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Groundwater visual modflow is a 3-D modelling software. The model must be calibrated before running the simulation.
For manual calibration, an extensive set of built-in model calibration plotting utilities and statistical calculations help you properly evaluate the modeling results and interpret the calibration data. Comprehensive calibration plotting utilities and statistical summaries provide you with all the graphical interpretation tools you need to properly and thoroughly analyze the model calibration data.
Visual MODFLOW allows you to assign multi-level observation wells and group the observation points for isolated analysis of local model regions.
For each simulation Visual MODFLOW calculates the following calibration statistics:
~ Mean Error
~ Mean Absolute Error
~ Standard Error of the Estimate
~ Root Mean Error
~ Normalized Root Mean Error
These statistics can be calculated for all observations, or just for selected groups of observation points (as defined by the user).
The calibration plotting options provided include:
~ Scatter plot of calculated vs. observed data
~ Histogram of calibration residuals
~ Time-series plot of calculated and observed data
~ Time-series plot of calibration statistics
~ Bubble plot of calibration residuals
All plots can be exported to common image format (.BMP, .JPG, .TIF, .PNG), and the plot data can be exported to .ASCII for further analysis.
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Freeware PMWIN 5.3 download here.
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Rank: Newbie
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In groundwater modelling, the compilation or acquisition of hydraulic conductivity data is one of the first steps. Field measurements of hydraulic conductivity based on standard methods, slug test, packer tests or pumping tests can be used based on geological situations. Slug tests and packer tests are essentially point measurements, yielding hydraulic conductivity estimates for the area immediately around the test well screen. Pumping tests generally provide an average value for the area covered by the observation well array. However, the pumping test area may still represent only a small part of the region to be modelled. Whatever methods are used, the set of measured hydraulic conductivity values frequently covers a wide range, even when all measurements are taken in the same lithologic material and over a limited geographic area. This is critical steps in model development for accounting all heterogeneity in simulation.
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Groundwater models consist of a governing equation, boundary conditions and initial conditions. Boundary conditions are mathematical statements specifying the dependent variable (head) or the derivative of the dependent variable (flux) at the boundaries of the problem domain.
Proper selection of boundary conditions is a critical step in model design. In steady-state simulations, the boundaries largely determine the flow pattern. Boundary conditions influence transient solutions when the effects of the transient stress reach the boundary. In this case, the boundaries must be selected so that the simulated effect is realistic.
Physical boundaries of groundwater flow systems are formed by the physical presence of an impermeable body of rock or a large body of surface water. Other boundaries form as a result of hydrologic conditions. These invisible boundaries are hydraulic boundaries that include groundwater divides and streamlines.
Hydrogeologic boundaries are represented by the following three types of mathematical conditions:
1. Specified head boundaries for which head are given.
2. Specified flow boundaries for which the derivative of head (flux) across the boundary is given. A no-flow boundary condition is set by specifying flux to be zero.
3. Head-dependent flow boundaries for which flux across the boundary is calculated given a boundary head value. This type of boundary condition is sometimes called a mixed boundary condition because it relates boundary heads to boundary flows.
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The location of a boundary condition within the grid is dependent on whether a block-centered finite difference, mesh-centered finite difference, or finite element grid is used.
Before simulation, must be clear about the purpose of the modelling exercise.
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