropriately dredged. The resulting Davies–Young equation provides a quantitative framework for aligning dredging intensity with vessel risk.

Finally, this work extends beyond physical metrics to explicitly incorporate the behavioral and economic consequences of shoaling. Statistical analyses of vessel draft distributions reveal how shoaled conditions reshape operator decisions through light-loading, tidal scheduling, or port avoidance, with measurable shifts in the tails and central tendency of draft usage. These distributional changes expose the hidden costs of shoaling that clearance metrics alone cannot capture and provide a quantitative basis for linking physical condition to operational adaptation. Together, these contributions form a unified framework—spanning prediction, evaluation, and operational consequence—that enhances USACE’s ability to manage federal waterways. By connecting sediment dynamics, vessel behavior, and dredging strategy, this research offers a path toward safer, more efficient, and economically resilient navigation channel maintenance.

Completion Date

2025

Semester

Fall

Committee Chair

Dr. Jiannan Chen

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Civil, Environmental, and Construction Engineering

Format

PDF

Identifier

DP0029849

Document Type

Thesis

Campus Location

UCF Online

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