{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GIS operations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Geographic Information System (GIS) operations are crucial in hydrological analysis. This section illustrates how to leverage the `xHydro` library for performing key GIS tasks, including delineating watershed boundaries and extracting critical physiographic, climatological, and geographical variables at the watershed scale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import leafmap\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import xclim\n",
    "import xdatasets\n",
    "from IPython.display import clear_output\n",
    "\n",
    "import xhydro as xh\n",
    "import xhydro.gis as xhgis\n",
    "\n",
    "clear_output(wait=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Watershed delineation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Currently, watershed delineation utilizes HydroSHEDS' [HydroBASINS](https://www.hydrosheds.org/products/hydrobasins) (hybas_na_lev01-12_v1c) and is compatible with any location in North America. The process involves identifying all upstream sub-basins from a specified outlet and consolidating them into a unified watershed. The [leafmap](https://leafmap.org/) library is used to generate interactive maps, which allow for the selection of outlets or the visualization of the resulting watershed boundaries. While the use of the map is not mandatory for performing the calculations, it greatly enhances the visualization and understanding of the watershed delineation process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = leafmap.Map(center=(48.63, -74.71), zoom=5, basemap=\"USGS Hydrography\")"
   ]
  },
  {
   "attachments": {
    "bbfc640d-4fe8-43b2-b2be-76e2c3e522c6.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image_feneral.png](attachment:bbfc640d-4fe8-43b2-b2be-76e2c3e522c6.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### a) From a list of coordinates\n",
    "A first option is to provide a list of coordinates. In the example below, we select two pour points, with each one representing the outlet for the watersheds of Montmorency and the Beaurivage River, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "lng_lat = [\n",
    "    (-71.15069, 46.89431),  # Montmorency river watershed\n",
    "    (-71.28512, 46.66141),  # Beaurivage river watershed\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### b) From markers on a map"
   ]
  },
  {
   "attachments": {
    "b9428126-08e5-4d16-af7a-987435e85be6.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rather than using a list, a more interactive approach allows for directly selecting outlets from the existing map `m`, using the `Draw a marker` button located on the left of the map. The image below demonstrates how to select pour points by dragging markers to the desired locations on the map.\n",
    "\n",
    "![image_marker.png](attachment:b9428126-08e5-4d16-af7a-987435e85be6.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After selecting points using either approach a) or b), or a combination of both, we can initiate the watershed delineation calculation. This is done using the function `xhydro.gis.watershed_delineation`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function watershed_delineation in module xhydro.gis:\n",
      "\n",
      "watershed_delineation(\n",
      "    *,\n",
      "    coordinates: 'list[tuple] | tuple | None' = None,\n",
      "    m: 'leafmap.Map | None' = None\n",
      ") -> 'gpd.GeoDataFrame'\n",
      "    Calculate watershed delineation from pour point.\n",
      "\n",
      "    Watershed delineation can be computed at any location in North America using HydroBASINS (hybas_na_lev01-12_v1c).\n",
      "    The process involves assessing all upstream sub-basins from a specified pour point and consolidating them into a\n",
      "    unified watershed.\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    coordinates : list of tuple, tuple, optional\n",
      "        Geographic coordinates (longitude, latitude) for the location where watershed delineation will be conducted.\n",
      "    m : leafmap.Map, optional\n",
      "        If the function receives both a map and coordinates as inputs, it will generate and display watershed\n",
      "        boundaries on the map. Additionally, any markers present on the map will be transformed into\n",
      "        corresponding watershed boundaries for each marker.\n",
      "\n",
      "    Returns\n",
      "    -------\n",
      "    gpd.GeoDataFrame\n",
      "        GeoDataFrame containing the watershed boundaries.\n",
      "\n",
      "    Warnings\n",
      "    --------\n",
      "    This function relies on an Amazon S3-hosted dataset to delineate watersheds.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(xhgis.watershed_delineation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HYBAS_ID</th>\n",
       "      <th>Upstream Area (sq. km)</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7120034480</td>\n",
       "      <td>1157.6</td>\n",
       "      <td>POLYGON ((-71.15208 46.8838, -71.15612 46.8869...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7120365812</td>\n",
       "      <td>693.5</td>\n",
       "      <td>POLYGON ((-71.09758 46.40035, -71.09409 46.403...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     HYBAS_ID  Upstream Area (sq. km)  \\\n",
       "0  7120034480                  1157.6   \n",
       "1  7120365812                   693.5   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((-71.15208 46.8838, -71.15612 46.8869...  \n",
       "1  POLYGON ((-71.09758 46.40035, -71.09409 46.403...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf = xhgis.watershed_delineation(coordinates=lng_lat, m=m)\n",
    "gdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The outcomes are stored in a GeoPandas `gpd.GeoDataFrame` object, enabling us to save the polygons in various common formats, such as ESRI Shapefile or GeoJSON. If a map `m` is available, the polygons will be automatically added to it. To visualize the map, simply type `m` in the code cell to render it. If displaying the map directly is not compatible with your notebook interpreter, you can use the following code to extract the HTML from the map and plot it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "m.zoom_to_gdf(gdf)"
   ]
  },
  {
   "attachments": {
    "d52b56d1-860e-4b19-9a63-0c999ef89a9a.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image_gdf.png](attachment:d52b56d1-860e-4b19-9a63-0c999ef89a9a.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### c) From [xdatasets](https://github.com/hydrologie/xdatasets)\n",
    "\n",
    "While automatically delineating watershed boundaries is a valuable tool, users are encouraged to utilize official watershed boundaries when available, rather than generating new ones. The [xdatasets](https://github.com/hydrologie/xdatasets) library, for example, hosts a few official boundaries that can be accessed using the `xdatasets.Query` function. As of today, the following watershed sources are available:\n",
    "\n",
    "| Source                                                                                                                                                             | Dataset name   |\n",
    "|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------|\n",
    "| [(Canada) National Water Data Archive: HYDAT](https://www.canada.ca/en/environment-climate-change/services/water-overview/quantity/monitoring/survey/data-products-services/national-archive-hydat.html) | hydat_polygons |\n",
    "| [(Quebec) Provincial Ministry of Environment (MELCCFP/DPEH)](https://www.cehq.gouv.qc.ca/atlas-hydroclimatique/stations-hydrometriques/index.htm)                                                                         | deh_polygons   |\n",
    "| [(Quebec) Hydro-Quebec](https://www.hydroquebec.com/)                                                                                                                                | hq_polygons    |\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Station</th>\n",
       "      <th>Superficie</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>031502</td>\n",
       "      <td>15.708960</td>\n",
       "      <td>POLYGON ((-72.50126 46.21216, -72.50086 46.213...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>042103</td>\n",
       "      <td>579.479614</td>\n",
       "      <td>POLYGON ((-78.49014 46.64514, -78.4901 46.6450...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Station  Superficie                                           geometry\n",
       "0  031502   15.708960  POLYGON ((-72.50126 46.21216, -72.50086 46.213...\n",
       "1  042103  579.479614  POLYGON ((-78.49014 46.64514, -78.4901 46.6450..."
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xdatasets.Query(\n",
    "    **{\n",
    "        \"datasets\": {\n",
    "            \"deh_polygons\": {\n",
    "                \"id\": [\"031502\", \"0421*\"],\n",
    "                \"regulated\": [\"Natural\"],\n",
    "            }\n",
    "        }\n",
    "    }\n",
    ").data.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extraction of watershed properties"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once the watershed boundaries are obtained, we can extract valuable properties such as geographical information, land use classification, and climatological data from the delineated watersheds."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### a) Geographical watershed properties\n",
    "\n",
    "First, `xhydro.gis.watershed_properties` can be used to extract the geographical properties of the watershed, including the perimeter, total area, Gravelius coefficient, and basin centroid. It is important to note that this function returns all the columns present in the provided `gpd.GeoDataFrame` argument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function watershed_properties in module xhydro.gis:\n",
      "\n",
      "watershed_properties(\n",
      "    gdf: 'gpd.GeoDataFrame',\n",
      "    *,\n",
      "    unique_id: 'str | None' = None,\n",
      "    projected_crs: 'int | str | None' = 'NAD83',\n",
      "    output_format: \"Literal['xarray', 'xr.Dataset', 'geopandas', 'gpd.GeoDataFrame']\" = 'geopandas'\n",
      ") -> 'gpd.GeoDataFrame | xr.Dataset'\n",
      "    Watershed properties extracted from a gpd.GeoDataFrame.\n",
      "\n",
      "    The calculated properties are :\n",
      "    - area\n",
      "    - perimeter\n",
      "    - gravelius\n",
      "    - centroid coordinates\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    gdf : gpd.GeoDataFrame\n",
      "        GeoDataFrame containing watershed polygons. Must have a defined .crs attribute.\n",
      "    unique_id : str, optional\n",
      "        The column name in the GeoDataFrame that serves as a unique identifier.\n",
      "    projected_crs : int | str\n",
      "        The projected coordinate reference system (crs) to utilize for calculations, such as determining watershed area.\n",
      "        If a string is provided, it should be a valid Geodetic CRS for the `gpd.estimate_utm_crs()` method.\n",
      "        If None, the function will use the `gpd.estimate_utm_crs()` default (WGS 84).\n",
      "        Default is an estimated CRS based on NAD83.\n",
      "    output_format : str\n",
      "        One of either `xarray` (or `xr.Dataset`) or `geopandas` (or `gpd.GeoDataFrame`).\n",
      "\n",
      "    Returns\n",
      "    -------\n",
      "    gpd.GeoDataFrame or xr.Dataset\n",
      "        Output dataset containing the watershed properties.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(xhgis.watershed_properties)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HYBAS_ID</th>\n",
       "      <th>Upstream Area (sq. km)</th>\n",
       "      <th>area (m2)</th>\n",
       "      <th>estimated_area_diff (%)</th>\n",
       "      <th>perimeter (m)</th>\n",
       "      <th>gravelius (m/m)</th>\n",
       "      <th>centroid_lon</th>\n",
       "      <th>centroid_lat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7120034480</td>\n",
       "      <td>1157.6</td>\n",
       "      <td>1.160550e+09</td>\n",
       "      <td>0.254842</td>\n",
       "      <td>263428.762122</td>\n",
       "      <td>2.181355</td>\n",
       "      <td>-71.091980</td>\n",
       "      <td>47.257839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7120365812</td>\n",
       "      <td>693.5</td>\n",
       "      <td>5.855856e+08</td>\n",
       "      <td>-15.560840</td>\n",
       "      <td>158295.639822</td>\n",
       "      <td>1.845308</td>\n",
       "      <td>-71.260464</td>\n",
       "      <td>46.452161</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     HYBAS_ID  Upstream Area (sq. km)     area (m2)  estimated_area_diff (%)  \\\n",
