{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Subsetting climate variables over a watershed\n", "\n", "Hydrological models are driven by precipitation, temperature and a number of other variables depending on the processes that are simulated. These variables are typically provided by networks of weather stations. For practicality, these point values are often interpolated over space to create *gridded products*, that is, arrays of climate variables over regular coordinates of time and space.\n", "\n", "Global hydrological models however require time series of average climate variables over the entire watersheds. When the watershed includes multiples stations, or covers multiple grid cells, we first need to average these multiple stations or grids to yield a single value per time step. The Raven modeling framework can work directly with gridded datasets, provided the configuration includes the weights to apply to the array. For example, all grid cells outside the watershed could be given weights of 0, while all grid cells inside given a weight proportional to the area of the grid that is inside the watershed.\n", "\n", "While there are now utilities to work with grid weights, it is usually more computationally efficient to feed Raven sub-watershed averages. Here we fetch a watershed outline from a geospatial data server, then use the Finch server to compute the watershed average." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2024-10-16T17:31:24.955099Z", "start_time": "2024-10-16T17:31:24.950060Z" }, "execution": { "iopub.execute_input": "2025-04-23T21:53:03.690356Z", "iopub.status.busy": "2025-04-23T21:53:03.688933Z", "iopub.status.idle": "2025-04-23T21:53:04.739080Z", "shell.execute_reply": "2025-04-23T21:53:04.738215Z" } }, "outputs": [], "source": [ "# Import the necessary libraries.\n", "import datetime as dt\n", "import os\n", "\n", "import birdy\n", "import geopandas as gpd" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2024-10-16T17:31:30.620314Z", "start_time": "2024-10-16T17:31:25.099384Z" }, "execution": { "iopub.execute_input": "2025-04-23T21:53:04.745441Z", "iopub.status.busy": "2025-04-23T21:53:04.744257Z", "iopub.status.idle": "2025-04-23T21:53:07.224724Z", "shell.execute_reply": "2025-04-23T21:53:07.223685Z" } }, "outputs": [], "source": [ "# Set the links to the servers.\n", "# Note that if Finch is a remote server, Raven needs to be accessible on the next because some cells\n", "# below use the output from Raven processes to feed into Finch.\n", "\n", "url_finch = os.environ.get(\n", " \"FINCH_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/finch/wps\"\n", ")\n", "\n", "url_raven = os.environ.get(\n", " \"WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\"\n", ")\n", "\n", "# Establish client connexions to the remote servers\n", "finch = birdy.WPSClient(url_finch)\n", "raven = birdy.WPSClient(url_raven)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Extracting the watershed contour and sub-basins identifiers\n", "\n", "Let's try to identify a sub-basin feeding into Lake Kénogami. We'll start by launching a process with Raven to find the upstream watersheds. The process, called `hydrobasins_select`, takes as an input geographical point coordinates, finds the HydroSheds sub-basin including this point, then looks up into the HydroSheds database to find all upstream sub-basins. It returns the polygon of the watershed contour as a GeoJSON file, as well as a list of all the sub-basins IDs within the watershed." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2024-10-16T17:31:36.825624Z", "start_time": "2024-10-16T17:31:30.628321Z" }, "execution": { "iopub.execute_input": "2025-04-23T21:53:07.228553Z", "iopub.status.busy": "2025-04-23T21:53:07.228291Z", "iopub.status.idle": "2025-04-23T21:53:12.247325Z", "shell.execute_reply": "2025-04-23T21:53:12.246472Z" } }, "outputs": [], "source": [ "# Send a request to the server and get the response.\n", "hydrobasin_resp = raven.hydrobasins_select(\n", " location=\"-71.41, 47.96\", aggregate_upstream=True\n", ")\n", "\n", "# Wait for the process to complete before continuing with calculations." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2024-10-16T17:31:37.106752Z", "start_time": "2024-10-16T17:31:36.857307Z" }, "execution": { "iopub.execute_input": "2025-04-23T21:53:12.251189Z", "iopub.status.busy": "2025-04-23T21:53:12.250860Z", "iopub.status.idle": "2025-04-23T21:53:12.271918Z", "shell.execute_reply": "2025-04-23T21:53:12.271154Z" } }, "outputs": [], "source": [ "# Collecting the response: the watershed contour and the subbasin ids\n", "feature_url, sb_ids = hydrobasin_resp.get()\n", "feature, subbasin_ids = hydrobasin_resp.get(asobj=True)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2024-10-16T17:31:38.034035Z", "start_time": "2024-10-16T17:31:37.132606Z" }, "execution": { "iopub.execute_input": "2025-04-23T21:53:12.275324Z", "iopub.status.busy": "2025-04-23T21:53:12.275011Z", "iopub.status.idle": "2025-04-23T21:53:12.952089Z", "shell.execute_reply": "2025-04-23T21:53:12.951145Z" } }, "outputs": [ { "data": { "text/plain": [ "'Number of subbasins: 4'" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot our vector shapefile\n", "df = gpd.GeoDataFrame.from_file(feature_url)\n", "df.plot()\n", "\n", "display(f\"Number of subbasins: {len(subbasin_ids)}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Subsetting a gridded climate dataset\n", "\n", "We can then use this watershed outline to average climate data. The watershed shape is given as a GeoJSON file to the `average_polygon` process, along with the gridded file to average." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2024-10-16T17:37:55.203739Z", "start_time": "2024-10-16T17:37:52.375684Z" }, "execution": { "iopub.execute_input": "2025-04-23T21:53:12.955824Z", "iopub.status.busy": "2025-04-23T21:53:12.955303Z", "iopub.status.idle": "2025-04-23T21:53:16.043390Z", "shell.execute_reply": "2025-04-23T21:53:16.042399Z" } }, "outputs": [], "source": [ "# Compute the watershed temperature average.\n", "nc_file = \"https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/dodsC/birdhouse/testdata/xclim/NRCANdaily/nrcan_canada_daily_tasmin_1990.nc\"\n", "\n", "resp = finch.average_polygon(\n", " resource=str(nc_file),\n", " shape=feature_url,\n", " tolerance=0.1,\n", " start_date=dt.datetime(1990, 5, 1),\n", " end_date=dt.datetime(1990, 9, 1),\n", ")" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2024-10-16T17:37:56.145331Z", "start_time": "2024-10-16T17:37:55.274835Z" }, "execution": { "iopub.execute_input": "2025-04-23T21:53:16.050582Z", "iopub.status.busy": "2025-04-23T21:53:16.049997Z", "iopub.status.idle": "2025-04-23T21:53:18.035978Z", "shell.execute_reply": "2025-04-23T21:53:18.033403Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Downloading to /tmp/tmp4vbx6bl9/nrcan_canada_daily_tasmin_1990_avg.nc.\n" ] }, { "data": { "text/plain": [ "[]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Get the output files and plot the temperature time series averaged over the subbasins.\n", "ds, meta = resp.get(asobj=True)\n", "ds.tasmin.plot()\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.12" } }, "nbformat": 4, "nbformat_minor": 4 }