These are the students that I have supervised or co-supervised for M.S. degrees, or whose studies toward an M.S. are still in progress.
Ben R. Hodges
University of Texas at Austin
Students (M.S.)
-
Supervisor: Ben R. Hodges
Project funding: Office of Naval Research, Young Investigator Program Award.
-
Supervisor: Ben R. Hodges
Project funding: Texas Water Development Board
ABSTRACT:The more frequent use of two-dimensional hydrodynamic river models also requires more detailed bathymetry surveys. For smooth bathymetries, there is little difficulty in developing accurate translations from survey data to model; however, in rivers with significant bottom structure (e.g., large woody debris), simple data averaging and interpolation methods may lead to misrepresentation of the bottom bathymetry. It is necessary to identify in the data set what is true bathymetry from what is caused by large woody debris. Two groups of methods are investigated to serve our objective: statistical techniques and filtering techniques. While the former are appealing for their simplicity and direct applicability in modeling, they fail at consistently treating spikes (hypothesized to be large woody debris signature) in the data set. Among filtering techniques, linear filters are turned down due to their inherent trade-off between edge retention and spike rejection. Two nonlinear filters are examined. Median and erosion filters are specifically designed to preserve sharp edges while eradicate spikes. Finally, median filtering is preferred to erosion filtering, for the former leaves large-scale bathymetric features virtually undisturbed -
Supervisor: Ben R. Hodges
Project funding: Office of Naval Research Young Investigator Program Award
-
Supervisor: Ben R. Hodges
Project funding: National Science Foundation Fellowship to P. Kulis
-
Supervisor: Ben R. Hodges
Project funding: Office of Naval Research Young Investigator Program Award
ABSTRACT:
The construction of a water desalination plant is being considered near Corpus Christi Bay TX, as a demonstration initiative funded by the State of Texas to determine whether desalination is a practical approach to obtaining a drought-proof water supply. Desalination plants discharge brine (hypersaline water) in the process of creating fresh water. Existing hypersaline water inflows to Corpus Christi Bay from adjacent waters are suspected to enhance density stratification in the water column. Stratification is often correlated with hypoxia. Therefore the desalination brine could possibly affect the development of hypoxia. There remains an open question as to whether disposal of desalination brine into Corpus Christi Bay would have negative ecological effects. Corpus Christi Bay hypoxia has been documented, but its physical causes have not been clearly identified. There is a need to understand the physical conditions leading to temporary stratification and hypoxia in a bay which is generally vertically mixed and has no long duration dissolved oxygen problems. To investigate stratification on short time scales, measurements were taken at two different areas in Corpus Christi Bay (near Oso Bay and Laguna Madre) using a variety of instruments (microprofiler, weather stations, water quality profiler, etc.) during four field trips that were conducted during the summer of 2005. The present thesis investigates the shorttime scale physics of density currents entering Corpus Christi Bay from the adjacent upper Laguna Madre. There are two principal objectives to this work: 1) document the temporal and spatial behavior of salinity and temperature near the outlet of Laguna Madre where hypoxia has previously been recorded; and 2) develop new data processing, display and analysis methods for the SCAMP microstructure profiler. Note that this research project is not intended to provide conclusive demonstration that high-salinity density currents are directly linked to hypoxia, but is instead building the foundations for future analysis of this problem.
-
Supervisor: Ben R. Hodges
ABSTRACT:
Spatially-distributed depth and velocity predictions are required for habitat based instream flow studies. The purpose of this thesis is to estimate uncertainty of two-dimensional (2D) depth-averaged hydraulic models when applied with close spacing of computational nodes. Motivation for close node spacing is discussed from the ecological, aquatic habitat perspective. Model-generated maps of predicted depth and velocity require sufficient resolution to capture spatial variations relevant to aquatic habitat; however, bathymetric variations at that resolution are more complex than strictly applicable for the depth-averaged hydrostatic model equations. Hydraulic model assumptions are discussed and the geometry of a typical model is analyzed to identify areas that do not conform to assumptions.
Model input data, including bathymetry, water surface elevation, flow rate, depth and velocity measurements, have accuracy within 5% of actual values. Accuracy of depth measurements conducted with a boat-mounted echosounder approach 15 centimeters and are the greatest source of uncertainty for depth error in model predictions. For model test scenarios using the RMA2 2D depth-averaged finite element code, geometries exhibiting slopes greater than 0.10 (ratio of rise to run) or exhibiting abrupt lateral changes in width are shown to cause changes in continuity (velocity conservation) of greater than 2.5%. For a calibrated model of the Brazos River, Texas, 95% of the model area exhibited low uncertainty with continuity deviations less than 2.5%; remaining areas exhibited higher uncertainty resulting from steep slopes or high Froude numbers.
