This tool combines the function of the "Stream Drop Analysis" tool and the "Stream Definition by Threshold" tool. It applies a series of thresholds (determined from the input parameters) to the input accumulated stream source grid (*ssa) grid and outputs the results in the stream drop statistics table (*drp.txt). Then it outputs a stream raster grid, which is an indicator (1,0) grid of stream cells. Stream cells are defined as those cells where the accumulated stream source value is >= the optimal threshold as determined from the stream drop statistics. There is an option to include a mask input to replicate the functionality for using the *sca file as an edge contamination mask. The threshold logic should be: src = ((ssa >= thresh) & (mask >=0)) ? 1:0
There is no usage for this tool.
StreamDefWithDropAnalysis
(Input_Pit_Filled_Elevation_Grid, Input_D8_Flow_Direction_Grid,
Input_D8_Contributing_Area_Grid, Input_Accumulated_Stream_Source_Grid,
Input_Outlets, {Input_Mask_Grid}, Minimum_Threshold_Value,
Maximum_Threshold_Value, Number_of_Threshold_Values,
Use_logarithmic_spacing_for_threshold_values, Input_Number_of_Processes,
Output_Drop_Analysis_Text_File, Output_Stream_Raster_Grid)
Parameter | Explanation | Data Type |
---|---|---|
Input_Pit_Filled_Elevation_Grid | Dialog
Reference This input is a grid of elevation values. As a general rule, it is recommended that you use a grid of elevation values that have had the pits removed for this input. Pits are generally taken to be artifacts that interfere with the analysis of flow across them. This grid can be obtained as the output of the "Pit Remove" tool, in which case it contains elevation values where the pits have been filled to the point where they just drain. There is no python reference for this parameter. |
Raster Layer |
Input_D8_Flow_Direction_Grid | Dialog
Reference A grid of D8 flow directions which are defined, for each cell, as the direction of the one of its eight adjacent or diagonal neighbors with the steepest downward slope. There is no python reference for this parameter. |
Raster Layer |
Input_D8_Contributing_Area_Grid | Dialog
Reference A grid of contributing area values for each cell that were calculated using the D8 algorithm. The contributing area for a cell is the sum of its own contribution plus the contribution from all upslope neighbors that drain to it, measured as a number of cells or the sum of weight loadings. This grid can be obtained as the output of the "D8 Contributing Area" tool. In this tool, it is the contributing area (A) that is compared in the formula A > ML^y to determine the transition to a stream. There is no python reference for this parameter. |
Raster Layer |
Input_Accumulated_Stream_Source_Grid | Dialog
Reference This grid nominally accumulates some characteristic or combination of characteristics of the watershed. The exact characteristic(s) varies depending on the stream network raster algorithm being used. This grid needs to have the property that grid cell values are monotonically increasing downslope along D8 flow directions, so that the resulting stream network is continuous. While this grid is often from an accumulation, other sources such as a maximum upslope function will also produce a suitable grid. There is no python reference for this parameter. |
Raster Layer |
Input_Outlets | Dialog
Reference A point feature defining the outlets of interest. If this input file is used, only the cells upslope of these outlet cells are considered to be within the domain being evaluated. There is no python reference for this parameter. |
Feature Layer |
Input_Mask_Grid (Optional) | Dialog
Reference This optional input is a grid that is used to mask the domain of interest and output is only provided where this grid is >= 0. A common use of this input is to use a D-Infinity contributing area grid as the mask so that the delineated stream network is constrained to areas where D-infinity contributing area is available, replicating the functionality of an edge contamination mask. There is no python reference for this parameter. |
Raster Layer |
Minimum_Threshold_Value | Dialog
Reference This parameter is the lowest end of the range searched for possible threshold values using drop analysis. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis see Tarboton et al. (1991, 1992), Tarboton and Ames (2001). There is no python reference for this parameter. |
Double |
Maximum_Threshold_Value | Dialog
Reference This parameter is the highest end of the range searched for possible threshold values using drop analysis. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis see Tarboton et al. (1991, 1992), Tarboton and Ames (2001). There is no python reference for this parameter. |
Double |
Number_of_Threshold_Values | Dialog
Reference The parameter is the number of steps to divide the search range into when looking for possible threshold values using drop analysis. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis see Tarboton et al. (1991, 1992), Tarboton and Ames (2001). There is no python reference for this parameter. |
Double |
Use_logarithmic_spacing_for_threshold_values | Dialog
Reference This checkbox indicates whether logarithmic or linear spacing should be used when looking for possible threshold values using drop ananlysis. There is no python reference for this parameter. |
Boolean |
Input_Number_of_Processes | Dialog
Reference The number of stripes that the domain will be divided into and the number of MPI parallel processes that will be spawned to evaluate each of the stripes. There is no python reference for this parameter. |
Long |
Output_Drop_Analysis_Text_File | Dialog
Reference This is a comma delimited text file with the following header line: Threshold, DrainDen, NoFirstOrd, NoHighOrd, MeanDFirstOrd, MeanDHighOrd, StdDevFirstOrd, StdDevHighOrd, T The file then contains one line of data for each threshold value examined, and then a summary line that indicates the optimum threshold value. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis, see Tarboton et al. (1991, 1992), Tarboton and Ames (2001). There is no python reference for this parameter. |
File |
Output_Stream_Raster_Grid | Dialog
Reference This is an indicator grid (1,0) that indicates the location of streams, with a value of 1 for each of the stream cells and 0 for the remainder of the cells. There is no python reference for this parameter. |
Raster Dataset |
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