General Module Function
The Krig_2D module models two-dimensional parameter distributions within domains defined by the convex hull of a data set, within a rectilinear domain with equally spaced nodes, or a technique called Adaptive Grid (This feature available only in EVS-PRO and MVS) which uses the convex hull option, and then subdivides individual elements to place a "kriged" node at the location of each input data sample. This guarantees that the output will accurately reflect the input at all measured locations (i.e. the maximum in the output will be the maximum of the input). This option is now the default gridding option. Krig_2D creates a layer of quadrilateral (4 node) elements in which each node is assigned the kriged parameter value, and optionally its associated kriging confidence level and uncertainty. Upon execution of the module, Krig_2D produces a new input data file with a synthetic boring at the location of maximum uncertainty calculated from the previous kriging estimates, which can then be rerun to find the next area of highest uncertainty. The naming of the "DrillGuide©" file which is created when Krig_2D is run with all types of chemistry files ends in csv1, csv2, csv3, etc. the output file name will be .csv2, csv3, csv4.... There are no limits to the number of cycles that may be run.
The use of Krig_2D to perform analytically guided site assessment is covered in detail in Workbook 2: DrillGuide© Analytically Guided Site Assessment.
This process can be continued as many times as desired to define the number and placement of additional borings that are needed to reduce the maximum uncertainty in the modeled domain to a user specified level. The features of Krig_2D make it particularly useful for optimizing the benefits obtained from environmental sampling or ore drilling programs. Krig_2D also provides some special data processing options that are unique to it, which allow it to extract 2-dimensional data sets from input data files that contain three-dimensional data. This functionality allows it to use the same .csv files as all of the other EVS input and kriging modules, and allows detailed analyses of property characteristics along 2-dimensional planes through the data set. Krig_2D also provides the user with options to magnify or distort the resulting grid by the kriged value of the property at each grid node. Krig_2D also allows the user to automatically clamp the data distribution to a specified level along a boundary that can be offset from the convex hull of the data domain by a user defined amount.
Module Input Ports
External Grid (Blue/Black): (Available only in MVS) This port allows a previously created grid to be imported into the module. All data will be kriged onto this grid and the input file will be ignored for gridding purposes.
Filename (Yellow/Blue/Yellow): This port allows for the sharing of filenames between related modules.
External Data (Blue/Black): (Available only in MVS) This port allows a previously created data field to be imported into the module. This data will be kriged onto the grid and the input file will be ignored for data purposes.
Module Output Ports
Filename (Yellow/Blue/Yellow): This port allows for the sharing of filenames between related modules.
Surface Output (Blue/Black): This port outputs a 2D data field that can be input to any of the Subsetting and Processing modules that have the same color input port.
Surf_Out (Red): This port outputs a geometry of the component surface which can be input directly to the viewer. Connecting the geometry port directly to the viewer allows use of the clamping functions in Krig_2D Data Processing to quickly investigate the distributions of components within the specified range.
When the Plot Semivariogram option is selected three additional output ports will appear as in the above figure.
Out2 (Red/Grey): This port outputs a geometry of the calculated semivariogram.
status_out (Blue-Green) : This port outputs a string that has the current status message from the module. This string is updated as the module runs.
VG_fld_out (Blue/Black): This port outputs a 3D data field representing the lines (semivariogram cloud pairs) and is provided primarily for connection to the axes module.
VG_scale_fact (Grey/Brown): This port is the Z_Scale of the semivariogram plot and is also provided primarily for connection to the axes module.
Module Status: Interruptible
This module's computational processes can be terminated (interrupted) using the "C Tech" icon in the Windows Notification Area (aka System Tray) in the lower right corner of your desktop. If you hover over the icon, it will tell you the status of the module and expected completion time. Double-Right-Clicking will terminate the process. Note that if you do stop any process, the output of the module is corrupted and any downstream module's results are not usable. You will need to re-run the module.
Module Control Panel
The control panel of Krig_2D is shown in the figure above.
The Read Data File button opens a File Browser which lists the *.csv;*.gwc; or*.geo files that are present in the current directory shown in the directory window. The format of .csv files is described in the csv_file_format help topic.