       "0  7120034480                  1157.6  1.160550e+09                 0.254842   \n",
       "1  7120365812                   693.5  5.855856e+08               -15.560840   \n",
       "\n",
       "   perimeter (m)  gravelius (m/m)  centroid_lon  centroid_lat  \n",
       "0  263428.762122         2.181355    -71.091980     47.257839  \n",
       "1  158295.639822         1.845308    -71.260464     46.452161  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xhgis.watershed_properties(gdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For added convenience, we can also retrieve the same results in the form of an `xarray.Dataset`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 128B\n",
       "Dimensions:                 (HYBAS_ID: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID                (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "Data variables:\n",
       "    Upstream Area (sq. km)  (HYBAS_ID) float64 16B 1.158e+03 693.5\n",
       "    area                    (HYBAS_ID) float64 16B 1.161e+09 5.856e+08\n",
       "    estimated_area_diff     (HYBAS_ID) float64 16B 0.2548 -15.56\n",
       "    perimeter               (HYBAS_ID) float64 16B 2.634e+05 1.583e+05\n",
       "    gravelius               (HYBAS_ID) float64 16B 2.181 1.845\n",
       "    centroid_lon            (HYBAS_ID) float64 16B -71.09 -71.26\n",
       "    centroid_lat            (HYBAS_ID) float64 16B 47.26 46.45</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0600918d-e637-4141-bb8b-5be5c274cab2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0600918d-e637-4141-bb8b-5be5c274cab2' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>HYBAS_ID</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-750f3e23-228b-4a0f-aba1-b96a06cc94c8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-750f3e23-228b-4a0f-aba1-b96a06cc94c8' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>HYBAS_ID</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>7120034480 7120365812</div><input id='attrs-9a391f5b-c15a-4f70-b36a-cbc086dee858' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a391f5b-c15a-4f70-b36a-cbc086dee858' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce66bcbd-589d-4781-b599-43895169dee6' class='xr-var-data-in' type='checkbox'><label for='data-ce66bcbd-589d-4781-b599-43895169dee6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>HYBAS_ID</dd><dt><span>cf_role :</span></dt><dd>timeseries_id</dd></dl></div><div class='xr-var-data'><pre>array([7120034480, 7120365812])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8b12f32c-49c5-41e5-83ea-a070df6d3d8b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8b12f32c-49c5-41e5-83ea-a070df6d3d8b' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Upstream Area (sq. km)</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.158e+03 693.5</div><input id='attrs-179a98a1-f767-47d8-a46d-e9221224a20b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-179a98a1-f767-47d8-a46d-e9221224a20b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40e3de82-d060-429f-8a9e-f04a67f6830e' class='xr-var-data-in' type='checkbox'><label for='data-40e3de82-d060-429f-8a9e-f04a67f6830e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1157.6,  693.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.161e+09 5.856e+08</div><input id='attrs-a91d15a7-c653-4035-9327-06dc1dab368e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a91d15a7-c653-4035-9327-06dc1dab368e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7ff30b4-5804-445d-bbb8-e6b2e55c5453' class='xr-var-data-in' type='checkbox'><label for='data-a7ff30b4-5804-445d-bbb8-e6b2e55c5453' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m2</dd><dt><span>long_name :</span></dt><dd>Drainage area</dd></dl></div><div class='xr-var-data'><pre>array([1.16055005e+09, 5.85585577e+08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>estimated_area_diff</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2548 -15.56</div><input id='attrs-e0eafd77-e718-4795-8ce3-1f7f661e7e3c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0eafd77-e718-4795-8ce3-1f7f661e7e3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18a536a3-ad3c-448c-8e91-c899679f8e29' class='xr-var-data-in' type='checkbox'><label for='data-18a536a3-ad3c-448c-8e91-c899679f8e29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Estimated difference between the calculated area and the original source</dd></dl></div><div class='xr-var-data'><pre>array([  0.25484162, -15.56083972])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perimeter</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.634e+05 1.583e+05</div><input id='attrs-2fd0482b-3a1e-43a9-b1ff-b675ec3557e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fd0482b-3a1e-43a9-b1ff-b675ec3557e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-501dfa1f-fc0c-4ef8-82de-5c689ee9bf2f' class='xr-var-data-in' type='checkbox'><label for='data-501dfa1f-fc0c-4ef8-82de-5c689ee9bf2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Perimeter</dd></dl></div><div class='xr-var-data'><pre>array([263428.76212203, 158295.63982241])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gravelius</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.181 1.845</div><input id='attrs-1e8d0081-d57e-423d-a42e-090edc3ff5c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e8d0081-d57e-423d-a42e-090edc3ff5c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5db6abe-c992-4c6f-80ab-1e6737760b0c' class='xr-var-data-in' type='checkbox'><label for='data-a5db6abe-c992-4c6f-80ab-1e6737760b0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/m</dd><dt><span>long_name :</span></dt><dd>Gravelius index</dd></dl></div><div class='xr-var-data'><pre>array([2.18135486, 1.84530787])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centroid_lon</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-71.09 -71.26</div><input id='attrs-d9040289-44bd-4065-a5a4-2db689328d7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9040289-44bd-4065-a5a4-2db689328d7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90e4df6d-a064-45e5-921f-e649bdee357d' class='xr-var-data-in' type='checkbox'><label for='data-90e4df6d-a064-45e5-921f-e649bdee357d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>Longitude of the centroid of the watershed</dd></dl></div><div class='xr-var-data'><pre>array([-71.09197995, -71.26046365])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centroid_lat</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>47.26 46.45</div><input id='attrs-7f6050c3-6fc7-474f-817c-247706063734' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f6050c3-6fc7-474f-817c-247706063734' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a00c11b9-d227-48ab-a046-fb44b6985d0d' class='xr-var-data-in' type='checkbox'><label for='data-a00c11b9-d227-48ab-a046-fb44b6985d0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>Latitude of the centroid of the watershed</dd></dl></div><div class='xr-var-data'><pre>array([47.25783877, 46.45216103])</pre></div></li></ul></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 128B\n",
       "Dimensions:                 (HYBAS_ID: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID                (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "Data variables:\n",
       "    Upstream Area (sq. km)  (HYBAS_ID) float64 16B 1.158e+03 693.5\n",
       "    area                    (HYBAS_ID) float64 16B 1.161e+09 5.856e+08\n",
       "    estimated_area_diff     (HYBAS_ID) float64 16B 0.2548 -15.56\n",
       "    perimeter               (HYBAS_ID) float64 16B 2.634e+05 1.583e+05\n",
       "    gravelius               (HYBAS_ID) float64 16B 2.181 1.845\n",
       "    centroid_lon            (HYBAS_ID) float64 16B -71.09 -71.26\n",
       "    centroid_lat            (HYBAS_ID) float64 16B 47.26 46.45"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xhgis.watershed_properties(gdf, unique_id=\"HYBAS_ID\", output_format=\"xarray\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### b) Surface properties\n",
    "\n",
    "We can use `xhydro.gis.surface_properties` to extract surface properties for the same `gpd.GeoDataFrame`, such as slope and aspect. By default, these properties are calculated using [Copernicus' GLO-90 Digital Elevation Model](https://portal.opentopography.org/raster?opentopoID=OTSDEM.032021.4326.1) as of 2021-04-22. However, both the source and the date can be modified through the function's arguments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function surface_properties in module xhydro.gis:\n",
      "\n",
      "surface_properties(\n",
      "    gdf: 'gpd.GeoDataFrame',\n",
      "    *,\n",
      "    unique_id: 'str | None' = None,\n",
      "    projected_crs: 'int | str | None' = 'NAD83',\n",
      "    operation: 'str' = 'mean',\n",
      "    dataset_date: 'str' = '2021-04-22',\n",
      "    collection: 'str' = 'cop-dem-glo-90',\n",
      "    output_format: \"Literal['xarray', 'xr.Dataset', 'geopandas', 'gpd.GeoDataFrame']\" = 'geopandas'\n",
      ") -> 'gpd.GeoDataFrame | xr.Dataset'\n",
      "    Surface properties for watersheds.\n",
      "\n",
      "    Surface properties are calculated using Copernicus's GLO-90 Digital Elevation Model.\n",
      "    By default, the dataset has a geographic coordinate system (EPSG: 4326) and this function expects a projected crs for more accurate results.\n",
      "\n",
      "    The calculated properties are :\n",
      "    - elevation (meters)\n",
      "    - slope (degrees)\n",
      "    - aspect ratio (degrees)\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    gdf : gpd.GeoDataFrame\n",
      "        GeoDataFrame containing watershed polygons. Must have a defined .crs attribute.\n",
      "    unique_id : str, optional\n",
      "        The column name in the GeoDataFrame that serves as a unique identifier.\n",
      "    projected_crs : int | str\n",
      "        The projected coordinate reference system (crs) to utilize for calculations, such as determining watershed area.\n",
      "        If a string is provided, it should be a valid Geodetic CRS for the `gpd.estimate_utm_crs()` method.\n",
      "        If None, the function will use the `gpd.estimate_utm_crs()` default (WGS 84).\n",
      "        Default is an estimated CRS based on NAD83.\n",
      "    operation : str\n",
      "        Aggregation statistics such as `mean` or `sum`.\n",
      "    dataset_date : str\n",
      "        Date (%Y-%m-%d) for which to select the imagery from the dataset. Date must be available.\n",
      "    collection : str\n",
      "        Collection name from the Planetary Computer STAC Catalog. Default is `cop-dem-glo-90`.\n",
      "    output_format : str\n",
      "        One of either `xarray` (or `xr.Dataset`) or `geopandas` (or `gpd.GeoDataFrame`).\n",
      "\n",
      "    Returns\n",
      "    -------\n",
      "    gpd.GeoDataFrame or xr.Dataset\n",
      "        Output dataset containing the surface properties.\n",
      "\n",
      "    Warnings\n",
      "    --------\n",
      "    This function relies on the Microsoft Planetary Computer's STAC Catalog to retrieve the Digital Elevation Model (DEM) data.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(xhgis.surface_properties)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>elevation</th>\n",
       "      <th>slope</th>\n",
       "      <th>aspect</th>\n",
       "      <th>time</th>\n",
       "      <th>spatial_ref</th>\n",
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       "      <td>725.898315</td>\n",
       "      <td>5.307655</td>\n",
       "      <td>186.393692</td>\n",
       "      <td>2021-04-22</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>222.474442</td>\n",
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       "      <td>212.094788</td>\n",
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      "text/plain": [
       "           elevation     slope      aspect       time  spatial_ref\n",
       "geometry                                                          \n",
       "0         725.898315  5.307655  186.393692 2021-04-22            0\n",
       "1         222.474442  1.356003  212.094788 2021-04-22            0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
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   ],
   "source": [
    "xhgis.surface_properties(gdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, for convenience, we can output the results in `xarray.Dataset` format :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
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       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
       "  );\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: var(\n",
       "    --jp-content-font-color0,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
       "  );\n",
       "  --xr-font-color2: var(\n",
       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
       "  );\n",
