![]() ![]() To other network flow monitoring protocols. (IETF) standard, although “netflow” is also now used as a general term to refer ![]() ![]() This comparative study shows the differences and uncertainties between two models as well as examines the implications of using them for long term model predictions.NetFlow is recognized as an Internet Engineering Task Force Results from data-calibrated CNM when compared to a corresponding calibrated DFN model shows that the CNM calibrates and adapts better than a DFN model with uniform fracture surfaces. It was observed that an optimal CNM connectivity map for channel conductance calibration can only be developed by jointly fitting flow rates, drawdowns and tracer mass recovery values. Semi-automated calibration of channel conductances to field characterization data (flow rates, drawdowns, and tracer recoveries) is performed using PEST algorithm. This study applies the principle of channel networks, implemented in the Pychan3d simulator, to analyze the hydraulic and tracer transport behavior in a 450-m-deep fractured granite system at the Äspö Hard Rock Laboratory in Sweden, where extensive site characterization data, including hydraulic and tracer test data are available. ![]() Discrete fracture network (DFN) models are widely used for such modeling while channel network models (CNM) provide an alternative representation, the latter focusing on the fact that flow and transport in deep fractured media often are dominated by a small number of long preferential flow paths. Uncertainties may arise both from the selection of the conceptual model as well as the estimation of the related model parameters. Performance assessment of nuclear waste disposal in deep crystalline bedrock demands a thorough understanding of the related flow and transport processes. ![]()
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