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Berkeley, CA, United States

MacWilliams M.L.,Delta Modeling Associates Inc. | Gross E.S.,Resource Management Associates Inc.
San Francisco Estuary and Watershed Science | Year: 2013

Circulation in Clifton Court Forebay (CCF) was simulated using the three-dimensional(3-D) hydrodynamic model UnTRIM. These numerical simulations were performed to provide a better understanding of circulation patterns, flow pathways, and residence time in Clifton Court Forebay in support of ongoing studies of pre-screen loss and fish facility efficiency for delta smelt (Hypomesus transpacificus) at the California State Water Project (SWP) export facilities. The 3-D hydrodynamic model of CCF was validated through comparisonsto observed water surface elevations inside CCF, and comparisons to observed drifter paths and velocity measurements collected by the U.S. Geological Survey as part of this study. Flow measurements collected near the radial gates for 2 days during relatively low inflows suggest that the Hills (1988) gate equations may over-estimate inflow by as much as 39% when the CCF radial gates are only partially opened. Several alternative approaches toimprove the implementation of the radial gate flows in the UnTRIM model were evaluated. The resulting model accurately predicts water surface elevations and currents inside CCF over a range of wind and operating conditions. The validated model was used to predict residence time and other transport time scales for two 21-day simulation periods, one of very low daily SWP export pumping averaging 19.3 m3 s-1 and one for moderate daily SWP export pumping averaging 66.6 m3 s-1. The average transit time, indicating the time from entering CCF to reaching the fish facility, was estimated as 9.1 days for low export conditions and 4.3 days for moderate export conditions. These transport time scale estimates may be used to inform estimates of pre-screen losses inside CCF due to predation or other causes. Source

Enterprise Resource Management Associates | Date: 2016-04-01

Meat, fish, poultry and game; meat extracts; preserved, frozen, dried and cooked fruits and vegetables; jellies, jams, compotes; eggs, milk and milk products; edible oils and fats. Agricultural, horticultural and forestry products and grains not included in other classes; live animals; fresh fruits and vegetables; seeds, natural plants and flowers; foodstuffs for animals; malt.

DeGeorge J.F.,Resource Management Associates Inc. | Ackerman M.E.,Resource Management Associates Inc. | Baker P.R.,U.S. Army
World Environmental and Water Resources Congress 2014: Water Without Borders - Proceedings of the 2014 World Environmental and Water Resources Congress | Year: 2014

The Hydrologic Engineering Center's (HEC) watershed analysis tool (HEC-WAT) has been developed to facilitate integrated numerical modeling studies for water resources planning. One of the key design concepts of HEC-WAT is the use of "plug-in technology" as a means of incorporating a wide range of independently developed numerical models and data-processing tools into an integrated simulation sequence. For example, the application of HEC-WAT for the Columbia River Treaty (CRT) 2014/2024 Review analysis includes simulation of hydrology, reservoir operation for hydropower and flood control, river hydraulics, and flood impact analysis, which for some runs includes nearly 50 linked model simulations. Plug-ins used in the CRT analysis include standard models (HEC-ResSim, HEC-RAS, and HEC-FIA), existing software tools specific to the Columbia River system, and specific code developed for CRT. HEC-WAT defines an application programming interface (API) that allows independent developers the ability to contribute a "plug-in" module that provides access to numerical models data-processing tools for use in an HEC-WAT program sequence. This plug-in architecture allows HEC-WAT to stay model independent while supporting complex system-specific analysis, such as CRT. The HEC-WAT plug-in API facilitates the file management, editing model data, passing of data from one model to the next in the program sequence, and viewing results. © 2014 American Society of Civil Engineers. Source

MacWilliams M.L.,Delta Modeling Associates Inc. | Bever A.J.,Delta Modeling Associates Inc. | Gross E.S.,Resource Management Associates Inc. | Ketefian G.S.,Resource Management Associates Inc. | And 3 more authors.
San Francisco Estuary and Watershed Science | Year: 2015

The three-dimensional UnTRIM San Francisco Bay- Delta model was applied to simulate tidal hydrodynamics and salinity in the San Francisco Estuary using an unstructured grid. Model predictions were compared to observations of water level, tidal flow, current speed, and salinity collected at 137 locations throughout the estuary. A quantitative approach based on multiple model assessment metrics was used to evaluate the model accuracy for each comparison. These comparisons demonstrate that the model accurately predicted water level, tidal flow, and salinity during a three year simulation period which spanned a large range of flow and salinity conditions. The model is therefore suitable for detailed investigation of circulation patterns and salinity distributions in the estuary. The model was used to investigate the location, and spatial and temporal extent of the low-salinity zone (LSZ), defined by salinity between 0.5 and 6 psu. X2, the distance up the axis of the estuary to the daily-averaged 2 psu near-bed salinity, and the spatial extent of the low-salinity zone were calculated for each day during the three-year simulation. The location, area, volume, and average depth of the lowsalinity zone varied with X2; however this variation was not monotonic and was largely controlled by bathymetric features. Predicted daily X2 values and the corresponding daily Delta outflow for each day during the threeyear simulation were used to develop a new equation to relate X2 to Delta outflow. This equation provides a conceptual improvement over previous equations by allowing the time constant for daily changes in X2 to vary with flow conditions. This improvement resulted in a smaller average error in X2 prediction than previous equations. These analyses demonstrate that a well-calibrated three-dimensional hydrodynamic model is a valuable tool for investigating the salinity distributions in the estuary and their influence on the distribution and abundance of physical habitat. © 2015 by the article author(s). Source

Chacon B.,Resource Management Associates Inc. | Faber B.A.,U.S. Army | DeGeorge J.F.,Resource Management Associates Inc. | Fleming M.J.,U.S. Army
World Environmental and Water Resources Congress 2014: Water Without Borders - Proceedings of the 2014 World Environmental and Water Resources Congress | Year: 2014

The Flood Risk Analysis (FRA) compute option is an enhancement to the Hydrologic Engineering Center's (HEC) Watershed Analysis Tool (HEC-WAT) that allows the user to perform risk analysis using a Monte Carlo simulation approach. Hydrologic inputs as well as parameters of the models in the HEC-WAT program sequence can be defined as random variables to represent uncertainty. In order to separately consider epistemic and aleatoric uncertainty (knowledge uncertainty and natural variability), the HEC-WAT sequence of programs is executed for a large random sample of flood events, which are clustered into realizations. Random variables with epistemic uncertainty vary from one realization to another, while variables driven by aleatoric uncertainty are re-sampled for every flood event in a realization. The Monte Carlo nature makes FRA simulations (with thousands of flood events) much more computationally intensive than deterministic HEC-WAT simulations, and so not all results from all models need to be saved nor even the programs/models executed for every randomly sampled flood event. Computation of an event can be aborted at any step of the program sequence according to user-defined criteria. Conversely, interesting events can be tagged so that detailed results are saved. Interesting results can be replicated, modified or analyzed in more detail. In order to achieve repeatability, random number generators throughout the FRA compute are seeded in a deterministic, pseudo-random hierarchical fashion. Monte Carlo iteration continues until the mean or a quantile of one or more userdefined variables chosen from the sequence of models converge within certain tolerance. At the back end of a simulation, statistical summaries are assembled by the Performance Metrics plug-in. Data is collected throughout a simulation to estimate variables of interest such as average annual damage, or annual exceedance probability. © 2014 American Society of Civil Engineers. Source

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