-
Supervisor: Ben R. Hodges
-
Supervisor: Ben R. Hodges
ABSTRACT:
The west campus of Texas A&M University is located in the White Creek watershed and has experienced increases in urbanization in recent years. This urbanization has dramatically impacted White Creek, including bank erosion from higher runoff volumes and peak flows. This study uses HEC-HMS and SWMM models to evaluate the effectiveness of low impact development (LID) and best management practices (BMP) in lowering runoff volumes and peak flows on the Texas A&M Campus. The LID techniques evaluated were green roofs, rainwater harvesting and pervious pavements and the BMP evaluated was a detention pond. A new metric, the Hydrologic Footprint Residence, developed by Giacomoni and Zechman (2009) is used for further comparison. HFR incorporates the quantity of flow from a storm with the cross sections of the stream to determine the flood area. This flood area is plotted with respect to time and the area under the curve represents the HFR, in area-time. The LID and BMP technologies were applied to the watershed and evaluated using 77 historical precipitation events. A set of 10 representative storms were used for analysis. In general, the scenario that was the most effective in lowering the peak flow, runoff volume, and HFR of the storm was the combination of rainwater harvesting and pervious pavements. The detention pond was shown to effectively lower the peak flow for larger storms, but does not change the runoff volume of any storm. The LID techniques were shown to be more effective in reducing the impacts of urbanization for small storms. The results also gave insight into the importance of the precipitation intensity and duration. The importance of the Antecedent Moisture Condition of the soil is evaluated in the second part of the study. The AMC was found to have an impact on the peak flows with AMCIII (saturated soil) resulting in the highest peak flow for each storm event and AMCI (dry soil) resulting in lowest peak flow. -
Supervisor: Ben R. Hodges
Project funding: U.S. National Science Foundation Grant 0710901
ABSTRACT:
New survey technologies are able to provide detailed data on the form and topography of riverbeds. With this increased data resolution, the required computational time rather than data availability has become the limiting factor for river models. Detailed bathymetric data can be used to provide better empirical representation of drag and roughness at fine scales, allowing a priori selection of roughness using known physics rather than a posteriori calibration. However, we do not have sufficient guidance or understanding from the literature to represent known heterogeneities smaller than our practical grid scale. The problem is what to do with known subgrid-scale bathymetric features and roughness when our models must use a coarser computational grid. In this project, we simplify this complex problem to analyzing flow in a simple open channel with a single patch of relatively high roughness against an otherwise uniform background of low roughness. We model this open channel with a two-dimensional, depth-averaged river model. By running multiple simulations using different grid sizes we gain insight into how the relationship between the grid cell size and the patch size affects the appropriate physical selection of roughness parameter.
As the primary focus, the present work proposes and investigates several methods for upscaling known fine-scale drag coefficient data to a coarser grid resolution for a model. For the tested conditions, it appears that a simple area-weighted linear average is simple to apply and creates a flow field very similar to the best results achieved by calibration.
As a secondary issue, the present work examines grid-dependent behaviors when using model calibration. Although recalibration of models for different grid scales is a common practice among modelers, we could find relatively little documentation or analysis. In our work, we examine both single-cell calibration (i.e. changing roughness in only the cell containing the rough patch) and multiple-grid cell calibration involving neighbor cells. With either method, improving calibration required multiple model simulations and comparative analysis for each tested grid size and was inefficient compared to the upscaling approach. As expected, the calibration at a given grid size was always inappropriate for a different grid size.
-
Supervisor: Ben R. Hodges
Project funding: Texas General Land Office (TGLO).
ABSTRACT:
A new method for automatically integrating the results of hydrodynamic models of currents in Texas bays with the National Oceanic and Atmospheric Administration’s (NOAA) in house oil spill trajectory model, the General NOAA Operational Modeling Environment (GNOME), is presented. Oil spill trajectories are predicted by inputting wind and water current forces on an initial spill in a dedicated spill trajectory model. These currents can be field measured, but in most real and meaningful cases, the current field is too spatially complex to measure with any accuracy. Instead, current fields are simulated by hydrodynamic models, whose results must then be coupled with a dedicated spill trajectory model. The newly developed automated approach based on Python scripting eliminates the present labor-intensive practice of manually coupling outputs and inputs of the separate models, which requires expert interpretation and modification of data formats and setup conditions for different models.