Note that this module will not begin running until a valid chemistry file has been selected, or a valid field containing data has been imported, and the Accept All Current Values button is pushed.
The Data Component slider allows the user to select which of the property values in the chemistry file will be kriged by execution of the module. The default value is -1, which results in kriging of all of the data components in the file during a single execution of the module.
The "Run" toggle controls whether the module will run when applications are loaded or data changes. When this is on, the module runs when applications are loaded or the "Accept" button is pushed (or the geology input changes). When it is off, the module will not run.
The "New-Reset Variables" toggle (on by default) resets all expert system calculated variables to zero before each run. This allows multiple calculations to be performed without tedious manual resetting of these variables. To change an expert system calculated variable, the toggle must be off.
Module Parameter Subpanels
Krig_2D has six subpanels which allow the user to set the parameters used for preprocessing the input data, producing the semivariogram, executing kriging, and post processing kriged output. Clicking on either the check boxes next to the subpanel names, or on the names themselves will bring up the subpanel parameter screens.
The Gridding Options subpanel is shown in the figure above. It is used to specify all parameters that affect the grid exported from Krig_2D. The availability of many options depends on whether geologic input is available or if the grid is created totally within Krig_2D. The window above shows the options with no geologic input. NOTE: If an external grid is imported into Krig_2D this panel will be blank.
The Minimum X, Maximum X, Minimum Y, and Maximum Y parameters allow the user to define the horizontal domain within the data set in which kriging of the parameter distribution will be completed. A value of 0 is the default for these parameters, which results in a model domain that is defined by the rectilinear bounds of the entire data set when the module is run. Krig_2D utilizes a model domain that is bounded by the limits of the data set, unless the user specifies a different domain by setting the Min and Max Values for X and Y. Utilizing the default extents effectively minimizes the extrapolation of parameters within the model to that area which is enclosed by the measured data points. If the user is uncertain of the X and Y limits of the data domain, the module should be run with the default 0 values, and upon completion of execution, the values in the X and Y input fields will be the min and max values of these parameters in the data set. The Stat CSV GEO module can also be used to investigate the limits and distribution of values in the input data set, and the statistics module can be used to output the distribution of values in the kriged model.
The X / Y Resolution parameters specify the number of grid nodes that will be included within the model domain. The number of grid elements along any axis of the model is simply the axis Resolution value minus one, as every element has two bounding nodes along an axis. The default value for the X and Y Res parameters is 51. However, the user can specify any number desired, up to the limit of available memory resources in the computer and run time limitations imposed by the patience of the user.
The Grid Type radio buttons (Rectilinear / Convex Hull) allows the user to select the type of domain in which the kriging will be completed. A convex hull boundary should be utilized when the user wishes to produce a model that can have irregular boundaries that are defined by the extent of the measured data points. The convex hull of a data set can be thought of as the domain that would be outlined by stretching a rubber band around the external data points in the data set. The convex adaptive grid (This feature available only in EVS PRO and MVS) is the same as the convex hull grid, except that the grid is automatically adapted to place grid nodes at all of the measured data points. The adaptive grid will result in a kriged parameter distribution that honors all of the measured data points exactly. This is the default domain used by Krig_2D. Utilizing a convex hull boundary effectively minimizes the extrapolation of parameters within the model to that area which is enclosed by the measured data points, or by the specified Boundary offset.
The Boundary Offset parameter sets the distance in user units that the grid coordinate range for the kriging domain will be set outside of the actual coordinate range of the data. This parameter allows the user to specify the distance outside of the actual data in which the parameter values will be extrapolated. A value for the Boundary Offset of 0 units, specifies that the true (not offset) convex hull of the data set will be used.
Coordinate Units - This field contains the default coordinate units for the grid, if no coordinate units are specified in the file being read, these units will be used.
The Data Processing parameters subpanel is shown in the figure above. It is divided into four groups: Preprocessing; Postprocessing; Artificial Boundary Clamping; and External Data to Krig.