       "  --xr-font-color3: var(\n",
       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, #111111)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
       "  );\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "  line-height: 1.6;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 72B\n",
       "Dimensions:      (HYBAS_ID: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID     (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "    time         datetime64[ns] 8B 2021-04-22\n",
       "    spatial_ref  int64 8B 0\n",
       "    geometry     (HYBAS_ID) geometry 16B POLYGON ((336034.51117111975 5194499...\n",
       "Data variables:\n",
       "    elevation    (HYBAS_ID) float32 8B 725.9 222.5\n",
       "    slope        (HYBAS_ID) float32 8B 5.308 1.356\n",
       "    aspect       (HYBAS_ID) float32 8B 186.4 212.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6ee5c273-2ac0-483b-98db-ea0672da7138' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ee5c273-2ac0-483b-98db-ea0672da7138' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>HYBAS_ID</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2bedc211-4b7d-4b00-a942-606b96560d32' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2bedc211-4b7d-4b00-a942-606b96560d32' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>HYBAS_ID</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>7120034480 7120365812</div><input id='attrs-17ac4207-c168-405b-be57-d6e7e70385fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17ac4207-c168-405b-be57-d6e7e70385fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd52927a-e1e7-4858-b2bf-af6b41d40fe9' class='xr-var-data-in' type='checkbox'><label for='data-bd52927a-e1e7-4858-b2bf-af6b41d40fe9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>HYBAS_ID</dd><dt><span>cf_role :</span></dt><dd>timeseries_id</dd></dl></div><div class='xr-var-data'><pre>array([7120034480, 7120365812])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-04-22</div><input id='attrs-51c8464a-e970-49b4-a594-b4ab6541a1f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-51c8464a-e970-49b4-a594-b4ab6541a1f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9861bae-1225-4ddb-a8dd-968eb3b975d0' class='xr-var-data-in' type='checkbox'><label for='data-e9861bae-1225-4ddb-a8dd-968eb3b975d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;2021-04-22T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-45d609e8-e4b7-4e45-850a-133506ff1fbc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45d609e8-e4b7-4e45-850a-133506ff1fbc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ea4e409-0855-4afd-a655-5daf817c43a3' class='xr-var-data-in' type='checkbox'><label for='data-9ea4e409-0855-4afd-a655-5daf817c43a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;NAD83 / UTM zone 19N&quot;,GEOGCS[&quot;NAD83&quot;,DATUM[&quot;North_American_Datum_1983&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4269&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-69],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;26919&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314140356</dd><dt><span>inverse_flattening :</span></dt><dd>298.257222101</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>GRS 1980</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>NAD83</dd><dt><span>horizontal_datum_name :</span></dt><dd>North American Datum 1983</dd><dt><span>projected_crs_name :</span></dt><dd>NAD83 / UTM zone 19N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-69.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;NAD83 / UTM zone 19N&quot;,GEOGCS[&quot;NAD83&quot;,DATUM[&quot;North_American_Datum_1983&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4269&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-69],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;26919&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>310390.0344280064 443.0845889844382 0.0 5276492.045018455 0.0 -443.0845889844382</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geometry</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>geometry</div><div class='xr-var-preview xr-preview'>POLYGON ((336034.51117111975 519...</div><input id='attrs-5c66b640-9d4d-4397-b2df-5db51896506b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c66b640-9d4d-4397-b2df-5db51896506b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eda71a8-1beb-43d5-8210-9f0264388cb0' class='xr-var-data-in' type='checkbox'><label for='data-6eda71a8-1beb-43d5-8210-9f0264388cb0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:26919</dd></dl></div><div class='xr-var-data'><pre>&lt;GeometryArray&gt;\n",
       "[&lt;POLYGON ((336034.511 5194499.95, 335736.315 5194856.288, 334768.148 5195009...&gt;, &lt;POLYGON ((338756.838 5140668.986, 339034.864 5141046.334, 339222.257 514108...&gt;]\n",
       "Length: 2, dtype: geometry</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fcd2b3b8-8a57-41f1-a13b-58a99dea0289' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fcd2b3b8-8a57-41f1-a13b-58a99dea0289' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>elevation</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>725.9 222.5</div><input id='attrs-d851485c-5763-4f38-9d11-5295c9088a00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d851485c-5763-4f38-9d11-5295c9088a00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03a37be7-b912-45f8-94f2-683f498be675' class='xr-var-data-in' type='checkbox'><label for='data-03a37be7-b912-45f8-94f2-683f498be675' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Elevation</dd><dt><span>standard_name :</span></dt><dd>surface_altitude</dd></dl></div><div class='xr-var-data'><pre>array([725.8983 , 222.47444], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.308 1.356</div><input id='attrs-82b368c6-e885-4d9f-b927-909b111a877e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82b368c6-e885-4d9f-b927-909b111a877e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f8d91ad-d0ff-4118-af3d-b676c83febeb' class='xr-var-data-in' type='checkbox'><label for='data-2f8d91ad-d0ff-4118-af3d-b676c83febeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>long_name :</span></dt><dd>Slope</dd></dl></div><div class='xr-var-data'><pre>array([5.307655 , 1.3560029], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aspect</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>186.4 212.1</div><input id='attrs-656d05d0-814c-464c-8afb-1d7d4c1c1327' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-656d05d0-814c-464c-8afb-1d7d4c1c1327' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f95e09d-c579-4cab-9aa1-d386d6a490c1' class='xr-var-data-in' type='checkbox'><label for='data-3f95e09d-c579-4cab-9aa1-d386d6a490c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>long_name :</span></dt><dd>Aspect</dd></dl></div><div class='xr-var-data'><pre>array([186.39369, 212.09479], dtype=float32)</pre></div></li></ul></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 72B\n",
       "Dimensions:      (HYBAS_ID: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID     (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "    time         datetime64[ns] 8B 2021-04-22\n",
       "    spatial_ref  int64 8B 0\n",
       "    geometry     (HYBAS_ID) geometry 16B POLYGON ((336034.51117111975 5194499...\n",
       "Data variables:\n",
       "    elevation    (HYBAS_ID) float32 8B 725.9 222.5\n",
       "    slope        (HYBAS_ID) float32 8B 5.308 1.356\n",
       "    aspect       (HYBAS_ID) float32 8B 186.4 212.1"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xhgis.surface_properties(gdf, unique_id=\"HYBAS_ID\", output_format=\"xarray\")"
   ]
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  {
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    "### c) Land use classification\n",
    "\n",
    "Finally, we can retrieve land use classifications using `xhydro.gis.land_use_classification`. This function is powered by the Planetary Computer's STAC catalog and, by default, uses the [10m Annual Land Use Land Cover (9-class) V2](https://planetarycomputer.microsoft.com/dataset/io-lulc-annual-v02) dataset (\"io-lulc-annual-v02\"). However, alternative collections can be specified as arguments to the function.\n"
   ]
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  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "Help on function land_use_classification in module xhydro.gis:\n",
      "\n",
      "land_use_classification(\n",
      "    gdf: 'gpd.GeoDataFrame',\n",
      "    *,\n",
      "    unique_id: 'str | None' = None,\n",
      "    collection='io-lulc-annual-v02',\n",
      "    year: 'str | int' = 'latest',\n",
      "    output_format: \"Literal['xarray', 'xr.Dataset', 'geopandas', 'gpd.GeoDataFrame']\" = 'geopandas'\n",
      ") -> 'gpd.GeoDataFrame | xr.Dataset'\n",
      "    Calculate land use classification.\n",
      "\n",
      "    Calculate land use classification for each polygon from a gpd.GeoDataFrame. By default,\n",
      "    the classes are generated from the Planetary Computer's STAC catalog using the\n",
      "    `10m Annual Land Use Land Cover` dataset.\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    gdf : gpd.GeoDataFrame\n",
      "        GeoDataFrame containing watershed polygons. Must have a defined .crs attribute.\n",
      "    unique_id : str\n",
      "        GeoDataFrame containing watershed polygons. Must have a defined .crs attribute.\n",
      "    collection : str\n",
      "        Collection name from the Planetary Computer STAC Catalog.\n",
      "    year : str | int\n",
      "        Land use dataset year between 2017 and 2022.\n",
      "    output_format : str\n",
      "        One of either `xarray` (or `xr.Dataset`) or `geopandas` (or `gpd.GeoDataFrame`).\n",
      "\n",
      "    Returns\n",
      "    -------\n",
      "    gpd.GeoDataFrame or xr.Dataset\n",
      "        Output dataset containing the watershed properties.\n",
      "\n",
      "    Warnings\n",
      "    --------\n",
      "    This function relies on the Microsoft Planetary Computer's STAC Catalog to retrieve the Digital Elevation Model (DEM) data.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(xhgis.land_use_classification)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
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       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 168B\n",
       "Dimensions:                 (HYBAS_ID: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID                (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "    spatial_ref             int64 8B 0\n",
       "Data variables:\n",
       "    pct_trees               (HYBAS_ID) float64 16B 0.9088 0.5992\n",
       "    pct_rangeland           (HYBAS_ID) float64 16B 0.05135 0.08354\n",
       "    pct_water               (HYBAS_ID) float64 16B 0.02159 0.002957\n",
       "    pct_built_area          (HYBAS_ID) float64 16B 0.01713 0.03685\n",
       "    pct_snow/ice            (HYBAS_ID) float64 16B 0.0005296 0.0002937\n",
       "    pct_crops               (HYBAS_ID) float64 16B 0.0002972 0.277\n",
       "    pct_flooded_vegetation  (HYBAS_ID) float64 16B 0.0001879 0.0\n",
       "    pct_bare_ground         (HYBAS_ID) float64 16B 0.0001111 6.814e-05\n",
       "    pct_clouds              (HYBAS_ID) float64 16B 0.0 5.926e-05\n",
       "Attributes:\n",
       "    year:                2023\n",
       "    collection:          io-lulc-annual-v02\n",
