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Evaluates the extreme (either maximum or minimum) upslope value from an input grid based on the D8 flow model. This is intended initially for use in stream raster generation to identify a threshold of the slope times area product that results in an optimum (according to drop analysis) stream network.
If the optional outlet point shapefile is used, only the outlet cells and the cells upslope (by the D8 flow model) of them are in the domain to be evaluated.
By default, the tool checks for edge contamination. This is defined as the possibility that a result may be underestimated due to grid cells outside of the domain not being counted. This occurs when drainage is inwards from the boundaries or areas with “no data” values for elevation. The algorithm recognizes this and reports “no data” for the result for these grid cells. It is common to see streaks of “no data” values extending inwards from boundaries along flow paths that enter the domain at a boundary. This is the desired effect and indicates that the result for these grid cells is unknown due to it being dependent on terrain outside of the domain of data available. Edge contamination checking may be turned off in cases where you know this is not an issue or want to ignore these problems, if for example, the DEM has been clipped along a watershed outline.
Optional.
A point shape file defining outlets of interest. If this input file is used, only the area upslope of these outlets will be evaluated by the tool.
A flag that indicates whether the tool should check for edge contamination.
Por defecto: True
A flag to indicate whether the maximum or minimum upslope value is to be calculated.
Por defecto: True
processing.runalg('taudem:d8extremeupslopevalue', -p, -sa, -o, -nc, -min, -ssa)
Creates an indicator grid (1, 0) that evaluates A >= (M)(Ly) based on upslope path length, D8 contributing area grid inputs, and parameters M and y. This grid indicates likely stream source grid cells. This is an experimental method with theoretical basis in Hack’s law which states that for streams L ~ A 0.6. However for hillslopes with parallel flow L ~ A. So a transition from hillslopes to streams may be represented by L ~ A 0.8 suggesting identifying grid cells as stream cells if A > M (L (1/0.8)).
The multiplier threshold (M) parameter which is used in the formula: A > (M)(Ly), to identify the beginning of streams.
Por defecto: 0.03
The exponent (y) parameter which is used in the formula: A > (M)(Ly), to identify the beginning of streams. In branching systems, Hack’s law suggests that L = 1/M A(1/y) with 1/y = 0.6 (or 0.56) (y about 1.7). In parallel flow systems L is proportional to A (y about 1). This method tries to identify the transition between these two paradigms by using an exponent y somewhere in between (y about 1.3).
Por defecto: 1.3
processing.runalg('taudem:lengthareastreamsource', length_grid, contrib_area_grid, threshold, exponent, stream_source_grid)
Moves outlet points that are not aligned with a stream cell from a stream raster grid, downslope along the D8 flow direction until a stream raster cell is encountered, the “max_dist” number of grid cells are examined, or the flow path exits the domain (i.e. a “no data” value is encountered for the D8 flow direction). The output file is a new outlets shapefile where each point has been moved to coincide with the stream raster grid, if possible. A field “dist_moved” is added to the new outlets shapefile to indicate the changes made to each point. Points that are already on a stream cell are not moved and their “dist_moved” field is assigned a value 0. Points that are initially not on a stream cell are moved by sliding them downslope along the D8 flow direction until one of the following occurs: a) A stream raster grid cell is encountered before traversing the “max_dist” number of grid cells. In which case, the point is moved and the “dist_moved” field is assigned a value indicating how many grid cells the point was moved. b) More than the “max_number” of grid cells are traversed, or c) the traversal ends up going out of the domain (i.e., a “no data” D8 flow direction value is encountered). In which case, the point is not moved and the “dist_moved” field is assigned a value of -1.
Un archivo con forma de punto define puntos de interés o salidas que se deberían localizar en una corriente, pero no pueden estar exactamente en la corriente debido al hecho que las localizaciones de puntos de forma archivo no pueden haber sido registrado con precisión respecto a la grilla de trama de corriente.
This input paramater is the maximum number of grid cells that the points in the input outlet shapefile will be moved before they are saved to the output outlet shapefile.
Predeterminado: 50
processing.runalg('taudem:moveoutletstostreams', -p, -src, -o, -md, -om)
Creates an indicator grid (1, 0) of upward curved grid cells according to the Peuker and Douglas algorithm.
With this tool, the DEM is first smoothed by a kernel with weights at the center, sides, and diagonals. The Peuker and Douglas (1975) method (also explained in Band, 1986), is then used to identify upwardly curving grid cells. This technique flags the entire grid, then examines in a single pass each quadrant of 4 grid cells, and unflags the highest. The remaining flagged cells are deemed “upwardly curved”, and when viewed, resemble a channel network. This proto-channel network generally lacks connectivity and requires thinning, issues that were discussed in detail by Band (1986).
The center weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells.
Predeterminado: 0.4
The side weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells.
Por defecto: 0.1
The diagonal weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells.
Predeterminado: 0.05
processing.runalg('taudem:peukerdouglas', elevation_grid, center_weight, side_weight, diagonal_weight, stream_source_grid)
Creates a grid of slope-area values = (Sm) (An) based on slope and specific catchment area grid inputs, and parameters m and n. This tool is intended for use as part of the slope-area stream raster delineation method.
El parámetro exponente de inclinación (“m”) que será usado en la fórmula: “(Sm)(An)”, que que se usará para crear la cuadrícula area-inclinación.
Predeterminado: 2
The area exponent (n) parameter which will be used in the formula: (Sm)(An), that is used to create the slope-area grid.