It is important to note that all preprocessing actions are applied directly to the data in memory, and that the original data file is not altered. However, all of the functions within Krig_2D and the modules downstream of Krig_2D will be using the preprocessed (and kriged) parameter distribution. The user should refer back to the preprocessing subpanel when setting values for the filtering and display of the kriged data (i.e., to correctly specify whether the data has been log transformed, scaled, and/or clipped).
The Data Processing radio buttons allow the user to specify whether the data will be used as is, or will be processed to compute the log (base 10) of the parameter value before kriging. Note that if the log10 of the data is taken, a Clip Min value (which must be greater than 0) must be used to replace values in the data below the specified minimum value because the log function is undefined for values equal or less than zero.
The Data Scaling input field is used to specify a value by which all nodal data values will be multiplied before kriging. The default value is 1, but the user can specify any negative or positive value. This option is most commonly used to convert the units of the property being kriged, such as to convert concentrations in ppb to ppm or visa-versa. The user should bear in mind that any scaling of the data that is completed in Krig_2D will affect all downstream modules.
The number entered into the Pre-Clip Min input field will be used during preprocessing to replace any nodal property value that is less than the specified number. When log processing is being used, the value of Clip Min must be a positive, non-zero value. Generally, Clip Min should be set to a value that is one-half to one-tenth of the lowest detection limit in the data set, unless the user wishes to make the influence of not detected values stronger. As an example, if the lowest detection limit is 0.1 (which is present in the data set as a 0), and the user sets Clip Min to 0.0001, the clipped non-detected values forces three orders of magnitude to be present between any detected value and the non-detected values.
The number entered into the Pre-Clip Max input field will be used during preprocessing to replace any nodal property value that is greater than the specified number. The clipping values can be used to lessen the importance placed on extremes of the data, or outlier data values, before kriging. The preprocessing functions can be used in various ways to investigate the kriging confidence levels within specified ranges or limits of the data sets. An example of this type of analysis is provided in the Sample Networks section.
The LT Multiplier value affects any file value with a preceeding "<" character. It will multiply these values by the set value.
The Detection Limit value affects any file values set with the "ND" or other non-detect flags (for a list of these flags open the help for the CSV file format). When the module encounters this flag in the file it will insert the a value equal to (Detection Limit * LT Multiplier).
The 3D to 2D collapse method allows the user to extract data from within the interval specified in Min Z and Max Z using four different methods. It should be noted that if multiple samples occur at the exact same x, y, and z coordinates (duplicate samples), the average of these samples will be calculated first to provide a single data point for that coordinate, and then the extract method will be applied to other samples in the specified depth interval. If the Average radio button is selected, then Krig_2D will search the vertical interval in each boring and calculate the average of all the values found for input to the kriging analysis. If the Max radio button is selected (the default selection), then Krig_2D will extract the maximum property value that exists within the specified Z interval. When the Slice radio button is chosen, Krig_2D will look for the closest data point above the specified Min Z value, and the closest data point below the specified Min Z value, and calculate the average of these two points for input to the kriging analysis. The Slice Extract Method is provided as a convenient method for the user to assemble a 2-D data set that will contain at least one data point from each sampling location. If only one data point exists for a sampling location, then that value will be extracted for that location whether it is actually located above or below the specified Slice Position. If the Min radio button is selected, then Krig_2D will extract the minimum property value that exists within the specified Z interval.
The Tolerance parameter further extends the definition of coincident points. It allows all points within a +/- x-y box to be treated as coincident. This is not the same a true euclidean distance, since two points which were different in both x and y by 0.9999 would be considered coincident if the tolerance were 1, even though the true distance between the points was over 1.4 (square root of the sum of the squares).
Postprocessing of the data from Krig_3D affects the calculation of the kriging confidence and uncertainty estimates that are produced by the model, and allows the user to apply a filter for the data passed to all modules downstream of Krig_2D. Note that the postprocessing does not affect any of the other Semivariogram or kriging algorithms that execute in Krig_2D, so the user can experiment with different values of postprocessing parameters to obtain the type of display desired, independent of the internal kriging process.
