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Application Of An Artificial Neural Network For Analysis Of Subsurface Contamination At The Schuyler Falls Landfill, Ny, Lance E. Besaw, Donna M. Rizzo, P. J. Mouser
Application Of An Artificial Neural Network For Analysis Of Subsurface Contamination At The Schuyler Falls Landfill, Ny, Lance E. Besaw, Donna M. Rizzo, P. J. Mouser
International Congress on Environmental Modelling and Software
Current subsurface site characterization, plume delineation, remediation designs and monitoring network designs that rely on a limited, albeit large, number of sparsely collected data, tend to be expensive, cumbersome and frequently inadequate for solving multi-objective, long-term environmental management problems. We present a subsurface characterization methodology that integrates multiple types of data using a modified counterpropagation artificial neural network (ANN) to provide parameter estimates and delineate groundwater contamination at a leaking landfill. Apparent conductivity survey data and hydrochemistry data (i.e. heavy metals, BOD5,20, chloride concentration, etc.) are used to estimate the extent of subsurface contamination at the Schuyler Falls Landfill, located …
Application Of An Artificial Neural Network For Analysis Of Subsurface Contamination At The Schuyler Falls Landfill, Ny, Lance E. Besaw, Donna M. Rizzo, P. J. Mouser
Application Of An Artificial Neural Network For Analysis Of Subsurface Contamination At The Schuyler Falls Landfill, Ny, Lance E. Besaw, Donna M. Rizzo, P. J. Mouser
International Congress on Environmental Modelling and Software
Current subsurface site characterization, plume delineation, remediation designs and monitoring network designs that rely on a limited, albeit large, number of sparsely collected data, tend to be expensive, cumbersome and frequently inadequate for solving multi-objective, long-term environmental management problems. We present a subsurface characterization methodology that integrates multiple types of data using a modified counterpropagation artificial neural network (ANN) to provide parameter estimates and delineate groundwater contamination at a leaking landfill. Apparent conductivity survey data and hydrochemistry data (i.e. heavy metals, BOD5,20, chloride concentration, etc.) are used to estimate the extent of subsurface contamination at the Schuyler Falls Landfill, located …
Kriging Of Groundwater Levels – A Case Study
Kriging Of Groundwater Levels – A Case Study
Journal of Spatial Hydrology
In this paper, application of the spatial statistical technique, kriging, for the spatial analysis of groundwater levels is shown. The data set consists of groundwater levels measured at about 60 points (the number of points vary from year to year) twice in a year (June and September) for six years (1985-1990) in an area of 2100 sq km in part of the canal command area of Indira Gandhi Nahar Pariyojana (IGNP) in Rajasthan, India. With the use of measured elevations of the water table, experimental semivariograms were constructed that characterises the spatial variability of the measured groundwater levels. Spherical, exponential …
Estimation Of Aquifer Transmissivity Using Kriging, Artificial Neural Network, And Neuro-Fuzzy Models
Journal of Spatial Hydrology
In interpolation of groundwater properties such as transmissivity, due to the unknown distributed values of the variables and heterogenity, the best and the unbiased aspects are frequently difficult to obtain. Therefore, applying a modern technique is necessary to obtain a real estimation of transmissivity. To gain the transmissivity values as an input data in groundwater modelling, the ordinary log kriging method has been used. In this study, the efficiency of the Adaptive Network based Fuzzy Inference System (ANFIS), artificial neural networks and ordinary kriging are investigated for interpolation of transmissivity in an unconfined aquifer. The results indicate that ANFIS model …
Spatial Distribution, Temporal Stability, And Yield Loss Estimates For Annual Grasses And Common Ragweed (Ambrosia Artimisiifolia) In A Corn/Soybean Production Field Over Nine Years, Sharon A. Clay, Bruce Kreutner, David E. Clay, Cheryl Reese, Jonathan Kleinjan, Frank Forcella
Spatial Distribution, Temporal Stability, And Yield Loss Estimates For Annual Grasses And Common Ragweed (Ambrosia Artimisiifolia) In A Corn/Soybean Production Field Over Nine Years, Sharon A. Clay, Bruce Kreutner, David E. Clay, Cheryl Reese, Jonathan Kleinjan, Frank Forcella
Agronomy, Horticulture and Plant Science Faculty Publications
Weeds generally occur in patches in production fields. Are these patches spatially and temporally stable? Do management recommendations change on the basis of these data? The population density and location of annual grass weeds and common ragweed were examined in a 65-ha corn/soybean production field from 1995 to 2004. Yearly treatment recommendations were developed from field means, medians, and kriging grid cell densities, using the hyperbolic yield loss (YL) equation and published incremental YL values (I ), maximum YL values (A), and YL limits of 5, 10, or 15%. Mean plant densities ranged from 12 to 131 annual grasses m22 …