The integrated system is demonstrated by coupling GNOME independently with TXBLEND – a 2D depth-averaged model which is currently used by the Texas Water Development Board, and SELFE – a newer 3D hydrodynamic model with turbulent wind mixing. A hypothetical spill in Galveston Bay is simulated under different conditions using both models, and a brief qualitative comparison of the results is used to raise questions that may be addressed in future work using the automated coupling system to determine the minimum modeling requirements for an advanced oil spill nowcast/forecast platform in Texas bays.
-
Supervisor: Ben R. Hodges
Project funding: Texas Water Development Board (TWDB), U.S. Army Corps of Engineers.
ABSTRACT:
Increasing municipal and regional water demands have reduced freshwater inflows to the Nueces Delta. These flow reductions impair the marsh ecosystem’s functionality. As part of a United States Army Corps of Engineers multi-agency collaboration to restore the Nueces River and its tributaries, we have developed a massconservative hydrodynamic model to analyze fate and transport of freshwater and tidal inflows to the Nueces Delta. The model is built upon the LIDAR bathymetric data collected by the Coastal Bend Bays and Estuaries Program (CBBEP). Input data includes tidal, salinity, and wind data obtained from the Texas Coastal Ocean Observation Network (TCOON), pumping data from the Nueces River Authority, precipitation data from NOAA, and river flow from the USGS.
The underlying modeling method uses conservative finite-difference/volume discretization on a Cartesian rectangular grid to simulate the movement of water and salt fluxes across the delta. Sub-models to represent the hydraulic influence of flow constrictions (e.g. railroads trestles, culverts) have been developed. The model’s response to forcing from wind, precipitation, and roughness were analyzed. The time to spin up for the model was analyzed and found to be approximately seven days. Preliminary validation of the model was qualitative but the overall trend of the tide coming in appears correct at the monitoring stations analyzed, indicating that the lowest frequency forcing of the tide and wind are correct. The effects of pumping into the delta were investigated under different pumping conditions to reveal the area inundation and impacts on salinity from pumping.
-
Supervisor: Ben R. Hodges
Project Funding: Texas General Land Office (TGLO)
ABSTRACT:
A new method is presented to provide automatic sequencing of multiple hydrodynamic models and automated analysis of model forecast uncertainty. A Hydrodynamic and oil spill model Python (HyosPy) wrapper was developed to run the hydrodynamic model, link with the oil spill, and visualize results. The HyosPy wrapper completes the following steps automatically: (1) downloads wind and tide data (nowcast, forecast and historical); (2) converts data to hydrodynamic model input; (3) initializes a sequence of hydrodynamic models starting at pre-defined intervals on a multi-processor workstation. Each model starts from the latest observed data, so that the multiple models provide a range of forecast hydrodynamics with different initial and boundary conditions reflecting different forecast horizons. As a simple testbed for integration strategies and visualization on Google Earth, a Runge-Kutta 4th order (RK4) particle transport tracer routine is developed for oil spill transport. The model forecast uncertainty is estimated by the difference between forecasts in the sequenced model runs and quantified by using statistics measurements. The HyosPy integrated system with wind and tide force is demonstrated by introducing an imaginary oil spill in Corpus Christi Bay. The results show that challenges in operational oil spill modeling can be met by leveraging existing models and web visualization methods to provide tools for emergency managers.
-
Supervisor: Ben R. Hodges
Project funding: City of Austin.
ABSTRACT:
Barton Springs Pool (BSP) is an important ecological and recreational resource to the City of Austin (CoA). Due to sediment accumulation, excessive algal growth, and concern for water velocities through salamander habitat, improving the flow regime of BSP was identified as an important focus for future infrastructure development in Barton Springs Pool. The CoA commissioned this project to develop and test a hydrodynamic model to provide a basis for understanding the flow dynamics of BSP, and to aid in future infrastructure developments in BSP. This phase of the project included the collection of bathymetric and velocity data, creating a hydrodynamic model of BSP that dynamically represents space-time varying 3D velocities, and testing the model using the default settings and an adjustment of the outlet coefficients. The model was run with three targeted inflow scenarios to determine both how the model responds with varying inflows, and to provide a general idea of how flow in BSP is affected by the magnitude o fthe inflow.
The model used was the Fine Resolution Environmental Hydrodynamic Model that solves the 3D non-hydrostatic Navier-Stokes equations in a split hydrostatic/nonhydrostatic approach. The model was run using the default settings and the outputs were compared to available data. Results from these initial runs showed that further calibration is necessary. Model runs under the targeted inflow scenarios showed that as inflow increases, velocities in the upstream portion of BSP increase correspondingly, but this is not reflected in the downstream portion of BSP.
