Browsing by Subject "Hydrodynamic model"

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Evaluating hydrodynamic uncertainty in oil spill modeling
(2013-05) Hou, Xianlong; Hodges, Ben R.
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.
Modeling hydrodynamic fluxes in the Nueces River Delta
(2011-08) Ryan, Andrea Johanna; Hodges, Ben R.
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 mass-conservative 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.