The Post-Clip Min parameter specifies the smallest nodal value that will be present in the data field output by Krig_2D. This parameter is useful for limiting or enhancing the effects of not detected values or outliers in a data set, and for optimizing the use of the dynamic color range used to represent the property distribution. Clip Min has a default value of 0.001, but can be set to any negative or positive value with magnitude from -1.0 E09 to 1.0 E09. In general, good results are obtained by setting this value to the lowest property value or detection limit in the input data set. It is important to note that because not detected values are represented in the .csv file as zeros, the Clip Min value can be used to strengthen the influence of small values or non-detects that are present in the data set. As an example, if the detection limit for a certain chemical analysis is 0.1 (which is entered into the .csv file as 0), and the Clip Min is set to 0.0001, then this not detected value will have an effective influence on the kriged distribution near this data point that is three orders of magnitude stronger than the actual detection limit. The user should bear in mind that if mass or volume estimates are being made in the analysis, the Clip Min value could affect the estimates if considerable data are present that are being clipped. For volume estimates, if the specified lower bound of the concentrations of interest is well above the Clip Min value, then their will be no effects on the results. If the specified lower bound of concentrations for the volume estimate is lower than Clip Min, then the clipping will truncate the volume at the Clip Min value, and the estimated volume will be from the entire model domain.
The Post-Clip Max parameter specifies the largest nodal value that will be present in the data field output by Krig_2D. Again this parameter can be used to optimize the use of the dynamic color range when a data set has a few extremely high values, but the user is most interested in seeing the detailed changes in the distribution in some lower range of the data. It can also be used to investigate the kriging confidence or uncertainty levels near certain threshold values of a property. As an example, if the regulatory threshold for a parameter is 10 units, then the Clip Max parameter can be set to 10, and all kriged values greater than 10 will have the same strength in the calculation of the uncertainty levels in the kriged distribution. Clip Max has a default value of 1,000,000, but can be set to any negative or positive value with magnitude form -1.00E09 to 1.00E09.
Artificial Boundary Clamping creates a ring of artificial points outside the grid coordinate range to control how extrapolation is done outside of the data set. The artificial points are not used in the production of the semivariogram.
The Offset Boundary parameter specifies the distance outside of the coordinate range of the data set that a boundary (or ring) of synthetic data points, which have property values that are equivalent to the specified Preprocessing Clip Min, will be automatically generated for kriging.
The Point Spacing parameter sets the linear distance along this clamp boundary at which the synthetic data points will be placed. The default value for Offset Boundary is -1.0, which specifies that no clamping boundary should be used. The user can set this value to any distance in user units that is within the kriging Reach distance specified, to modify how sharply the kriged data distribution will transition to the clamped value. The default Point Spacing parameter value is 0.0, which specifies that no points will be placed along the clamp boundary. Again, the user can input any value in user units that will provide the desired modeled data distribution.
The user should be aware that the synthetic data points do not affect the kriging semivariogram production, but they do affect the kriging confidence and uncertainty values that are output by Krig_2D, as they are considered by the kriging algorithms to be real data points. Therefore, a clamping boundary should not be used when confidence or uncertainty values are of importance to the analysis. The clamping boundary is provided primarily as a display control tool, and will produce a very even and regular synthetic boundary along the outside of the data domain.
When external data is being imported into the module the External Data to Krig window becomes active. This window allows the user to select which data components to krige by switching on or off the toggles associated with that data component. The Automatically exponentiate log data toggle will detect if the data being imported has been log processed and if it has exponentiate it. This avoids double log processing the data with the Preprocessing option.
(EVS PRO and MVS Only)
This panel is for chemistry files (*.csv, *.gwc) that are set up as time domain files (i.e. one analyte whose values are recorded over time).
The Chem. File is Time Domain toggle turns on date interpolation for time domain chemistry files.
The Specify Date by Component toggle will cause the module to ignore the set Date for Interpolation and instead use the component slider to select the date
The Date for Interpolation field is the date being interpolated to, for example if you have an analyte value of 2 on 1/01/05 and a value of 4 on 1/03/05 and the date is set to 1/02/05 with Direct Interpolation the value should be set to 3. The Date can be either set by hand or imported. This makes the module useful in a time_loop.
In time domain files there is no place to set either the analyte name that has been kriged over time or the analyte units; these can be set in the Analyte Name and Analyte Units fields.