       "    spatial_resolution:  10.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4fd0f3d5-772b-410d-b9e5-83f41ed4a82b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4fd0f3d5-772b-410d-b9e5-83f41ed4a82b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>HYBAS_ID</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-dd536088-9e8d-45a5-b490-676347c0ad58' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dd536088-9e8d-45a5-b490-676347c0ad58' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>HYBAS_ID</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>7120034480 7120365812</div><input id='attrs-4b11d1c8-6bcf-47d4-9389-b6285636a7ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b11d1c8-6bcf-47d4-9389-b6285636a7ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac8a3359-5ae9-4aee-82cb-f7b923092141' class='xr-var-data-in' type='checkbox'><label for='data-ac8a3359-5ae9-4aee-82cb-f7b923092141' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>HYBAS_ID</dd><dt><span>cf_role :</span></dt><dd>timeseries_id</dd></dl></div><div class='xr-var-data'><pre>array([7120034480, 7120365812])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-522a0fbc-6121-4c91-8d32-7248dee1250b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-522a0fbc-6121-4c91-8d32-7248dee1250b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e7b85f0-1458-4df5-9faa-c874935fa364' class='xr-var-data-in' type='checkbox'><label for='data-3e7b85f0-1458-4df5-9faa-c874935fa364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 19N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-69],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32619&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 19N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-69.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 19N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-69],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32619&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>327810.0 10.0 0.0 5275830.0 0.0 -10.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-372597b7-39d6-43a9-99dc-49817ec4cb22' class='xr-section-summary-in' type='checkbox'  checked><label for='section-372597b7-39d6-43a9-99dc-49817ec4cb22' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>pct_trees</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9088 0.5992</div><input id='attrs-51f42ad0-2bbf-490f-a8f7-f6524905670f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51f42ad0-2bbf-490f-a8f7-f6524905670f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fe6f67d-f5ee-4e5c-ace7-00d4e5b26ba7' class='xr-var-data-in' type='checkbox'><label for='data-2fe6f67d-f5ee-4e5c-ace7-00d4e5b26ba7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([0.90880738, 0.5992189 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_rangeland</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.05135 0.08354</div><input id='attrs-9a36116e-175e-41d4-a0c7-18996c255e33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a36116e-175e-41d4-a0c7-18996c255e33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b6f1bd1-3443-4dea-b559-b50f421bfece' class='xr-var-data-in' type='checkbox'><label for='data-8b6f1bd1-3443-4dea-b559-b50f421bfece' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([0.05134534, 0.08354355])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_water</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02159 0.002957</div><input id='attrs-defe2007-12ea-462e-9ec4-92086673429c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-defe2007-12ea-462e-9ec4-92086673429c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a86cdb1-9ad7-4c8e-a3c9-cf6d480d17ca' class='xr-var-data-in' type='checkbox'><label for='data-5a86cdb1-9ad7-4c8e-a3c9-cf6d480d17ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([0.02158885, 0.0029574 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_built_area</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.01713 0.03685</div><input id='attrs-35f83494-31a0-49c5-b09d-64309078963a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35f83494-31a0-49c5-b09d-64309078963a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4da4a38-5761-4328-81a8-ffeaf932078e' class='xr-var-data-in' type='checkbox'><label for='data-f4da4a38-5761-4328-81a8-ffeaf932078e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([0.01713266, 0.0368483 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_snow/ice</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0005296 0.0002937</div><input id='attrs-fc389c9b-0e09-4ab9-8e5d-e5ab6970c22d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc389c9b-0e09-4ab9-8e5d-e5ab6970c22d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1733cbd-b8ef-4018-9da2-5d2bf4f7540a' class='xr-var-data-in' type='checkbox'><label for='data-e1733cbd-b8ef-4018-9da2-5d2bf4f7540a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([0.00052958, 0.00029372])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_crops</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0002972 0.277</div><input id='attrs-a3a5d06d-d98d-42ca-b506-88292633b3a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3a5d06d-d98d-42ca-b506-88292633b3a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df22b814-c16d-4434-9d74-ccfdba6fa863' class='xr-var-data-in' type='checkbox'><label for='data-df22b814-c16d-4434-9d74-ccfdba6fa863' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([0.00029719, 0.27701073])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_flooded_vegetation</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0001879 0.0</div><input id='attrs-d2d0457f-5f90-43f8-bafd-6a7cd6758e2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2d0457f-5f90-43f8-bafd-6a7cd6758e2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ca34094-ebd1-4dd7-a2d2-e73eb5623865' class='xr-var-data-in' type='checkbox'><label for='data-8ca34094-ebd1-4dd7-a2d2-e73eb5623865' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([0.00018793, 0.        ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_bare_ground</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0001111 6.814e-05</div><input id='attrs-13714369-7d10-4dce-bfb7-a9983b8dcdc6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13714369-7d10-4dce-bfb7-a9983b8dcdc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e3ac3f8-0402-483a-a6dd-c9657e08f367' class='xr-var-data-in' type='checkbox'><label for='data-4e3ac3f8-0402-483a-a6dd-c9657e08f367' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([1.11068650e-04, 6.81373403e-05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_clouds</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 5.926e-05</div><input id='attrs-205a401d-89ab-43ad-8f28-1eb2d9c132c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-205a401d-89ab-43ad-8f28-1eb2d9c132c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa57e8f7-b856-4f0a-a1ae-8ea2630c56ed' class='xr-var-data-in' type='checkbox'><label for='data-aa57e8f7-b856-4f0a-a1ae-8ea2630c56ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:02] : Calculated land_use_classification - xhydro version: 0.6.2-dev.8</dd></dl></div><div class='xr-var-data'><pre>array([0.00000000e+00, 5.92572859e-05])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f78abe2a-c805-4df9-a946-592a9226e7a6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f78abe2a-c805-4df9-a946-592a9226e7a6' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>year :</span></dt><dd>2023</dd><dt><span>collection :</span></dt><dd>io-lulc-annual-v02</dd><dt><span>spatial_resolution :</span></dt><dd>10.0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 168B\n",
       "Dimensions:                 (HYBAS_ID: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID                (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "    spatial_ref             int64 8B 0\n",
       "Data variables:\n",
       "    pct_trees               (HYBAS_ID) float64 16B 0.9088 0.5992\n",
       "    pct_rangeland           (HYBAS_ID) float64 16B 0.05135 0.08354\n",
       "    pct_water               (HYBAS_ID) float64 16B 0.02159 0.002957\n",
       "    pct_built_area          (HYBAS_ID) float64 16B 0.01713 0.03685\n",
       "    pct_snow/ice            (HYBAS_ID) float64 16B 0.0005296 0.0002937\n",
       "    pct_crops               (HYBAS_ID) float64 16B 0.0002972 0.277\n",
       "    pct_flooded_vegetation  (HYBAS_ID) float64 16B 0.0001879 0.0\n",
       "    pct_bare_ground         (HYBAS_ID) float64 16B 0.0001111 6.814e-05\n",
       "    pct_clouds              (HYBAS_ID) float64 16B 0.0 5.926e-05\n",
       "Attributes:\n",
       "    year:                2023\n",
       "    collection:          io-lulc-annual-v02\n",
       "    spatial_resolution:  10.0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = xhgis.land_use_classification(gdf, unique_id=\"HYBAS_ID\", output_format=\"xarray\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = xhgis.land_use_plot(gdf, unique_id=\"HYBAS_ID\", idx=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### d) Climate indicators\n",
    "\n",
    "The extraction of climate indicators is the most complex step, as it requires accessing a weather dataset, then subsetting and averaging the data over the various watersheds within the `GeoDataFrame` object. These steps are outside the scope of `xHydro`, and users will need to rely on other libraries for this task. One approach, outlined in the [Use Case Example](use_case.ipynb), involves using a combination of `xscen` and `xESMF`. Another approach, demonstrated here, utilizes `xdatasets`. Indeed, `xdatasets` enables the extraction of all the pixels from a gridded dataset within a watershed while accounting for the weighting of each pixel intersecting the watershed.\n",
    "\n",
    "For this example, we will use ERA5-Land reanalysis data covering the period from 1981 to 2010 as our climatological dataset.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Temporal operations: processing tp with era5_land_reanalysis: 100%|██████████| 2/2 [00:00<00:00, 34.55it/s]\n"
     ]
    }
   ],
   "source": [
    "datasets = {\n",
    "    \"era5_land_reanalysis\": {\"variables\": [\"t2m\", \"tp\"]},\n",
    "}\n",
    "space = {\n",
    "    \"clip\": \"polygon\",  # bbox, point or polygon\n",
    "    \"averaging\": True,\n",
    "    \"geometry\": gdf,\n",
    "    \"unique_id\": \"HYBAS_ID\",\n",
    "}\n",
    "time = {\n",
    "    \"start\": \"1981-01-01\",\n",
    "    \"end\": \"1982-12-31\",\n",
    "    \"timezone\": \"America/Montreal\",\n",
    "    \"timestep\": \"D\",\n",
    "    \"aggregation\": {\"tp\": np.nansum, \"t2m\": np.nanmean},\n",
    "}\n",
    "\n",
    "ds = xdatasets.Query(datasets=datasets, space=space, time=time).data.squeeze()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because the next steps utilize [xclim](https://xclim.readthedocs.io/en/stable/index.html) under the hood, the dataset must be [CF-compliant](https://cfconventions.org/cf-conventions/cf-conventions.html). At a minimum, the `xarray.DataArray` used should adhere to the following principles:\n",
    "\n",
    "- The dataset must include a `time` dimension, typically at a daily frequency, with no missing timesteps (although NaNs are supported). If your data deviates from this format, extra caution should be taken when interpreting the results.\n",
    "- If there is a 1D spatial dimension, such as `HYBAS_ID` in the example below, it must have an attribute `cf_role` with the value `timeseries_id`.\n",
    "- The variable must include at least a `units` attribute. While not mandatory, other attributes such as `long_name` and `cell_methods` are expected by `xclim`, and warnings will be raised if they are missing.\n",
    "- Variable names should match those supported by `xclim`.\n",
    "\n",
    "The following code will format the ERA5-Land data obtained from `xdatasets` to add missing metadata and change the variable names and units:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
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       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "  line-height: 1.6;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 29kB\n",
       "Dimensions:      (HYBAS_ID: 2, time: 730)\n",
       "Coordinates:\n",
       "  * HYBAS_ID     (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "  * time         (time) datetime64[ns] 6kB 1981-01-01 1981-01-02 ... 1982-12-31\n",
       "    spatial_agg  &lt;U7 28B &#x27;polygon&#x27;\n",
       "    timestep     &lt;U1 4B &#x27;D&#x27;\n",
       "    source       &lt;U20 80B &#x27;era5_land_reanalysis&#x27;\n",
       "Data variables:\n",
       "    tas          (HYBAS_ID, time) float64 12kB -19.64 -15.9 ... -6.387 -5.33\n",
       "    pr           (HYBAS_ID, time) float64 12kB 0.01237 3.258 ... 0.07566 0.176\n",
       "Attributes: (12/30)\n",
       "    GRIB_NV:                                  0\n",
       "    GRIB_Nx:                                  1171\n",
       "    GRIB_Ny:                                  701\n",
       "    GRIB_cfName:                              unknown\n",
       "    GRIB_cfVarName:                           t2m\n",
       "    GRIB_dataType:                            fc\n",
       "    ...                                       ...\n",
       "    GRIB_totalNumber:                         0\n",
       "    GRIB_typeOfLevel:                         surface\n",
       "    GRIB_units:                               K\n",
       "    long_name:                                2 metre temperature\n",
       "    standard_name:                            unknown\n",
