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Quality Modeling (quality + modeling)

Distribution by Scientific Domains

Engineering	66%

Selected Abstracts

WATER QUALITY MODELING OF ALTERNATIVE AGRICULTURAL SCENARIOS IN THE U.S. CORN BELT,

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 3 2002
Kellie B. Vaché
ABSTRACT: Simulated water quality resulting from three alternative future land-use scenarios for two agricultural watersheds in central Iowa was compared to water quality under current and historic land use/land cover to explore both the potential water quality impact of perpetuating current trends and potential benefits of major changes in agricultural practices in the U.S. Corn Belt. The Soil Water Assessment Tool (SWAT) was applied to evaluate the effect of management practices on surface water discharge and annual loads of sediment and nitrate in these watersheds. The agricultural practices comprising Scenario 1, which assumes perpetuation of current trends (conversion to conservation tillage, increase in farm size and land in production, use of currently-employed Best Management Practices (BMPs)) result in simulated increased export of nitrate and decreased export of sediment relative to the present. However, simulations indicate that the substantial changes in agricultural practices envisioned in Scenarios 2 and 3 (conversion to conservation tillage, strip intercropping, rotational grazing, conservation set-asides and greatly extended use of best management practices (BMPs) such as riparian buffers, engineered wetlands, grassed waterways, filter strips and field borders) could potentially reduce current loadings of sediment by 37 to 67 percent and nutrients by 54 to 75 percent. Results from the study indicate that major improvements in water quality in these agricultural watersheds could be achieved if such environmentally-targeted agricultural practices were employed. Traditional approaches to water quality improvement through application of traditional BMPs will result in little or no change in nutrient export and minor decreases in sediment export from Corn Belt watersheds. [source]

Quality modeling and analysis of polymer composite products

POLYMER COMPOSITES, Issue 4 2006
R.T. Durai Prabhakaran
The present article gives a new direction for quality modeling and analysis of polymer matrix composite products. Quality of composite products depends upon conformance of requirements of the customer. These requirements are translated into design specifications of all the contributing factors and subsystems up to component level of composite system. Quality of interaction amongst different subsystems, sub-subsystems, and other factors affects quality of products are also to be considered. Therefore, the present article considers quality of subsystems as well as quality of all interactions together and modeled using graph theory, matrix algebra as quality graph, quality matrix, and quality permanent function of the composite product. These models are useful to design quality of every subsystem and factors in such a manner that can lead to achieve six-sigma limits (almost zero error) i.e. 3.34 defects per million products produced. A number of analytical tests derived from these models help to carry out optimum selection of qualities of subsystems and interactions for designing competitive composite products. SWOT (strength,weakness,opportunities,threats) analysis integrated with these models becomes very powerful tool to convert an unsuccessful product into successful competitive product. Evaluation, ranking, and comparison procedures can be developed with the help of these proposed models. Coefficients of similarity and dissimilarity are developed for comparison among feasible products. Step-by-Step procedure based on systems approach is useful to designer, manufacturer at conceptual stage of design, and during manufacturing stages of composite products. This is basically a virtual prototyping methodology of complete system, leading to high quality competitive composite products. POLYM. COMPOS. 27:329,340, 2006. © 2006 Society of Plastics Engineers [source]

Incorporating variable source area hydrology into a curve-number-based watershed model

HYDROLOGICAL PROCESSES, Issue 25 2007
Elliot M. Schneiderman
Abstract Many water quality models use some form of the curve number (CN) equation developed by the Soil Conservation Service (SCS; U.S. Depart of Agriculture) to predict storm runoff from watersheds based on an infiltration-excess response to rainfall. However, in humid, well-vegetated areas with shallow soils, such as in the northeastern USA, the predominant runoff generating mechanism is saturation-excess on variable source areas (VSAs). We reconceptualized the SCS,CN equation for VSAs, and incorporated it into the General Watershed Loading Function (GWLF) model. The new version of GWLF, named the Variable Source Loading Function (VSLF) model, simulates the watershed runoff response to rainfall using the standard SCS,CN equation, but spatially distributes the runoff response according to a soil wetness index. We spatially validated VSLF runoff predictions and compared VSLF to GWLF for a subwatershed of the New York City Water Supply System. The spatial distribution of runoff from VSLF is more physically realistic than the estimates from GWLF. This has important consequences for water quality modeling, and for the use of models to evaluate and guide watershed management, because correctly predicting the coincidence of runoff generation and pollutant sources is critical to simulating non-point source (NPS) pollution transported by runoff. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Review of Urban Stormwater Quality Models: Deterministic, Stochastic, and Hybrid Approaches,

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 6 2007
Christopher C. Obropta
Abstract:, The growing impact of urban stormwater on surface-water quality has illuminated the need for more accurate modeling of stormwater pollution. Water quality based regulation and the movement towards integrated urban water management place a similar demand for improved stormwater quality model predictions. The physical, chemical, and biological processes that affect stormwater quality need to be better understood and simulated, while acknowledging the costs and benefits that such complex modeling entails. This paper reviews three approaches to stormwater quality modeling: deterministic, stochastic, and hybrid. Six deterministic, three stochastic, and three hybrid models are reviewed in detail. Hybrid approaches show strong potential for reducing stormwater quality model prediction error and uncertainty. Improved stormwater quality models will have wide ranging benefits for combined sewer overflow management, total maximum daily load development, best management practice design, land use change impact assessment, water quality trading, and integrated modeling. [source]

COMPARISON OF PROCESS-BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED,

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 3 2006
Puneet Srivastava
ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash-Sutcliffe coefficient of efficiency (E) and coefficient of determination (R2) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R2 were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ,0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds. [source]