There are 5 different Interpolation methods that are available, each interpolation method is used to define how to interpolate when given unsampled times in a file.
Direct Interpolation Only: This is the most basic interpolation method, and the most accurate in terms of representing the data as it has been entered. This method looks at the two dates surrounding the input Date. If either date is unsampled, the value for that sample will remain unsampled and no interpolation will occur. If both dates have sampled values it will interpolate between them.
Interpolate Only: This method will look at the two dates surrounding the input Date. If the date before the input Date is an unsampled date it will continue to look backwards through each time column until it finds a sampled date.. If the date after the input Date is unsampled it will look forward through the time columns until it finds a sampled date. If either search fails to find a useable dates then it will set the value for that time to a unsampled value. Else it will interpolate between the two found dates. This is useful for files that have a small amount of unsampled values.
Interpolate and Extrapolate Beyond: This method will look at the two dates surrounding the input Date. If the date before the input Date is an unsampled date it will continue to look backwards through each time column until it finds a sampled date. If the date after the input Date is unsampled it will look forward through the time columns until it finds a sampled date. If it does not find a sampled date after the input Date, it will extrapolate beyond the last useable date to the input Date.
Interpolate and Extrapolate: This method will look at the two dates surrounding the input Date. If the date before the input Date is an unsampled date it will continue to look backwards through each time column until it finds a sampled date. If it fails to find one it will extrapolate the first value backwards to the input Date. If the date after the input Date is unsampled it will look forward through the time columns until it finds a sampled date. It will also extrapolate beyond the last valid date in the file.
Interpolate (Use with Shrink): This method uses the same interpolation algorithm as method one, but should be used for clarity when there is a post_samples or STAT_CSV_GEO module in the network that is using the Interpolate and Shrink to Unsampled option.
The Create TCF File toggle will cause the Krig_2D module to run in a loop, going through each component and creating an EFB file at that time. These EFB files will be linked together in the specified TCF file and can be used with the Read_TCF module for animation purposes. NOTE: This function will not work unless a TCF name is selected as well.
Kriging Parameters
The Kriging Parameters subpanel of Krig_2D is shown in the figure above.
Note: The "new" toggle on the main panel (on by default) resets all expert system calculated variables to zero before each run. This allows multiple calculations to be performed without tedious manual resetting of these variables. To change an expert system calculated variable, the toggle must be off.
The Interpolation Method radio buttons determine the type of statistical information which will be included in the nodal data components output from Krig_2D or to select IDW vs. kriging.
If Statistics is chosen, Each Concentration (for every chemical in the .csv file) will have a corresponding Confidence (based on the Confidence Bound parameter) and Uncertainty. The display when Statistics is selected and the data is log processed is shown above.
The display when Statistics is selected and the data is NOT log processed is shown below. In this case, the confidence bound is a tolerance vs. a factor.
If Min-Max Plume is chosen (This feature available only in EVS PRO and MVS) three different Concentration components will be calculated, the Nominal, Minimum and Maximum. These different distributions are determined based on the standard deviation and nominal concentration at each node based on the Confidence parameter which is expressed in percent (nominally 60%). Note that at a "confidence" of 50%, the nominal, minimum and maximum concentrations are identical.
If either Inverse Distance Weighted (IDW) estimation method (Shepard and Franke/Nielson) is selected, kriging is not performed and one of these algorithms is used as an alternative to kriging in Krig_2D. This also affects the available parameters as show in the figure below:
The Semivariogram Parameters toggle opens the Semivariogram Parameters subpanel.
The Semivariogram Parameters subpanel is shown in the figure above.
The Pair Search Range specifies the radial distance from any input data point that will be searched to assemble the data pairs that are used in the variance analysis. Clicking in the window and using standard windows style editing procedures changes the values in the data windows. The default value for the pair search range is set to 0, which if left alone, results in the value being set to approximately 2/3 of the largest distance between data points in the data set. The user must consider the spatial characteristics of the data set when setting or revising the default calculated Pair Search Range. If large areas exist in the data domain that do not have data points within them, the user must set the Pair Search Range to a value that will allow a pair of data points to be identified, if these outlying data are going to affect the characteristics of the semivariogram. Data sets with large variations over short distances can be modeled most accurately using smaller pair search ranges, as this effectively limits the distance over which the semivariogram will search for and include data points. If a large number of data points exists in the data set which are in close proximity to each other, the user should set the pair search range to the shortest distance that will allow trends in the data to be included in the semivariogram production.