       "    units:                                    K</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7f023d8a-017a-40b7-9b0a-f61f0552b280' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7f023d8a-017a-40b7-9b0a-f61f0552b280' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>HYBAS_ID</span>: 2</li><li><span class='xr-has-index'>time</span>: 730</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7d7c790f-1306-4532-bada-54257cd834a3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d7c790f-1306-4532-bada-54257cd834a3' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>HYBAS_ID</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>7120034480 7120365812</div><input id='attrs-cbdb459c-4a86-4f0e-a897-fefd80da0b6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbdb459c-4a86-4f0e-a897-fefd80da0b6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d83fc5a3-17a2-4117-b09b-a5c926401373' class='xr-var-data-in' type='checkbox'><label for='data-d83fc5a3-17a2-4117-b09b-a5c926401373' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cf_role :</span></dt><dd>timeseries_id</dd></dl></div><div class='xr-var-data'><pre>array([7120034480, 7120365812])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-01-01 ... 1982-12-31</div><input id='attrs-e0a2b59e-4c64-459b-9ed0-b868de7fc053' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0a2b59e-4c64-459b-9ed0-b868de7fc053' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9663648-46f3-4abc-8ed1-e1f27d1bea9c' class='xr-var-data-in' type='checkbox'><label for='data-c9663648-46f3-4abc-8ed1-e1f27d1bea9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-01-03T00:00:00.000000000&#x27;, ..., &#x27;1982-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-12-30T00:00:00.000000000&#x27;, &#x27;1982-12-31T00:00:00.000000000&#x27;],\n",
       "      shape=(730,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_agg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;polygon&#x27;</div><input id='attrs-690820e2-626c-46c4-8569-054bb4f3a65e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-690820e2-626c-46c4-8569-054bb4f3a65e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe7ede75-4596-4310-bfc7-6748d05caa8a' class='xr-var-data-in' type='checkbox'><label for='data-fe7ede75-4596-4310-bfc7-6748d05caa8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;polygon&#x27;, dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timestep</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;D&#x27;</div><input id='attrs-2fb26866-8ed4-4dd3-aa90-6dcaca2479ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2fb26866-8ed4-4dd3-aa90-6dcaca2479ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32b4954d-2a94-4310-afd4-878622f543b8' class='xr-var-data-in' type='checkbox'><label for='data-32b4954d-2a94-4310-afd4-878622f543b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;D&#x27;, dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;era5_land_reanalysis&#x27;</div><input id='attrs-bc1d58fa-f250-426f-be26-35eac36e0012' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bc1d58fa-f250-426f-be26-35eac36e0012' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-400adb1d-36b0-488e-888b-b91a22c0c4d8' class='xr-var-data-in' type='checkbox'><label for='data-400adb1d-36b0-488e-888b-b91a22c0c4d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;era5_land_reanalysis&#x27;, dtype=&#x27;&lt;U20&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-56616563-2165-4f83-9a74-1b3d3ba5473c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-56616563-2165-4f83-9a74-1b3d3ba5473c' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-19.64 -15.9 ... -6.387 -5.33</div><input id='attrs-679905ba-df1e-4435-aa3d-6faacd53ca2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-679905ba-df1e-4435-aa3d-6faacd53ca2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e654314b-ce2d-4351-b60e-61155480e364' class='xr-var-data-in' type='checkbox'><label for='data-e654314b-ce2d-4351-b60e-61155480e364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><pre>array([[-19.63824662, -15.89966346, -32.07008162, ...,  -3.17191403,\n",
       "        -14.87888952, -12.18083874],\n",
       "       [-20.1518098 , -13.11810535, -29.14483026, ...,   1.7140714 ,\n",
       "         -6.38717805,  -5.33026845]], shape=(2, 730))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.01237 3.258 ... 0.07566 0.176</div><input id='attrs-dc2a8085-05f4-4e7e-ba32-490afd258316' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc2a8085-05f4-4e7e-ba32-490afd258316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dada6bb2-7be9-4c53-b99b-ba5d176686c0' class='xr-var-data-in' type='checkbox'><label for='data-dada6bb2-7be9-4c53-b99b-ba5d176686c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tp</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>228</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>mm d-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean within days</dd></dl></div><div class='xr-var-data'><pre>array([[1.23723656e-02, 3.25842999e+00, 1.30195811e-01, ...,\n",
       "        3.04214460e+00, 9.30810394e-02, 4.57786940e-01],\n",
       "       [1.72042129e-03, 4.13432726e+00, 1.58362256e-01, ...,\n",
       "        6.67760769e-01, 7.56617318e-02, 1.75986502e-01]], shape=(2, 730))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-074b0067-f332-4322-86f0-22f70a66e90c' class='xr-section-summary-in' type='checkbox'  ><label for='section-074b0067-f332-4322-86f0-22f70a66e90c' class='xr-section-summary' >Attributes: <span>(30)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>K</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 29kB\n",
       "Dimensions:      (HYBAS_ID: 2, time: 730)\n",
       "Coordinates:\n",
       "  * HYBAS_ID     (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "  * time         (time) datetime64[ns] 6kB 1981-01-01 1981-01-02 ... 1982-12-31\n",
       "    spatial_agg  <U7 28B 'polygon'\n",
       "    timestep     <U1 4B 'D'\n",
       "    source       <U20 80B 'era5_land_reanalysis'\n",
       "Data variables:\n",
       "    tas          (HYBAS_ID, time) float64 12kB -19.64 -15.9 ... -6.387 -5.33\n",
       "    pr           (HYBAS_ID, time) float64 12kB 0.01237 3.258 ... 0.07566 0.176\n",
       "Attributes: (12/30)\n",
       "    GRIB_NV:                                  0\n",
       "    GRIB_Nx:                                  1171\n",
       "    GRIB_Ny:                                  701\n",
       "    GRIB_cfName:                              unknown\n",
       "    GRIB_cfVarName:                           t2m\n",
       "    GRIB_dataType:                            fc\n",
       "    ...                                       ...\n",
       "    GRIB_totalNumber:                         0\n",
       "    GRIB_typeOfLevel:                         surface\n",
       "    GRIB_units:                               K\n",
       "    long_name:                                2 metre temperature\n",
       "    standard_name:                            unknown\n",
       "    units:                                    K"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = ds.rename({\"t2m_nanmean\": \"tas\", \"tp_nansum\": \"pr\"})\n",
    "ds[\"tas\"] = xclim.core.units.convert_units_to(ds[\"tas\"], \"degC\")\n",
    "ds[\"tas\"].attrs.update({\"cell_methods\": \"time: mean\"})\n",
    "\n",
    "ds[\"pr\"].attrs.update({\"units\": \"m d-1\", \"cell_methods\": \"time: mean within days\"})\n",
    "ds[\"pr\"] = xclim.core.units.convert_units_to(ds[\"pr\"], \"mm d-1\")\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Climate indicators can be calculated in various ways, and for most simple tasks, directly using `xclim` is always a viable option. `xclim` offers an extensive [list of available indicators](https://xclim.readthedocs.io/en/stable/indicators.html) within a user-friendly and flexible framework.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tg_max&#x27; (HYBAS_ID: 2, time: 2)&gt; Size: 32B\n",
       "array([[292.65401005, 295.1619582 ],\n",
       "       [296.13479571, 298.57350323]])\n",
       "Coordinates:\n",
       "  * HYBAS_ID     (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "  * time         (time) datetime64[ns] 16B 1981-01-01 1982-01-01\n",
       "    spatial_agg  &lt;U7 28B &#x27;polygon&#x27;\n",
       "    timestep     &lt;U1 4B &#x27;D&#x27;\n",
       "    source       &lt;U20 80B &#x27;era5_land_reanalysis&#x27;\n",
       "Attributes:\n",
       "    units:           K\n",
       "    units_metadata:  temperature: unknown\n",
       "    cell_methods:    time: mean time: maximum over days\n",
       "    history:         [2026-02-19 14:33:32] tg_max: TG_MAX(tas=tas, freq=&#x27;YS&#x27;)...\n",
       "    standard_name:   air_temperature\n",
       "    long_name:       Maximum daily mean temperature\n",
       "    description:     Annual maximum of daily mean temperature.</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;tg_max&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>HYBAS_ID</span>: 2</li><li><span class='xr-has-index'>time</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-18103319-70b2-4128-bdee-e9a542cf9b3d' class='xr-array-in' type='checkbox' checked><label for='section-18103319-70b2-4128-bdee-e9a542cf9b3d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>292.7 295.2 296.1 298.6</span></div><div class='xr-array-data'><pre>array([[292.65401005, 295.1619582 ],\n",
       "       [296.13479571, 298.57350323]])</pre></div></div></li><li class='xr-section-item'><input id='section-442ca46e-b94a-46e3-980f-ac1cceded095' class='xr-section-summary-in' type='checkbox'  checked><label for='section-442ca46e-b94a-46e3-980f-ac1cceded095' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>HYBAS_ID</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>7120034480 7120365812</div><input id='attrs-c0cafae8-7666-46b3-9410-ba98df80501b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0cafae8-7666-46b3-9410-ba98df80501b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31f98525-6647-4b20-8045-7e89c38d99fe' class='xr-var-data-in' type='checkbox'><label for='data-31f98525-6647-4b20-8045-7e89c38d99fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([7120034480, 7120365812])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-01-01 1982-01-01</div><input id='attrs-f240b3c2-c928-4e76-8750-6cef090d198e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f240b3c2-c928-4e76-8750-6cef090d198e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-390152a3-8120-4bb3-9b01-b5887c6c8c33' class='xr-var-data-in' type='checkbox'><label for='data-390152a3-8120-4bb3-9b01-b5887c6c8c33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1982-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_agg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;polygon&#x27;</div><input id='attrs-8d301083-1f9f-4ccb-9fdd-24b12dec7217' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8d301083-1f9f-4ccb-9fdd-24b12dec7217' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f09786e-7d1d-4308-96c6-2ba6d792f1a1' class='xr-var-data-in' type='checkbox'><label for='data-3f09786e-7d1d-4308-96c6-2ba6d792f1a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;polygon&#x27;, dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timestep</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;D&#x27;</div><input id='attrs-decdedd1-a9f9-48d3-88fa-90e40f204b61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-decdedd1-a9f9-48d3-88fa-90e40f204b61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b5edf63-2984-40c4-bec8-aee3a74e8847' class='xr-var-data-in' type='checkbox'><label for='data-2b5edf63-2984-40c4-bec8-aee3a74e8847' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;D&#x27;, dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;era5_land_reanalysis&#x27;</div><input id='attrs-978ffe62-d714-44c3-8d82-d9ef698eb903' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-978ffe62-d714-44c3-8d82-d9ef698eb903' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32f11373-62a8-4081-9d4d-52713384d170' class='xr-var-data-in' type='checkbox'><label for='data-32f11373-62a8-4081-9d4d-52713384d170' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;era5_land_reanalysis&#x27;, dtype=&#x27;&lt;U20&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bf0b6951-2d88-4ea1-9d46-a565fc56e177' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bf0b6951-2d88-4ea1-9d46-a565fc56e177' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean time: maximum over days</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tg_max: TG_MAX(tas=tas, freq=&#x27;YS&#x27;) with options check_missing=any - xclim version: 0.58.1</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Maximum daily mean temperature</dd><dt><span>description :</span></dt><dd>Annual maximum of daily mean temperature.</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'tg_max' (HYBAS_ID: 2, time: 2)> Size: 32B\n",
       "array([[292.65401005, 295.1619582 ],\n",
       "       [296.13479571, 298.57350323]])\n",
       "Coordinates:\n",
       "  * HYBAS_ID     (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "  * time         (time) datetime64[ns] 16B 1981-01-01 1982-01-01\n",
       "    spatial_agg  <U7 28B 'polygon'\n",
       "    timestep     <U1 4B 'D'\n",
       "    source       <U20 80B 'era5_land_reanalysis'\n",
       "Attributes:\n",
       "    units:           K\n",
       "    units_metadata:  temperature: unknown\n",
       "    cell_methods:    time: mean time: maximum over days\n",
       "    history:         [2026-02-19 14:33:32] tg_max: TG_MAX(tas=tas, freq='YS')...\n",
       "    standard_name:   air_temperature\n",
       "    long_name:       Maximum daily mean temperature\n",
       "    description:     Annual maximum of daily mean temperature."