-
Supervisor: Ben R. Hodges
Project funding: Gulf of Mexico Research Initiative (GoMRI).
ABSTRACT:
A vessel-mounted ADCP study focusing on channel-scale flow patterns in Galveston Bay near the Houston Shipping Channel and Mid-Bay Island is described. Winds of 5-7 m/s at 215-230 degrees from N were present during data collection. For both peak ebb and flood conditions, the tidal circulation forced flow in a direction opposing the wind, perhaps due to a large-scale flow divergence forced by Mid-Bay Island. The strongest such currents were measured closest the island.During peak flood flow, the shape of the along-channel velocity profile for the open water upwind of the channel at Mid-Bay Island indicated uniform flow, and the salinity profile indicated a well-mixed water column. The near-island along channel velocity profile showed a near-linear trend, and the salinity profile indicated a stratified water column. This suggested that the stratification had some effect the velocity profile shape, but further research is needed to better quantify this effect.
During peak ebb flow, the near-island along-channel velocities were highly variable with respect to the mean velocity, indicating an area of active turbulence. Salinity profiles collected in the open water and near-island both showed stratification, something that was not seen during flood conditions. Differences in observations between flood and ebb flows can possibly be attributed to the survey location with respect to the chain of dredge spoil islands. During flood flows Mid-Bay Island is the first of the islands, and the flows surrounding the island may part of a developing horizontal boundary layer. During ebb flows the island is last in the chain relative to the direction of flow, and therefore the surrounding flows are well back from the leading edge of a horizontal boundary layer.
-
Supervisor: Ben R. Hodges
Project funding: Fulbright Fellowship to Alfredo Hijar, U.S. NSF grant 1331610.
ABSTRACT:
A new methodology is presented to construct reliable river channel cross section approximations. These approximations are based on the idea of downstream hydraulic geometry as well as supported by the information collected by the USGS streamflow measurement stations across the study area. A hydraulic river routing model (SPRNT) is run with the newly constructed cross section approximations. Initial conditions for the simulation are estimated based on the steady state solution for the model. Boundary conditions or lateral inflows for the river network are estimated based on the outputs of a Land Surface model: Noah, which provides surface and sub-surface runoff for every catchment area in the San Antonio and Guadalupe river basins. Simulations are compared with observed measurements from the USGS stations.
-
Supervisor: Ben R. Hodges
Project funding: Texas Department of Transportation (TxDOT)
ABSTRACT:
The new Texas Department of Transportation curb inlet uses 6 inch flush slab supports for the top slab of a curb inlet. HEC-22, which provides design equations used by TxDOT, states flush slab supports can reduce an on-grade inlet’s interception capacity by as much as 50%, yet does not provide any guidance on quantifying these effects. Full-scale physical modeling of the TxDOT curb inlet on-grade was performed to investigate the effects of flush slab supports on hydraulic performance. In addition, the modeled curb inlet is compared with HEC-22 and other curb inlet design equations. No measurable difference in interception capacity or ponded width was found between curb inlets with flush slab supports and without. For the 5 ft modeled curb inlet a combination of Guo and MacKenzie (2012) design equation and HEC-22 align best, yet neither align with every tested slope combination. HEC-22 design equations were found to over-predict the 15 ft modeled curb inlet by an average factor of 2.3:1. No other design equations were found to accurately predict hydraulic performance for the 15 ft modeled curb inlet.
-
Supervisor: Ben R. Hodges
Project funding: U.S. Environmental Protection Agency, Cooperative Agreement No. 83595001
ABSTRACT:
Parameter calibration is considered a crucial, albeit arduous, step for reliable performance of the Stormwater Management Model, one that engineers often undertake manually. This research presents an open-source, automated calibration routine that returns a calibrated model input file to the user. The routine first represents the catchment network as a directed graph object using the NetworkX python package for flexibility in handling real-world observed data availability. Once the calibratable subset of the system is identified, a multi-objective, genetic algorithm (modified Non-Dominated Sorting Genetic Algorithm II) estimates the Pareto front for the objective functions within the feasible performance space. The solutions on this Pareto front represent the optimized parameter sets for matching simulated and observed catchment behavior. A specific solution among this Pareto set can be chosen by assigning weights to the objective functions. This solution is then returned to the user, completing a fully automated calibration process that requires minimal user input and no oversight.