The semivariogram pair search range is an important factor in the execution time required for calculating the semivariogram, as the number of data pairs to be considered is on the order of n squared, for n data samples. However, including a greater number of data pairs in the semivariogram analysis will generally produce kriged distributions that more accurately represent trends and other larger scale characteristics of the data set. If a large data set is being kriged using a large Pair Search Range, the number of pairs the best-fit variogramming procedure must consider also gets very large. EVS implements a deterministic random pair selection algorithm to limit the total number of pairs that are considered in the semivariogram production when the number of potential pairs exceeds 50,000. This algorithm speeds execution and allows the user to input very large data sets. The flexibility of EVS's modular design allows the user to experiment with different search ranges (preferably starting small and getting larger), to obtain the desired results with reasonable execution times.
The Semivariogram Symmetry parameter describes the degree to which EVS's expert system is allowed to distort the geometry of the semivariogram in calculating the best fit to the data. The valid range for this parameter is from 0 to 1. The default value is 1, which forces the semivariogram to be symmetrical in all axes of the data set. Symmetrical variograms run the fastest in EVS, and give reasonable results for many data sets. Unless the data being kriged shows a very high degree of asymmetry, good results are generally obtained by setting this parameter to a value between 0.5 and 1. When utilizing symmetry values less than 0.5, the user should post the original data set and examine areas of the resulting model in which only sparse data are available to fully understand the effects of the asymmetric model semivariogram.
The XY Minimum Range parameter defines the smallest distance in the XY plane at which the semivariogram procedure can set the sill of the semivariogram. In essence, this parameter constrains the minimum distance between data points beyond which EVS's best fit algorithms will consider all points to have an equal and minimum influence on the kriged model node value. The default value for the Minimum Range is 0, which allows the best fit procedure to calculate the range that produces the best fit to the data. The valid range for this parameter can be any number up to the largest distance between points in the data set. However it is generally not meaningful to set the minimum range to values less than approximately five times the shortest distance between data points. When this value is changed from 0, the user should check the calculated range to see if the specified value constrained the semivariogram production, which is indicated when the calculated range is set to the specified value (the output of the semivariogram and kriging procedures is displayed in the console window). If so, the user may want to experiment with different range values, or allow the default value to be used, and compare the kriged results.
The Z Minimum Range parameter defines the smallest distance in the Z axis of the data at which the semivariogram procedure can set the sill of the semivariogram. This parameter is similar to the XY Minimum Range in function, and the same considerations apply.
The user can now set the semivariogram by checking the Set Semivariogram toggle. This feature is useful for incorporating a semivariogram that was not calculated with the expert system. Type in boxes are supplied for Major Axis Rotation, Major Range, Sill, and Minor Range. Rotation angle requires an angle measured in degrees from East (equals 0) in a counterclockwise direction. The Major Range refers to the long axis of anisotropy (if any) and the Minor Range refers to the perpendicular of that axis. Note that both ranges refer strictly to the horizontal direction.
The Plot Semivariogram toggle causes a plot to be generated showing the semivariogram that has been selected and how the semivariogram surface fits to the data pair’s semivariance cloud. What is plotted is one-half of the square of the differences vs. the vector distance between the pairs. This is referred to as the semi-variance cloud. The total length of lines above the surface and below should be equal. However in general, the population of points below the surface will be greater (since there will be some large, squared differences balancing). The Z_Scale parameter has a default value of NULL, but a reasonable default value will be automatically computed based on the maximum semivariance and the variogram Pair Search Range.
When the Square Plot (vs. round) toggle is OFF, the semivariogram surface will be round. Additional information on this subject is in the Variograms chapter of the Geostatistics Workbook.