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xclim.atmos.tg_max(ds.tas)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For more complex tasks, or when computing multiple indicators simultaneously, `xhydro.indicators.compute_indicators` is often the preferred method. This function allows users to build and pass multiple indicators at once, either by providing a list of custom indicators created with `xclim.core.indicator.Indicator.from_dict` (see the INFO box below) or by referencing a YAML file (see [the `xscen` documentation](https://xscen.readthedocs.io/en/latest/notebooks/2_getting_started.html#Computing-indicators)).\n",
    "\n",
    "\n",
    "<div class=\"alert alert-info\"> <b>INFO</b>\n",
    "\n",
    "Custom indicators in `xHydro` are built by following the YAML formatting required by `xclim`.\n",
    "\n",
    "A custom indicator built using `xclim.core.indicator.Indicator.from_dict` will need these elements:\n",
    "\n",
    "- \"data\": A dictionary with the following information:\n",
    "  - \"base\": The \"YAML ID\" obtained from [here](https://xclim.readthedocs.io/en/stable/indicators.html).\n",
    "  - \"input\": A dictionary linking the default xclim input to the name of your variable. Needed only if it is different. In the link above, they are the string following \"Uses:\".\n",
    "  - \"parameters\": A dictionary containing all other parameters for a given indicator. In the link above, the easiest way to access them is by clicking the link in the top-right corner of the box describing a given indicator.\n",
    "  - More entries can be used here, as described [in the xclim documentation](https://xclim.readthedocs.io/en/latest/api.html#yaml-file-structure) under \"identifier\".\n",
    "- \"identifier\": A custom name for your indicator. This will be the name returned in the results.\n",
    "- \"module\": Needed, but can be anything. To prevent an accidental overwriting of `xclim` indicators, it is best to use something different from: [\"atmos\", \"land\", \"generic\"].\n",
    "\n",
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     "text": [
      "Help on function compute_indicators in module xscen.indicators:\n",
      "\n",
      "compute_indicators(\n",
      "    ds: xarray.core.dataset.Dataset,\n",
      "    indicators: str | os.PathLike | collections.abc.Sequence[xclim.core.indicator.Indicator] | collections.abc.Sequence[tuple[str, xclim.core.indicator.Indicator]] | module,\n",
      "    *,\n",
      "    periods: list[str] | list[list[str]] | None = None,\n",
      "    restrict_years: bool = True,\n",
      "    to_level: str | None = 'indicators',\n",
      "    rechunk_input: bool = False\n",
      ") -> dict\n",
      "    Calculate variables and indicators based on a YAML call to xclim.\n",
      "\n",
      "    The function cuts the output to be the same years as the inputs.\n",
      "    Hence, if an indicator creates a timestep outside the original year range (e.g. the first DJF for QS-DEC),\n",
      "    it will not appear in the output.\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    ds : xr.Dataset\n",
      "        Dataset to use for the indicators.\n",
      "    indicators : str | os.PathLike | Sequence[Indicator] | Sequence[tuple[str, Indicator]] | ModuleType\n",
      "        Path to a YAML file that instructs on how to calculate missing variables.\n",
      "        Can also be only the \"stem\", if translations and custom indices are implemented.\n",
      "        Can be the indicator module directly, or a sequence of indicators or a sequence of\n",
      "        tuples (indicator name, indicator) as returned by `iter_indicators()`.\n",
      "    periods : list of str or list of lists of str, optional\n",
      "        Either [start, end] or list of [start, end] of continuous periods over which to compute the indicators.\n",
      "        This is needed when the time axis of ds contains some jumps in time.\n",
      "        If None, the dataset will be considered continuous.\n",
      "    restrict_years : bool\n",
      "        If True, cut the time axis to be within the same years as the input.\n",
      "        This is mostly useful for frequencies that do not start in January, such as QS-DEC.\n",
      "        In that instance, `xclim` would start on previous_year-12-01 (DJF), with a NaN.\n",
      "        `restrict_years` will cut that first timestep. This should have no effect on YS and MS indicators.\n",
      "    to_level : str, optional\n",
      "        The processing level to assign to the output.\n",
      "        If None, the processing level of the inputs is preserved.\n",
      "    rechunk_input : bool\n",
      "        If True, the dataset is rechunked with :py:func:`flox.xarray.rechunk_for_blockwise`\n",
      "        according to the resampling frequency of the indicator. Each rechunking is done\n",
      "        once per frequency with :py:func:`xscen.utils.rechunk_for_resample`.\n",
      "\n",
      "    Returns\n",
      "    -------\n",
      "    dict\n",
      "        Dictionary (keys = timedeltas) with indicators separated by temporal resolution.\n",
      "\n",
      "    See Also\n",
      "    --------\n",
      "    xclim.indicators, xclim.core.indicator.build_indicator_module_from_yaml\n",
      "\n"
     ]
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   "source": [
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       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 208B\n",
       "Dimensions:        (HYBAS_ID: 2, time: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID       (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "  * time           (time) datetime64[ns] 16B 1981-01-01 1982-01-01\n",
       "    spatial_agg    &lt;U7 28B &#x27;polygon&#x27;\n",
       "    timestep       &lt;U1 4B &#x27;D&#x27;\n",
       "    source         &lt;U20 80B &#x27;era5_land_reanalysis&#x27;\n",
       "Data variables:\n",
       "    tg_max_summer  (HYBAS_ID, time) float64 32B 292.7 295.2 296.1 298.6\n",
       "    wet5mm         (HYBAS_ID, time) float64 32B 85.0 83.0 80.0 78.0\n",
       "Attributes: (12/34)\n",
       "    GRIB_NV:                                  0\n",
       "    GRIB_Nx:                                  1171\n",
       "    GRIB_Ny:                                  701\n",
       "    GRIB_cfName:                              unknown\n",
       "    GRIB_cfVarName:                           t2m\n",
       "    GRIB_dataType:                            fc\n",
       "    ...                                       ...\n",
       "    standard_name:                            unknown\n",
       "    units:                                    K\n",
       "    cat:xrfreq:                               YS-JAN\n",
       "    cat:frequency:                            yr\n",
       "    cat:processing_level:                     indicators\n",
       "    cat:variable:                             (&#x27;tg_max_summer&#x27;, &#x27;wet5mm&#x27;)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-40d14373-5624-481e-af91-6cd4e29e25e0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-40d14373-5624-481e-af91-6cd4e29e25e0' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>HYBAS_ID</span>: 2</li><li><span class='xr-has-index'>time</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-cec39d25-551a-4c37-bd48-aeac8996e5db' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cec39d25-551a-4c37-bd48-aeac8996e5db' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>HYBAS_ID</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>7120034480 7120365812</div><input id='attrs-ef7ecf5e-35ce-4fcb-b2af-f333def7802b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef7ecf5e-35ce-4fcb-b2af-f333def7802b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39605835-adb1-4d13-bfde-763e745d4808' class='xr-var-data-in' type='checkbox'><label for='data-39605835-adb1-4d13-bfde-763e745d4808' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cf_role :</span></dt><dd>timeseries_id</dd></dl></div><div class='xr-var-data'><pre>array([7120034480, 7120365812])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-01-01 1982-01-01</div><input id='attrs-5bac293f-3447-443b-9b0f-6428dcbf0cd4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5bac293f-3447-443b-9b0f-6428dcbf0cd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44084a19-82a1-4a75-862c-e4d89e145359' class='xr-var-data-in' type='checkbox'><label for='data-44084a19-82a1-4a75-862c-e4d89e145359' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1982-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_agg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;polygon&#x27;</div><input id='attrs-ba7470d4-f376-4d44-b29e-a9098ca871e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba7470d4-f376-4d44-b29e-a9098ca871e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-628f7b23-1e9a-47d7-82bb-c5f8b120a744' class='xr-var-data-in' type='checkbox'><label for='data-628f7b23-1e9a-47d7-82bb-c5f8b120a744' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;polygon&#x27;, dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timestep</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;D&#x27;</div><input id='attrs-1ef00e8d-76cf-4def-8f94-5789c84478f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ef00e8d-76cf-4def-8f94-5789c84478f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7d38e59-71ab-4f77-8c55-7ecfd80a280d' class='xr-var-data-in' type='checkbox'><label for='data-b7d38e59-71ab-4f77-8c55-7ecfd80a280d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;D&#x27;, dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;era5_land_reanalysis&#x27;</div><input id='attrs-65b87cab-9cfa-4313-8096-e1affbc7c811' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-65b87cab-9cfa-4313-8096-e1affbc7c811' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0de19b6-cb94-4674-bcb9-12039048d3a9' class='xr-var-data-in' type='checkbox'><label for='data-e0de19b6-cb94-4674-bcb9-12039048d3a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;era5_land_reanalysis&#x27;, dtype=&#x27;&lt;U20&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-673e3174-7dd4-412d-97f5-2590ad48005e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-673e3174-7dd4-412d-97f5-2590ad48005e' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tg_max_summer</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>292.7 295.2 296.1 298.6</div><input id='attrs-f1aa03cd-18a3-451c-98cc-455fcface49c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1aa03cd-18a3-451c-98cc-455fcface49c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bac6d0f-3836-4abd-a72d-f7c0abcc57e2' class='xr-var-data-in' type='checkbox'><label for='data-0bac6d0f-3836-4abd-a72d-f7c0abcc57e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean time: maximum over days</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tg_max_summer: example.TG_MAX_SUMMER(tas=tas, freq=&#x27;YS&#x27;) with options check_missing=any - xclim version: 0.58.1</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Maximum daily mean temperature</dd><dt><span>description :</span></dt><dd>Annual maximum of daily mean temperature.</dd></dl></div><div class='xr-var-data'><pre>array([[292.65401005, 295.1619582 ],\n",
       "       [296.13479571, 298.57350323]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet5mm</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>85.0 83.0 80.0 78.0</div><input id='attrs-dcb56dd9-e886-413c-8170-5d5e7e92b4c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcb56dd9-e886-413c-8170-5d5e7e92b4c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2a71e12-4c0e-4c04-9659-1f3decac4e05' class='xr-var-data-in' type='checkbox'><label for='data-c2a71e12-4c0e-4c04-9659-1f3decac4e05' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>days</dd><dt><span>cell_methods :</span></dt><dd>time: mean within days time: sum over days</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] wet5mm: example.WET5MM(pr=pr, freq=&#x27;YS&#x27;, op=&#x27;&gt;=&#x27;) with options check_missing=any - xclim version: 0.58.1</dd><dt><span>standard_name :</span></dt><dd>number_of_days_with_lwe_thickness_of_precipitation_amount_at_or_above_threshold</dd><dt><span>long_name :</span></dt><dd>Number of days with daily precipitation at or above 5 mm d-1</dd><dt><span>description :</span></dt><dd>Annual number of days with daily precipitation at or above 5 mm d-1.</dd></dl></div><div class='xr-var-data'><pre>array([[85., 83.],\n",
       "       [80., 78.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-41f2cfa3-5101-4bd7-894c-671a2c5518bc' class='xr-section-summary-in' type='checkbox'  ><label for='section-41f2cfa3-5101-4bd7-894c-671a2c5518bc' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cat:xrfreq :</span></dt><dd>YS-JAN</dd><dt><span>cat:frequency :</span></dt><dd>yr</dd><dt><span>cat:processing_level :</span></dt><dd>indicators</dd><dt><span>cat:variable :</span></dt><dd>(&#x27;tg_max_summer&#x27;, &#x27;wet5mm&#x27;)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 208B\n",
       "Dimensions:        (HYBAS_ID: 2, time: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID       (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "  * time           (time) datetime64[ns] 16B 1981-01-01 1982-01-01\n",
       "    spatial_agg    <U7 28B 'polygon'\n",
       "    timestep       <U1 4B 'D'\n",
       "    source         <U20 80B 'era5_land_reanalysis'\n",
       "Data variables:\n",
       "    tg_max_summer  (HYBAS_ID, time) float64 32B 292.7 295.2 296.1 298.6\n",
       "    wet5mm         (HYBAS_ID, time) float64 32B 85.0 83.0 80.0 78.0\n",
       "Attributes: (12/34)\n",
       "    GRIB_NV:                                  0\n",
       "    GRIB_Nx:                                  1171\n",
       "    GRIB_Ny:                                  701\n",
       "    GRIB_cfName:                              unknown\n",
       "    GRIB_cfVarName:                           t2m\n",
       "    GRIB_dataType:                            fc\n",
       "    ...                                       ...\n",
       "    standard_name:                            unknown\n",
       "    units:                                    K\n",
       "    cat:xrfreq:                               YS-JAN\n",
       "    cat:frequency:                            yr\n",
       "    cat:processing_level:                     indicators\n",
       "    cat:variable:                             ('tg_max_summer', 'wet5mm')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indicators = [\n",
    "    # Maximum summer temperature\n",
    "    xclim.core.indicator.Indicator.from_dict(\n",
