Our team has been awarded a 5-year grant to establish the National Center for Infrastructure Modeling and Management. As part of our research under NCIMM, we are working down in the guts of the computational kernel that drives the EPA’s Storm Water Management Mode (SWMM). This model is widely used across the USA and the world for design, analyses, and control of storm water systems in urban infrastructure. Our goal in this project is to create a computational engine that can readily parallelize across 1000’s of processors (or threads) so that SWMM will be a fast, adapatable model for the next generation of computers.  This project is the focus of Assoc. Prof Ben Hodges, Dr. Frank Liu of IBM Research Austin, and UT Research Fellow Dr. Ehsan Madadi-Kandjani.

We are working on a genetic algorithm that can be used to rapidly conduct a Monte-Carlo set of SWMM simulations as part of an automated calibration system.  This effort is being developed by graduate student Edward Tiernans, supervised by Assoc. Prof. Hodges.

Our team has been awarded a 5-year grant to establish the National Center for Infrastructure Modeling and Management. As part of our research under NCIMM, we are developing new capabilities for the EPA’s water distribution model (EPANET). This project is being driven by Asst. Profs. Lina Sela and Kasey Faust, who are supervising Research Fellow Dr. Ehsan Madadi-Kandjani.

The Texas Department of Transportation (TxDOT) is interested in performance of their new modular PCO curb inlets with the full-scale tilting roadway at the laboratories of the UT Center for Water and the Environment.  The results were surprising and showed that the established equations (known as HEC-22) are severe over-predictions of the full-capture capacity of long inlets (10 to 15 ft) under most installation conditions.  This study has been accomplished by graduate students Frank Schalla and Muhammad Ashraf under the supervision of Assoc. Prof. Hodges. Funding has been provided by TxDOT.

We have been working with the Fine Resolution Environmental Hydrodynamics Model (Frehd) on the Nueces River Delta to evaluate salt/fresh water exchange. Overbank flows and flooding of the Delta has been reduced over the past several decades, which has caused increasing episodes of hyper-salinity. The Coastal Bend Bays and Estuaries Program (CBBEP), the City of Corpus Christi, the Texas Water Development Board (TWDB), and the UT Marine Science Institute have been working towards restoring the functioning of the Delta. Our part has been to model the way in which fresh water and salt water transport occur across Delta with a goal of finding the most effective strategies for using the available fresh water. This research has been conducted by graduate students Andrea Ryan and Zhi Li, under the supervision of Assoc. Prof. Hodges. Funding has been provided by the Texas Water Development Board

We simply do not know what happens to much of the water that comes down the Trinity River under high flow conditions. We know that much of it will enter the Delta, but the pathways and flows are not understood. This issue is important because the quantity, timing, and location of freshwater supplies to the Delta and Galveston Bay will affect the fishery habitats and overall health of the environment.  The complexity of the interconnections in the marshland of the Trinity Delta are challenging to model (similar to, but larger than, the Nueces River Delta).  This work is being conducted by graduate student Zhi Li under the supervision of Assoc. Prof. Hodges.  Funding is provided by the Texas Water Development Board.

The Texas General Land Office (TGLO) in conjunction with the Texas Water Development Board (TWDB) uses computer models of Texas bays, estuaries, and coastal waters to predict likely oil spill transport paths during a spill event. We have been working to develop improved oil spill prediction capabilities with a modeling system called HyosPy – the Hydrodynamic Oil Spill system Python. This system combines the SUNTANS hydrodynamic model with the GNOME oil spill model in an automated multi-model system.  Our present focus is in a collaborative study with Prof. Scott Socolofsky and Dr. Kristen Thyng at Texas A&M University to better understand the connections between bays and the coastal waters.  This work has been the focus of graduate students Xianlong Hou and Dongyu Feng.

The National Water Model (NWM) has been developed by a broad team centered in the Office of Water Prediction at NOAA. The present model is able to provide predicted water flows in all 2.2 million miles of rivers and streams throughout the continental USA. However, the underlying computational algorithms in the NWM lack some of the important physics that affect water flow. In a collaboration with IBM Research Austin, we have been working towards advanced methods for modeling the full physics of river flows in continental-scale networks.  Graduate student Cheng-Wei (Justin) Yu has been working closely with Dr. Frank Liu of IBM and Assoc. Prof. Hodges on this work.  Partial funding for a related part of this work was provided by the US National Science Foundation.

Seawater desalination plants pose an unrecognized hazard if the brine discharge does not fully mix with ocean water. We have shown that a brine plume that has consistently even a small increase of salinity above ambient (about 2 ppt), is at risk for developing low oxygen (hypoxia) along the ocean bottom – in effect a “dead zone”. The models used to plan desalination plan discharges are typically rather poor at estimating the longevity of such small increases in salinity.  As a caveat, this effect is unlikely to occur if there are sufficient sources of ocean turbulence (e.g. strong currents and winds). A key problem is that no one seems to be looking for this problem – licensing of desalination discharges tend to be based on the salinity tolerance of biota rather than the fact that the denser brine water can cause stratification near the bottom, resulting in rapid loss of oxygen and a cutoff of the natural oxygen replenishment from the surface. (unfunded project)