The Reach input field defines the radial distance (in user units) from any given model node that the kriging module will look for data points to be included in the estimation of the model parameter at that node. The default value of reach is 0, which results in the module calculating a reach value which is approximately two-thirds of the longest distance between any two data points in the data set.
The Points parameter defines the maximum number of data points (within the specified reach) that will be considered for the parameter estimation at a model node. The default value for points is 20, which generally provides reasonably smooth modeled parameter distributions. The effects of decreasing and increasing the values for reach and points on the model output are somewhat similar, but for different reasons. If the data have a fairly even spatial distribution throughout the domain, then increasing these values will generally include more of the input data points that will be used to krige the value for a given model node, and thus will result in smoother modeled data distributions. Decreasing the values of reach and points (in an evenly distributed data set) results in fewer input data points being used to calculate the parameter estimates at a given model node, and result in modeled distributions with greater variations across smaller areas.
The user should consider both the spatial distribution and the range of values in the input data set when deciding upon values for the reach and points parameters. If the specified reach is too small to allow the kriging module to locate at least one point within the search area, then no kriging can be performed and the module will terminate with an error message to the Status Console.
If the user specifies a large number of points (that are within the specified reach), then the output will be smoother, but the execution time for the kriging can increase significantly. By posting the input data using the post_samples module, and looking at the characteristics of the resulting kriged data using the statistics module, the user can quickly analyze the characteristics and distribution of the kriging output for a given set of parameters, and test the effects of changing the kriging parameter values.
The Quad Search toggle changes the method by which data sample points are selected for inclusion in the kriging matrix. If this is on, the "Points" parameter switches to "Max Points in Quad". Searching is performed for each of the quadrilaterals surrounding the point to be kriged. Within each quadrilateral a maximum number of points (up to one-fourth of the total points) are selected. Then, points are taken sequentially from each quadrilateral up to the maximum number of total points or until all octant’s points have been used. The panel display changes when this option is selected as shown above. Quad Search is applicable for the Statistics and Min-Max Plume kriging modes.
The type-in value for Use all data if number of samples is under is off by default, but this option gives the smoothest surfaces since all data is used for the kriging process. Sometimes using all points results in faster computation since only one (large) kriging matrix must be solved.
The Confidence Bound parameter is used to specify what interval around the kriged model estimates the kriging confidence or uncertainty will apply to. The default value is 10, which essentially produces the confidence and uncertainty that the kriged data are within one order of magnitude of the "true" value. As an example, if the Confidence Bound is 10, the kriged property value at a node is 5, and the kriged confidence level at the node is 0.9, then 90% of the time, the "true" value of the kriged property at that node will be in the range of from 0.5 to 50 units. Additional discussions of confidence and uncertainty are provided in the Sample Networks.
The Display Settings window is shown in the image above. This window controls the display of the uncertainty sphere location. By default there is one uncertainty sphere for every analyte. The visibility of the spheres can be toggled on and off by click on the check box next to the name of the analyte. These spheres can also be vertically exaggerated to match any downstream scaling of the field itself.
The DrillGuide© panel is shown above. When the Run Drill Guide toggle is selected Krig_2D will run in a loop creating a synthetic boring at the maximum uncertainty location until it has reached the set # of synthetic samples.
The Boring Samples field indicates how many samples create at each synthetic boring that is created.
The Target Concentration at Isolevel toggle, when selected, changes the location of the uncertainty sphere based upon the specified target concentration.
The Condense Output toggle, when selected, will minimize the number of strings displayed in the EVS console window.
The User-Defined Synthetic Samples slider is used to add points to the grid for drill guide purposes. The purpose of this slider is to help eliminate areas of high uncertainty that cannot be drilled, for example under a building.
Krig_2D Module Hints
Manually adjusting kriging and semivariogram parameters
The user must un-check the new toggle in the main window in order to make manual adjustments to most parameters in this module. Otherwise the values will be calculated by EVS according to the spatial extents or distribution of the data.
When using the set semivariogram option, all other semivariogram parameters are ignored. But to go back to the expert system parameters the user must make all type-ins 0,00 (in set semivariogram), then check the new toggle on the main Krig_2D panel.