    "        data={\n",
    "            \"base\": \"tg_max\",\n",
    "            \"parameters\": {\"indexer\": {\"month\": [6, 7, 8]}},\n",
    "        },\n",
    "        identifier=\"tg_max_summer\",\n",
    "        module=\"example\",\n",
    "    ),\n",
    "    # Number of days with more than 5 mm of precipitation\n",
    "    xclim.core.indicator.Indicator.from_dict(\n",
    "        data={\n",
    "            \"base\": \"wetdays\",\n",
    "            \"parameters\": {\"thresh\": \"5 mm d-1\"},\n",
    "        },\n",
    "        identifier=\"wet5mm\",\n",
    "        module=\"example\",\n",
    "    ),\n",
    "]\n",
    "\n",
    "xh.indicators.compute_indicators(ds, indicators)[\"YS-JAN\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, `xhydro.indicators.get_yearly_op`, also built upon the `xclim` library, provides a flexible method for obtaining yearly values of specific statistics, such as annual or seasonal maxima. This can be particularly useful, for instance, when extracting raw data needed for frequency analyses.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function get_yearly_op in module xhydro.indicators.generic:\n",
      "\n",
      "get_yearly_op(\n",
      "    ds,\n",
      "    op,\n",
      "    *,\n",
      "    input_var: str = 'q',\n",
      "    window: int = 1,\n",
      "    timeargs: dict | None = None,\n",
      "    missing: str = 'skip',\n",
      "    missing_options: dict | None = None,\n",
      "    interpolate_na: bool = False\n",
      ") -> xarray.core.dataset.Dataset\n",
      "    Compute yearly operations on a variable.\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    ds : xr.Dataset\n",
      "        Dataset containing the variable to compute the operation on.\n",
      "    op : str\n",
      "        Operation to compute. One of [\"max\", \"min\", \"mean\", \"sum\"].\n",
      "    input_var : str\n",
      "        Name of the input variable. Defaults to \"q\".\n",
      "    window : int\n",
      "        Size of the rolling window. A \"mean\" operation is performed on the rolling window before the call to xclim.\n",
      "        This parameter cannot be used with the \"sum\" operation.\n",
      "    timeargs : dict, optional\n",
      "        Dictionary of time arguments for the operation.\n",
      "        Keys are the name of the period that will be added to the results (e.g. \"winter\", \"summer\", \"annual\").\n",
      "        Values are up to two dictionaries, with both being optional.\n",
      "        The first is {'freq': str}, where str is a frequency supported by xarray (e.g. \"YS\", \"YS-JAN\", \"YS-DEC\").\n",
      "        It needs to be a yearly frequency. Defaults to \"YS-JAN\".\n",
      "        The second is an indexer as supported by :py:func:`xclim.core.calendar.select_time`.\n",
      "        Defaults to {}, which means the whole year.\n",
      "        See :py:func:`xclim.core.calendar.select_time` for more information.\n",
      "        Examples: {\"winter\": {\"freq\": \"YS-DEC\", \"date_bounds\": [\"12-01\", \"02-28\"]}}, {\"jan\": {\"freq\": \"YS\", \"month\": 1}}, {\"annual\": {}}.\n",
      "    missing : str\n",
      "        How to handle missing values. One of \"skip\", \"any\", \"at_least_n\", \"pct\", \"wmo\".\n",
      "        See :py:func:`xclim.core.missing` for more information.\n",
      "    missing_options : dict, optional\n",
      "        Dictionary of options for the missing values' method. See :py:func:`xclim.core.missing` for more information.\n",
      "    interpolate_na : bool\n",
      "        Whether to interpolate missing values before computing the operation. Only used with the \"sum\" operation.\n",
      "        Defaults to False.\n",
      "\n",
      "    Returns\n",
      "    -------\n",
      "    xr.Dataset\n",
      "        Dataset containing the computed operations, with one variable per indexer.\n",
      "        The name of the variable follows the pattern `{input_var}{window}_{op}_{indexer}`.\n",
      "\n",
      "    Notes\n",
      "    -----\n",
      "    If you want to perform a frequency analysis on a frequency that is finer than annual, simply use multiple timeargs\n",
      "    (e.g. 1 per month) to create multiple distinct variables.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(xh.indicators.get_yearly_op)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `timeargs` argument relies on indexers that are compatible with `xclim.core.calendar.select_time`. Four types of indexers are currently accepted:\n",
    "\n",
    "- `month`, followed by a sequence of month numbers.\n",
    "- `season`, followed by one or more of `'DJF'`, `'MAM'`, `'JJA'`, and `'SON'`.\n",
    "- `doy_bounds`, followed by a sequence representing the inclusive bounds of the period to be considered (`'start'`, `'end'`).\n",
    "- `date_bounds`, similar to `doy_bounds`, but using a month-day (`'%m-%d'`) format.\n",
    "\n",
    "Subsequently, we specify the operations to be calculated for each variable. Supported operations include `\"max\"`, `\"min\"`, `\"mean\"`, and `\"sum\"`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "timeargs = {\n",
    "    \"january\": {\"month\": [1]},\n",
    "    \"spring\": {\"date_bounds\": [\"02-11\", \"06-19\"]},\n",
    "    \"summer_fall\": {\"date_bounds\": [\"06-20\", \"11-19\"]},\n",
    "    \"year\": {\"date_bounds\": [\"01-01\", \"12-31\"]},\n",
    "}\n",
    "\n",
    "operations = {\n",
    "    \"tas\": [\"max\", \"mean\"],\n",
    "    \"pr\": [\"sum\"],\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The combination of `timeargs` and `operations` through the Cartesian product enables the efficient generation of a comprehensive array of climate indicators."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
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       "    tas_mean_summer_fall  (HYBAS_ID, time) float64 32B 9.367 9.219 12.23 12.57\n",
       "    tas_mean_year         (HYBAS_ID, time) float64 32B 1.734 0.5356 4.881 4.094\n",
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       "    pr_sum_spring         (HYBAS_ID, time) float64 32B 591.9 343.5 453.4 333.9\n",
       "    pr_sum_summer_fall    (HYBAS_ID, time) float64 32B 603.6 626.1 743.2 535.9\n",
       "    pr_sum_year           (HYBAS_ID, time) float64 32B 1.417e+03 ... 1.163e+03\n",
       "Attributes: (12/35)\n",
       "    GRIB_NV:                                  0\n",
       "    GRIB_Nx:                                  1171\n",
       "    GRIB_Ny:                                  701\n",
       "    GRIB_cfName:                              unknown\n",
       "    GRIB_cfVarName:                           t2m\n",
       "    GRIB_dataType:                            fc\n",
       "    ...                                       ...\n",
       "    units:                                    K\n",
       "    cat:xrfreq:                               YS-JAN\n",
       "    cat:frequency:                            yr\n",
       "    cat:processing_level:                     indicators\n",
       "    cat:variable:                             (&#x27;tas_max_january&#x27;, &#x27;tas_max_sp...\n",
       "    cat:id:                                   </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-928788a4-593c-4e54-bbd4-063cf9e01646' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-928788a4-593c-4e54-bbd4-063cf9e01646' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>HYBAS_ID</span>: 2</li><li><span class='xr-has-index'>time</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-111c98b4-0392-4c75-9f06-ebe008496d96' class='xr-section-summary-in' type='checkbox'  checked><label for='section-111c98b4-0392-4c75-9f06-ebe008496d96' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>HYBAS_ID</span></div><div class='xr-var-dims'>(HYBAS_ID)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>7120034480 7120365812</div><input id='attrs-6a0383fa-ba9c-40b9-a007-c38e00d9f4b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a0383fa-ba9c-40b9-a007-c38e00d9f4b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ea097ff-d980-4a2d-b02f-807dc2155c8b' class='xr-var-data-in' type='checkbox'><label for='data-5ea097ff-d980-4a2d-b02f-807dc2155c8b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cf_role :</span></dt><dd>timeseries_id</dd></dl></div><div class='xr-var-data'><pre>array([7120034480, 7120365812])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-01-01 1982-01-01</div><input id='attrs-d9b8f60a-80c5-4633-b23a-a5251a0ecf4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d9b8f60a-80c5-4633-b23a-a5251a0ecf4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d62f8ef-8b5f-447a-93af-019fe6acbd50' class='xr-var-data-in' type='checkbox'><label for='data-4d62f8ef-8b5f-447a-93af-019fe6acbd50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1982-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_agg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;polygon&#x27;</div><input id='attrs-f6146286-88b4-4348-89ff-8665e2915b40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f6146286-88b4-4348-89ff-8665e2915b40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-909f5e6c-5e2e-482b-927a-86281301c6ee' class='xr-var-data-in' type='checkbox'><label for='data-909f5e6c-5e2e-482b-927a-86281301c6ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;polygon&#x27;, dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timestep</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;D&#x27;</div><input id='attrs-40a52b3b-a5af-449f-b30e-9dcff3ee39df' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40a52b3b-a5af-449f-b30e-9dcff3ee39df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f29f4a24-d178-47a6-a775-a286cfb79809' class='xr-var-data-in' type='checkbox'><label for='data-f29f4a24-d178-47a6-a775-a286cfb79809' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;D&#x27;, dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;era5_land_reanalysis&#x27;</div><input id='attrs-f3a5f277-ed73-42f9-abac-af93611875f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3a5f277-ed73-42f9-abac-af93611875f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f48ebb18-f44a-44e2-b52e-5f456e4b1567' class='xr-var-data-in' type='checkbox'><label for='data-f48ebb18-f44a-44e2-b52e-5f456e4b1567' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;era5_land_reanalysis&#x27;, dtype=&#x27;&lt;U20&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4feb1f10-d400-434d-8f79-d937116fd03a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4feb1f10-d400-434d-8f79-d937116fd03a' class='xr-section-summary' >Data variables: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas_max_january</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.165 -7.795 -0.1285 -3.176</div><input id='attrs-32240c07-206c-4fc1-996a-cf3e16d61866' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32240c07-206c-4fc1-996a-cf3e16d61866' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3543bf55-26b2-4431-a4c7-6578d4cbfe14' class='xr-var-data-in' type='checkbox'><label for='data-3543bf55-26b2-4431-a4c7-6578d4cbfe14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Maximum of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tas_max_january: fa.TAS_MAX_JANUARY(tas=tas) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual maximum of variable (m[1]).</dd></dl></div><div class='xr-var-data'><pre>array([[-4.16521451, -7.79473769],\n",
       "       [-0.12849112, -3.17560221]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas_max_spring</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>17.11 18.26 21.04 20.31</div><input id='attrs-2cb25f2d-90ad-4ef6-bcf7-0477fcef974a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cb25f2d-90ad-4ef6-bcf7-0477fcef974a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4771f5e-6ea5-4994-8129-f8e29c5afea5' class='xr-var-data-in' type='checkbox'><label for='data-c4771f5e-6ea5-4994-8129-f8e29c5afea5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Maximum of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tas_max_spring: fa.TAS_MAX_SPRING(tas=tas) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual maximum of variable (02-11 to 06-19).</dd></dl></div><div class='xr-var-data'><pre>array([[17.11018739, 18.26366722],\n",
       "       [21.04095403, 20.31446986]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas_max_summer_fall</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>19.5 22.01 22.98 25.42</div><input id='attrs-c2cc787a-cbda-4567-b3c7-c0294639ef78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2cc787a-cbda-4567-b3c7-c0294639ef78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49665566-cdad-4443-ab1d-324cfcc54a27' class='xr-var-data-in' type='checkbox'><label for='data-49665566-cdad-4443-ab1d-324cfcc54a27' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Maximum of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tas_max_summer_fall: fa.TAS_MAX_SUMMER_FALL(tas=tas) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual maximum of variable (06-20 to 11-19).</dd></dl></div><div class='xr-var-data'><pre>array([[19.50401005, 22.0119582 ],\n",
       "       [22.98479571, 25.42350323]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas_max_year</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>19.5 22.01 22.98 25.42</div><input id='attrs-0493e27b-00bf-4e5f-a39f-a3204c68711d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0493e27b-00bf-4e5f-a39f-a3204c68711d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e251978c-70d5-4bb3-a898-cf9c0f5b4d94' class='xr-var-data-in' type='checkbox'><label for='data-e251978c-70d5-4bb3-a898-cf9c0f5b4d94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Maximum of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tas_max_year: fa.TAS_MAX_YEAR(tas=tas) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual maximum of variable (01-01 to 12-31).</dd></dl></div><div class='xr-var-data'><pre>array([[19.50401005, 22.0119582 ],\n",
       "       [22.98479571, 25.42350323]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas_mean_january</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-18.11 -19.82 -16.08 -16.8</div><input id='attrs-148be8f0-96e4-416f-85c4-3d18f6b7f4ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-148be8f0-96e4-416f-85c4-3d18f6b7f4ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de08da1d-4c5e-43b0-8e21-375993077b6d' class='xr-var-data-in' type='checkbox'><label for='data-de08da1d-4c5e-43b0-8e21-375993077b6d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Average of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tas_mean_january: fa.TAS_MEAN_JANUARY(tas=tas) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual average of variable (m[1]).</dd></dl></div><div class='xr-var-data'><pre>array([[-18.11239077, -19.82298765],\n",
