{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# SSEBop" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "from pynhd import NLDI\n", "\n", "import pygeohydro as gh" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The daily actual evapotranspiration can be retrieved from [SEEBop](https://earlywarning.usgs.gov/ssebop/modis/daily) database. Note that since this service does not offer a web service and data are available as raster files on the server, so this function is not as fast as other functions and download speed might be the bottleneck.\n", "\n", "You can get the actual ET for location using ``ssebopeta_byloc`` and for a region using ``ssebopeta_bygeom``. Let's get a watershed geometry using NLDI and then get the actual ET." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "geometry = NLDI().get_basins(\"01031500\").geometry[0]" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "dates = (\"2005-10-01\", \"2005-10-05\")\n", "coords = (geometry.centroid.x, geometry.centroid.y)\n", "eta_p = gh.ssebopeta_byloc(coords, dates=dates)\n", "eta_g = gh.ssebopeta_bygeom(geometry, dates=dates)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = eta_g.isel(time=4).plot(size=5)\n", "ax.figure.savefig(\"../_static/eta.png\", bbox_inches=\"tight\", dpi=100)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.6" } }, "nbformat": 4, "nbformat_minor": 4 }