Predeterminado: 1
processing.runalg('taudem:slopeareacombination', slope_grid, area_grid, slope_exponent, area_exponent, slope_area_grid)
Operates on any grid and outputs an indicator (1, 0) grid identifing cells with input values >= the threshold value. The standard use is to use an accumulated source area grid to as the input grid to generate a stream raster grid as the output. If you use the optional input mask grid, it limits the domain being evaluated to cells with mask values >= 0. When you use a D-infinity contributing area grid (*sca) as the mask grid, it functions as an edge contamination mask. The threshold logic is:
src = ((ssa >= thresh) & (mask >= s0)) ? 1:0
This parameter is compared to the value in the Accumulated Stream Source grid (*ssa) to determine if the cell should be considered a stream cell. Streams are identified as grid cells for which ssa value is >= this threshold.
Predeterminado: 100
Optional.
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.
processing.runalg('taudem:streamdefinitionbythreshold', -ssa, -thresh, -mask, -src)
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 *drp.txt file the stream drop statistics table. This function is designed to aid in the determination of a geomorphologically objective threshold to be used to delineate streams. Drop Analysis attempts to select the right threshold automatically by evaluating a stream network for a range of thresholds and examining the constant drop property of the resulting Strahler streams. Basically it asks the question: Is the mean stream drop for first order streams statistically different from the mean stream drop for higher order streams, using a T-test. Stream drop is the difference in elevation from the beginning to the end of a stream defined as the sequence of links of the same stream order. If the T-test shows a significant difference then the stream network does not obey this “law” so a larger threshold needs to be chosen. The smallest threshold for which the T-test does not show a significant difference gives the highest resolution stream network that obeys the constant stream drop “law” from geomorphology, and is the threshold chosen for the “objective” or automatic mapping of streams from the DEM. This function can be used in the development of stream network rasters, where the exact watershed characteristic(s) that were accumulated in the accumulated stream source grid vary based on the method being used to determine the stream network raster.
The constant stream drop “law” was identified by Broscoe (1959). For the science behind using this to determine a stream delineation threshold, see Tarboton et al. (1991, 1992), Tarboton and Ames (2001).
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).
Predeterminado: 5
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).
Predeterminado: 500
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).
Predeterminado: 10
This parameter indicates whether logarithmic or linear spacing should be used when looking for possible threshold values using drop ananlysis.
Opciones:
0 — Logarítmico
1 — Lineal
Predeterminado: 0
This is a comma delimited text file with the following header line:
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).
processing.runalg('taudem:streamdropanalysis', d8_contrib_area_grid, d8_flow_dir_grid, pit_filled_grid, accum_stream_source_grid, outlets_shape, min_treshold, max_threshold, treshold_num, step_type, drop_analysis_file)
This tool produces a vector network and shapefile from the stream raster grid. The flow direction grid is used to connect flow paths along the stream raster. The Strahler order of each stream segment is computed. The subwatershed draining to each stream segment (reach) is also delineated and labeled with the value identifier that corresponds to the WSNO (watershed number) attribute in the Stream Reach Shapefile.
This tool orders the stream network according to the Strahler ordering system. Streams that don’t have any other streams draining in to them are order 1. When two stream reaches of different order join the order of the downstream reach is the order of the highest incoming reach. When two reaches of equal order join the downstream reach order is increased by 1. When more than two reaches join the downstream reach order is calculated as the maximum of the highest incoming reach order or the second highest incoming reach order + 1. This generalizes the common definition to cases where more than two reaches join at a point. The network topological connectivity is stored in the Stream Network Tree file, and coordinates and attributes from each grid cell along the network are stored in the Network Coordinates file.
The stream raster grid is used as the source for the stream network, and the flow direction grid is used to trace connections within the stream network. Elevations and contributing area are used to determine the elevation and contributing area attributes in the network coordinate file. Points in the outlets shapefile are used to logically split stream reaches to facilitate representing watersheds upstream and downstream of monitoring points. The program uses the attribute field “id” in the outlets shapefile as identifiers in the Network Tree file. This tool then translates the text file vector network representation in the Network Tree and Coordinates files into a shapefile. Further attributes are also evaluated. The program has an option to delineate a single watershed by representing the entire area draining to the Stream Network as a single value in the output watershed grid.
Optional.
A point shape file defining points of interest. If this file is used, the tool will only deliiniate the stream network upstream of these outlets. Additionally, points in the Outlets Shapefile are used to logically split stream reaches to facilitate representing watersheds upstream and downstream of monitoring points. This tool REQUIRES THAT THERE BE an integer attribute field “id” in the Outlets Shapefile, because the “id” values are used as identifiers in the Network Tree file.
This option causes the tool to delineate a single watershed by representing the entire area draining to the Stream Network as a single value in the output watershed grid. Otherwise a seperate watershed is delineated for each stream reach. Default is False (seperate watershed).
Predeterminado: False
This output is a polyline shapefile giving the links in a stream network. The columns in the attribute table are:
This output is a text file that details the network topological connectivity is stored in the Stream Network Tree file. Columns are as follows:
Esta salida es un archivo texto que contiene las coordenadas y atributos de puntos a lo largo de la red de cursos de agua. Las columnas son las siguientes:
Coordenada X
Coordenada Y
Elevación
Área contribuyente
processing.runalg('taudem:streamreachandwatershed', -fel, -p, -ad8, -src, -o, -sw, -ord, -w, -net, -tree, -coord)
Calculates Gage Watersheds Grid. Each grid cell is labeled with the identifier (from column id) of the gage to which it drains directly without passing through any other gages.
processing.runalg('taudem:gagewatershed2', -p, -o, -gw, -id)
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processing.runalg('taudem:topographicwetnessindex', -sca, -slp, -twi)