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Riparian vegetation provides many noteworthy functions in river and floodplain systems, including its influence on hydrodynamic processes. Traditional methods for predicting hydrodynamic characteristics in the presence of vegetation involve the application of static Manning's roughness, which does not directly account for vegetation characteristics and neglects changes in roughness due to local water depth and velocity. The objectives of this study were to (1) implement numerical routines for simulating vegetation‐induced hydraulic roughness in a two‐dimensional (2D) hydrodynamic model; (2) evaluate the performance of two vegetation roughness approaches; and (3) compare vegetation parameters and hydrodynamic model results based on field‐based and remote sensing acquisition methods. Two roughness algorithms were coupled to an existing 2D hydraulic solver, which requires vegetation parameters to calculate spatially distributed roughness coefficients. Vegetation parameters were determined by field survey and using airborne light detection and ranging (LiDAR) data for San Joaquin River, California, USA. Water surface elevations modeled using vegetation‐based roughness approaches produced an acceptable overall performance, but the results were sensitive to the vegetation parameterization method (field based vs. LiDAR). Spatial variations in roughness and hydraulic conditions (water depth and velocity) were observed based on vegetation species and discharges for vegetation‐based approaches. The proposed approach accounts for the complexities of the physical environment instead of relying on traditional roughness as model inputs. Thus, the method proposed here is beneficial for describing the hydraulic conditions for the area having spatial variation of vegetation (e.g., species and density). However, additional research is needed to quantify model performance with respect to spatially distributed water depth and velocity and parameterization of vegetation characteristics. [ABSTRACT FROM AUTHOR]

This study investigates the ability of fuzzy genetic (FG) approach in modeling of reference evapotranspiration (ET0). The daily climatic data, solar radiation, air temperature, relative humidity, and wind speed from three stations, Windsor, Oakville and Santa Rosa, in central California, are used as inputs to the FG models to estimate ET0 obtained using the FAO-56 Penman-Monteith equation. A comparison is made between the estimates provided by the FG and those of the following empirical models: the California Irrigation Management System Penman, Hargreaves, Ritchie, and Turc methods. The FG results are also compared with the artificial neural networks. Root-mean-square errors (RMSE), mean-absolute errors (MAE), and correlation coefficient statistics are used as comparing criteria for the evaluation of the models’ performances. The comparison results reveal that the FG models are superior to the ANN and empirical models in modeling ET0 process. For the Windsor, Oakville, and Santa Rosa stations, it was found that the FG models with RMSEW=0.138, MAEW=0.098, and RW=0.999; RMSEO=0.144, MAEO=0.102, and RO=0.999; and RMSES=0.167, MAES=0.115, and RS=0.998 in test period is superior in modeling daily ET0 than the other models, respectively. [ABSTRACT FROM AUTHOR]

Abstract: A mathematical model has been developed/updated to simulate the steady state and transient thermal-hydraulics of the International Thermonuclear Experimental Reactor (ITER) divertor module. The model predicts the thermal response of the armour coating, divertor plate structural materials and coolant channels. The selected heat transfer correlations cover all operating conditions of ITER under both normal and off-normal situations. The model also accounts for the melting, vaporization, and solidification of the armour material. The developed model is to provide a quick benchmark of the HEIGHTS multidimensional comprehensive simulation package. The present model divides the coolant channels into a specified axial regions and the divertor plate into a specified radial zones, then a two-dimensional heat conduction calculation is created to predict the temperature distribution for both steady and transient states. The model is benchmarked against experimental data performed at Sandia National Laboratory for both bare and swirl tape coolant channel mockups. The results show very good agreements with the data for steady and transient states. The model is then used to predict the thermal behavior of the ITER plasma facing and structural materials due to plasma instability event where 60MJ/m2 plasma energy is deposited over 500ms. The results for ITER divertor response is analyzed and compared with HEIGHTS results. [Copyright &y& Elsevier]

Abstract  Groundwater pumping has led to extensive water-level declines and seawater intrusion in coastal Los Angeles, California (USA). A SUTRA-based solute-transport model was developed to test the hydraulic implications of a sequence-stratigraphic model of the Dominguez Gap area and to assess the effects of water-management scenarios. The model is two-dimensional, vertical and follows an approximate flow line extending from the Pacific Ocean through the Dominguez Gap area. Results indicate that a newly identified fault system can provide a pathway for transport of seawater and that a stratigraphic boundary located between the Bent Spring and Upper Wilmington sequences may control the vertical movement of seawater. Three 50-year water-management scenarios were considered: (1) no change in water-management practices; (2) installation of a slurry wall; and (3) raising inland water levels to 7.6 m above sea level. Scenario 3 was the most effective by reversing seawater intrusion. The effects of an instantaneous 1-m sea-level rise were also tested using water-management scenarios 1 and 3. Results from two 100-year simulations indicate that a 1-m sea-level rise may accelerate seawater intrusion for scenario 1; however, scenario 3 remains effective for controlling seawater intrusion. [ABSTRACT FROM AUTHOR]

The Storm Water Management Model was adapted and calibrated to the Ballona Creek Watershed, a large urban catchment in Southern California. A geographic information system (GIS) was used to process the input data and generate the spatial distribution of precipitation. An optimization procedure using the complex method was incorporated to estimate runoff parameters, and ten storms were used for calibration and validation. The calibrated model predicted the observed outputs with reasonable accuracy. A sensitivity analysis showed the impact of the model parameters, and results were most sensitive to imperviousness and impervious depression storage and least sensitive to Manning roughness for surface flow. Optimized imperviousness was greater than imperviousness predicted from land-use information. The results demonstrate that this methodology of integrating GIS and stormwater model with a constrained optimization technique can be applied to large watersheds. [ABSTRACT FROM AUTHOR]

Evaluation of flood risk in an interior watershed (one protected from flooding by a levee) requires application of watershed, channel, statistical, and economic models in an integrated, coordinated manner. The Strong Ranch Slough and Chicken Ranch Slough watershed in Sacramento, California is such a watershed. We describe herein how we used standard-of-practice models within a coincident-frequency analysis framework to evaluate existing flood damage potential and flood damage potential with a variety of proposed damage-reduction measures. [ABSTRACT FROM AUTHOR]

As a part of a study examining alternatives for flow augmentation for fall run Chinook salmon migration on the Cosumnes River, California, two models were constructed to simulate channel flow combined with seepage losses. The first model is a numerical, one-dimensional diffusion wave approximation of the St. Venant equations coupled to a seepage routine that uses either a Green and Ampt infiltration routine or a head-based seepage routine that can handle seepage to or from the channel. The second model uses an analytical solution to the diffusion wave approximation of the St. Venant equations and also incorporates the Green and Ampt method to represent losses due to seepage for the simulation of flow over a dry riverbed. The two models are used to simulate low flow periods in the Michigan Bar to McConnell reach of the Cosumnes River in order to determine flows associated with a minimum depth necessary for fall run Chinook salmon migration. These computed flows were compared against historical data in order to determine volumes of flow augmentation for the time period October through December which corresponds to the spawning period of fall run Chinook salmon. Computed flow augmentation volumes were compared with available reservoir storage in the watershed in order to determine if such flow augmentation would be possible. Both models proved capable of simulating low flow periods on the Cosumnes River. During dry years, the computed flow augmentation volumes represent a significant percentage of the available reservoir storage, indicating that augmentation flows may not always be possible for the entire time period from this source alone. [ABSTRACT FROM AUTHOR]