       "       [-16.08425142, -16.79922022]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas_mean_spring</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.696 -0.8479 5.592 2.777</div><input id='attrs-0a851886-b6b0-4826-a0d2-923243950054' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a851886-b6b0-4826-a0d2-923243950054' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f757db3-3601-4e75-9922-4e110ba913b5' class='xr-var-data-in' type='checkbox'><label for='data-4f757db3-3601-4e75-9922-4e110ba913b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Average of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tas_mean_spring: fa.TAS_MEAN_SPRING(tas=tas) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual average of variable (02-11 to 06-19).</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.6959735 , -0.84792753],\n",
       "       [ 5.59207863,  2.77681628]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas_mean_summer_fall</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.367 9.219 12.23 12.57</div><input id='attrs-f45346da-7ad4-42c1-b9e7-51500b7b0e1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f45346da-7ad4-42c1-b9e7-51500b7b0e1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd513518-0f2f-41c5-ad12-fd39d516604c' class='xr-var-data-in' type='checkbox'><label for='data-cd513518-0f2f-41c5-ad12-fd39d516604c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Average of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tas_mean_summer_fall: fa.TAS_MEAN_SUMMER_FALL(tas=tas) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual average of variable (06-20 to 11-19).</dd></dl></div><div class='xr-var-data'><pre>array([[ 9.36683354,  9.21927664],\n",
       "       [12.22504885, 12.56877403]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas_mean_year</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.734 0.5356 4.881 4.094</div><input id='attrs-a3dee00b-e999-45e6-bfbe-9e652f5607d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3dee00b-e999-45e6-bfbe-9e652f5607d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8778bc03-b0fb-49fd-aeb4-25688c740693' class='xr-var-data-in' type='checkbox'><label for='data-8778bc03-b0fb-49fd-aeb4-25688c740693' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Average of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] tas_mean_year: fa.TAS_MEAN_YEAR(tas=tas) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual average of variable (01-01 to 12-31).</dd></dl></div><div class='xr-var-data'><pre>array([[1.73388093, 0.53555071],\n",
       "       [4.88074024, 4.09418479]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr_sum_january</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>34.29 88.93 28.49 85.93</div><input id='attrs-3f47a06e-addb-4bca-b33a-e1b05c041e50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f47a06e-addb-4bca-b33a-e1b05c041e50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-508dcebd-b878-43e4-82e5-1e2eb91f3b21' class='xr-var-data-in' type='checkbox'><label for='data-508dcebd-b878-43e4-82e5-1e2eb91f3b21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tp</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>228</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Integral of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean within days</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] pr_sum_january: fa.PR_SUM_JANUARY(pr=pr) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual integral of variable (m[1]).</dd></dl></div><div class='xr-var-data'><pre>array([[34.29132105, 88.93425073],\n",
       "       [28.49428269, 85.92510746]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr_sum_spring</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>591.9 343.5 453.4 333.9</div><input id='attrs-3d3176f5-1351-48eb-8349-5c01d2480310' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d3176f5-1351-48eb-8349-5c01d2480310' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb02f4aa-624e-4c1a-aeb4-5f02cd2005c4' class='xr-var-data-in' type='checkbox'><label for='data-bb02f4aa-624e-4c1a-aeb4-5f02cd2005c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tp</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>228</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Integral of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean within days</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] pr_sum_spring: fa.PR_SUM_SPRING(pr=pr) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual integral of variable (02-11 to 06-19).</dd></dl></div><div class='xr-var-data'><pre>array([[591.89041576, 343.52261632],\n",
       "       [453.36242901, 333.93934479]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr_sum_summer_fall</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>603.6 626.1 743.2 535.9</div><input id='attrs-804f0664-7b45-4868-9712-fc2a56fb337c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-804f0664-7b45-4868-9712-fc2a56fb337c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45b4082c-1988-4146-8bdb-7992cea483fd' class='xr-var-data-in' type='checkbox'><label for='data-45b4082c-1988-4146-8bdb-7992cea483fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tp</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>228</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Integral of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean within days</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] pr_sum_summer_fall: fa.PR_SUM_SUMMER_FALL(pr=pr) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual integral of variable (06-20 to 11-19).</dd></dl></div><div class='xr-var-data'><pre>array([[603.63711689, 626.14561683],\n",
       "       [743.18303562, 535.93357828]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr_sum_year</span></div><div class='xr-var-dims'>(HYBAS_ID, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.417e+03 1.286e+03 ... 1.163e+03</div><input id='attrs-9176617f-82d3-4e62-8933-61ee7d49a378' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9176617f-82d3-4e62-8933-61ee7d49a378' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ef62410-31b9-4ee0-b9b3-c6e15cb95bb6' class='xr-var-data-in' type='checkbox'><label for='data-8ef62410-31b9-4ee0-b9b3-c6e15cb95bb6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tp</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>228</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Integral of variable</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean within days</dd><dt><span>history :</span></dt><dd>[2026-02-19 14:33:32] pr_sum_year: fa.PR_SUM_YEAR(pr=pr) with options check_missing=skip - xclim version: 0.58.1</dd><dt><span>description :</span></dt><dd>Annual integral of variable (01-01 to 12-31).</dd></dl></div><div class='xr-var-data'><pre>array([[1416.79223843, 1285.51352174],\n",
       "       [1418.8632368 , 1163.13308214]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-35ddb2ca-f9a3-4e10-9fd0-d85f6e40527d' class='xr-section-summary-in' type='checkbox'  ><label for='section-35ddb2ca-f9a3-4e10-9fd0-d85f6e40527d' class='xr-section-summary' >Attributes: <span>(35)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1171</dd><dt><span>GRIB_Ny :</span></dt><dd>701</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.1</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>85.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>15.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-167.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>-50.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>820871</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cat:xrfreq :</span></dt><dd>YS-JAN</dd><dt><span>cat:frequency :</span></dt><dd>yr</dd><dt><span>cat:processing_level :</span></dt><dd>indicators</dd><dt><span>cat:variable :</span></dt><dd>(&#x27;tas_max_january&#x27;, &#x27;tas_max_spring&#x27;, &#x27;tas_max_summer_fall&#x27;, &#x27;tas_max_year&#x27;)</dd><dt><span>cat:id :</span></dt><dd></dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 528B\n",
       "Dimensions:               (HYBAS_ID: 2, time: 2)\n",
       "Coordinates:\n",
       "  * HYBAS_ID              (HYBAS_ID) int64 16B 7120034480 7120365812\n",
       "  * time                  (time) datetime64[ns] 16B 1981-01-01 1982-01-01\n",
       "    spatial_agg           <U7 28B 'polygon'\n",
       "    timestep              <U1 4B 'D'\n",
       "    source                <U20 80B 'era5_land_reanalysis'\n",
       "Data variables:\n",
       "    tas_max_january       (HYBAS_ID, time) float64 32B -4.165 -7.795 ... -3.176\n",
       "    tas_max_spring        (HYBAS_ID, time) float64 32B 17.11 18.26 21.04 20.31\n",
       "    tas_max_summer_fall   (HYBAS_ID, time) float64 32B 19.5 22.01 22.98 25.42\n",
       "    tas_max_year          (HYBAS_ID, time) float64 32B 19.5 22.01 22.98 25.42\n",
       "    tas_mean_january      (HYBAS_ID, time) float64 32B -18.11 -19.82 ... -16.8\n",
       "    tas_mean_spring       (HYBAS_ID, time) float64 32B 1.696 -0.8479 5.592 2.777\n",
       "    tas_mean_summer_fall  (HYBAS_ID, time) float64 32B 9.367 9.219 12.23 12.57\n",
       "    tas_mean_year         (HYBAS_ID, time) float64 32B 1.734 0.5356 4.881 4.094\n",
       "    pr_sum_january        (HYBAS_ID, time) float64 32B 34.29 88.93 28.49 85.93\n",
       "    pr_sum_spring         (HYBAS_ID, time) float64 32B 591.9 343.5 453.4 333.9\n",
       "    pr_sum_summer_fall    (HYBAS_ID, time) float64 32B 603.6 626.1 743.2 535.9\n",
       "    pr_sum_year           (HYBAS_ID, time) float64 32B 1.417e+03 ... 1.163e+03\n",
       "Attributes: (12/35)\n",
       "    GRIB_NV:                                  0\n",
       "    GRIB_Nx:                                  1171\n",
       "    GRIB_Ny:                                  701\n",
       "    GRIB_cfName:                              unknown\n",
       "    GRIB_cfVarName:                           t2m\n",
       "    GRIB_dataType:                            fc\n",
       "    ...                                       ...\n",
       "    units:                                    K\n",
       "    cat:xrfreq:                               YS-JAN\n",
       "    cat:frequency:                            yr\n",
       "    cat:processing_level:                     indicators\n",
       "    cat:variable:                             ('tas_max_january', 'tas_max_sp...\n",
       "    cat:id:                                   "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_climatology = xr.merge(\n",
    "    [\n",
    "        xh.indicators.get_yearly_op(ds, input_var=variable, op=op, timeargs=timeargs)\n",
    "        for (variable, ops) in operations.items()\n",
    "        for op in ops\n",
    "    ]\n",
    ")\n",
    "ds_climatology"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The same data can also be visualized as a `pd.DataFrame` as well :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>HYBAS_ID</th>\n",
       "      <th>7120034480</th>\n",
       "      <th>7120365812</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>spatial_agg</th>\n",
       "      <td>polygon</td>\n",
       "      <td>polygon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timestep</th>\n",
       "      <td>D</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source</th>\n",
       "      <td>era5_land_reanalysis</td>\n",
       "      <td>era5_land_reanalysis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tas_max_january</th>\n",
       "      <td>-5.979976</td>\n",
       "      <td>-1.652047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tas_max_spring</th>\n",
       "      <td>17.686927</td>\n",
       "      <td>20.677712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tas_max_summer_fall</th>\n",
       "      <td>20.757984</td>\n",
       "      <td>24.204149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tas_max_year</th>\n",
       "      <td>20.757984</td>\n",
       "      <td>24.204149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tas_mean_january</th>\n",
       "      <td>-18.967689</td>\n",
       "      <td>-16.441736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tas_mean_spring</th>\n",
       "      <td>0.424023</td>\n",
       "      <td>4.184447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tas_mean_summer_fall</th>\n",
       "      <td>9.293055</td>\n",
       "      <td>12.396911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tas_mean_year</th>\n",
       "      <td>1.134716</td>\n",
       "      <td>4.487463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pr_sum_january</th>\n",
       "      <td>61.612786</td>\n",
       "      <td>57.209695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pr_sum_spring</th>\n",
       "      <td>467.706516</td>\n",
       "      <td>393.650887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pr_sum_summer_fall</th>\n",
       "      <td>614.891367</td>\n",
       "      <td>639.558307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pr_sum_year</th>\n",
       "      <td>1351.15288</td>\n",
       "      <td>1290.998159</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "HYBAS_ID                        7120034480            7120365812\n",
       "spatial_agg                        polygon               polygon\n",
       "timestep                                 D                     D\n",
       "source                era5_land_reanalysis  era5_land_reanalysis\n",
       "tas_max_january                  -5.979976             -1.652047\n",
       "tas_max_spring                   17.686927             20.677712\n",
       "tas_max_summer_fall              20.757984             24.204149\n",
       "tas_max_year                     20.757984             24.204149\n",
       "tas_mean_january                -18.967689            -16.441736\n",
       "tas_mean_spring                   0.424023              4.184447\n",
       "tas_mean_summer_fall              9.293055             12.396911\n",
       "tas_mean_year                     1.134716              4.487463\n",
       "pr_sum_january                   61.612786             57.209695\n",
       "pr_sum_spring                   467.706516            393.650887\n",
       "pr_sum_summer_fall              614.891367            639.558307\n",
       "pr_sum_year                     1351.15288           1290.998159"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option(\"display.max_rows\", 100)\n",
    "ds_climatology.mean(\"time\").to_dataframe().T"
   ]
  }
 ],
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