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‎stream_length_utility/Application of stream_length utility.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<a href=\"http://landlab.github.io\"><img style=\"float: left\" src=\"https://raw.githubusercontent.com/landlab/tutorials/master/landlab_header.png\"></a>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"For instructions on how to run an interactive iPython notebook, click here: https://github.com/landlab/tutorials/blob/master/README.md\n",
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"For the unexpanded version to download and run, click here:http://nbviewer.jupyter.org/github/landlab/tutorials/blob/master/component_tutorial/component_tutorial_unexpanded.ipynb\n",
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"For more Landlab tutorials, click here: https://github.com/landlab/landlab/wiki/Tutorials"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Application of the stream_length utility on a Sicilian basin**"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This notebook illustrates how to run the stream_length utility on a real topography. For first, a watershed will be extracted from an input DEM by using the watershed utility. Then, a spatial distribution of the distances from each node to the watershed's outlet according to the path set with the D8 algorithm, will be obtained with the stream_length utility."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, import what we'll need:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from landlab.io import read_esri_ascii\n",
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"from landlab.components import FlowAccumulator\n",
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"from landlab.plot import imshow_grid\n",
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"from matplotlib.pyplot import figure\n",
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"from landlab.utils import watershed\n",
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"import numpy as np\n",
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"from landlab.utils.stream_length import calculate_stream_length"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Import a square DEM that includes the watershed:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"(mg, z) = read_esri_ascii('nocella_resampled.txt', name='topographic__elevation')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Run the FlowAccumulator and the DepressionFinderAndRouter components to find depressions, to route the flow across them and to calculate flow direction and drainage area:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"fr = FlowAccumulator(mg, flow_director = 'D8', depression_finder = 'DepressionFinderAndRouter')\n",
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"fr.run_one_step()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Fix the outlet's id (the one indicated in this example is the whole watershed's outlet):"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"outlet_id = 15324"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Run the watershed utility and show the watershed mask:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"ws_mask = watershed.get_watershed_mask(mg, outlet_id)\n",
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"figure(); imshow_grid(mg, ws_mask)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Run the stream_length utility:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"stream__length = calculate_stream_length(mg, add_to_grid=True, noclobber=False)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Mask the stream__length to the watershed mask:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"flow_length = np.zeros(len(ws_mask))\n",
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"for i in range (0,len(ws_mask)):\n",
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" if ws_mask[i] == True:\n",
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" flow_length[i] = stream__length[i]-stream__length[outlet_id]\n",
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" else:\n",
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" flow_length[i] = 0"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Add the flow_length field to the grid and show the spatial distribution of the distances from each node to the watershed's outlet:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"mg.add_field('node','flow_length',flow_length)\n",
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"figure(); imshow_grid(mg, mg['node']['flow_length'])"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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