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The present study focuses on the unexplored area of application of artificial neural network in groundwater hydrology. Three models, each based on artificial neural networks, are applied for predictio...
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 t...
The present study focuses on the unexplored area of application of artificial neural network in groundwater hydrology. Three models, each based on artificial neural networks, are applied for predictio...
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 t...
Statistical analysis of pumping-test data from wells have been used to calculate average values of transmissivity and permeability in different Swedish rocks. The influence of the well-loss on the c...
The 3 basic data types of contaminant hydrology are examined by stochastic modelling of a groundwater contamination case. The stochastic transport model, which is of the Monte Carlo type, uses a num...
The log-transmissivity may in many cases be predicted from the log-transformed specific capacity of wells by applying a linear statistical model. The coefficients of the linear equation can be estim...
Two physically based models are derived that can be used to predict the log-transmissivity from the lithology, e.g. as logged in boreholes. The first model uses the lithology as the only predictor, wh...
Fluid transmissivity (layer thickness times permeability) and electric transverse resistance (layer thickness time resistivity) are important parameter in groundwater and hydrocarbon exploration. Dete...
Biomass burning activities emit high concentrations of aerosol particles to the atmosphere. Such particles can interact with solar radiation, decreasing the amount of light reaching the surface and in...

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