25 Jun 2020

PUBLICATION NOTICE: Hydraulic Analysis and Modeling of Navigation Conditions near the Mississippi River Bridges in Vicksburg, Mississippi

Abstract: The River and Estuarine Engineering Branch of the Coastal and Hydraulics Laboratory developed a two-dimensional numerical model of the Mississippi River near Vicksburg, MS, using Adaptive Hydraulics to investigate navigation conditions through the Interstate 20 and Old Highway 80 Bridges reach. A focus of the study was determining the Marshall Brown Dikes impact to velocities and navigation through the reach. Proposed dikes, focused on improving currents, were also tested to determine if they are a feasible option to improve navigability through the bridges. A second proposed alternative, a levee to protect the articulated concrete mattress (ACM) field, was also simulated to determine if flood damage to the ACM field could be successfully reduced without negatively impacting navigation. Velocity data from 2008 throughout the reach of concern were used for validation along with water surface elevation data from 2008, 2011, 2016, and 2018. The Marshall Brown Dikes were shown to have a localized impact on velocities near the dikes, but the changes to the velocity downstream near the bridge were negligible for all tested flow rates. Simulations of the proposed dikes did not result in an improvement to navigation conditions, but the proposed levee was successful in decreasing velocities and depths over the ACM field.

17 Jun 2020

PUBLICATION NOTICE: Theory, Formulation, and Implementation of The Cartesian and Spherical Coordinate Two-Dimensional Depth-Averaged Module of the Adaptive Hydraulics (AdH) Finite Element Numerical Code

Abstract: The US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, has undertaken the development of the multi-module Adaptive Hydraulics (AdH) hydrodynamic, sediment, water quality, and transport numerical code. This report documents the mathematical formulation and numerical implementation of the two-dimensional depth-averaged module of AdH.

22 Apr 2020

PUBLICATION NOTICE: A Practical Two-Phase Approach to Improve the Reliability and Efficiency of Markov Chain Monte Carlo Directed Hydrologic Model Calibration

ABSTRACT: Markov chain Monte Carlo (MCMC) methods are widely used in hydrology and other fields for posterior inference in a Bayesian framework. A properly constructed MCMC sampler is guaranteed to converge to the correct limiting distribution, but convergence can be very slow. While most research is focused on improving the proposal distribution used to generate trial moves in the Markov chain, this work instead focuses on efficiently finding an initial population for population-based MCMC samplers that will expedite convergence. Four case studies, including two hydrological models, are used to demonstrate that using multi-level single linkage implicit filtering stochastic global optimization to initialize the population both reduces the overall computational cost and significantly increases the chance of finding the correct limiting distribution within the constraint of a fixed computational budget.