nwm_timeseries_data.ipynb

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   "source": [
    "**Import required libraries**"
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    "import intake\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "import numpy as np\n",
    "import xarray as xr"
   ]
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   "id": "49c7b53c-5f2c-4e56-bb2d-f25ef93610f9",
   "metadata": {},
   "source": [
    "**Open the NWM intake catalog**"
   ]
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   "id": "e06b7b4b-469b-47b8-ae5a-972a83299094",
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       "['NWM_Best_CONUS_Short_Range',\n",
       " 'NWM_Best_CONUS_Medium_Range',\n",
       " 'NWM_Best_Alaska_Short_Range',\n",
       " 'NWM_Best_Alaska_Medium_Range',\n",
       " 'NWM_Best_Hawaii_Short_Range',\n",
       " 'NWM_Best_PuertoRico_Short_Range']"
      ]
     },
     "execution_count": 2,
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   "source": [
    "catalog = intake.open_catalog('s3://noaa-nodd-kerchunk-pds/nwm_ll/nwm_intake.yml',storage_options={'anon':True})\n",
    "(list(catalog))"
   ]
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    "### Compare NWM souce dataset with Kerchunked virtual aggregate dataset\n",
    "\n",
    "Part of the processing included adding additional coordinate and attribute values to the souce netCDF files produced by NWM.  Below is a list of the additions.\n",
    "\n",
    "**Coordinates** added to the kerchunked datasets include: \n",
    "* latitude\n",
    "* longitude\n",
    "\n",
    "**Attributes** added include:\n",
    "* altitude: altitude of node \n",
    "* link_id: the link id of the node\n",
    "* from_link_id: the from_link_id of the node in the network topology\n",
    "* to_link_id: the to_link_id of the node in the network topology\n",
    "* terminal_node: whether this node is a terminal node or not\n",
    "\n",
    "\n",
    "**Time Dimension**\n",
    "\n",
    "Other changes include to the length of the `time` dimension in the dataset, showing the virtual aggregation of many forecast times in a single 'best time series' dataset."
   ]
  },
  {
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   "id": "596aef0a-cb26-4a69-9ec0-23ccc0422bd7",
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   "source": [
    "**Compare the short range channel forecast netCDF file with kerchunked equivalent**\n",
    "\n",
    "The xarray representation below shows the structure of the original/source datasets output by NWM.  "
   ]
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   "execution_count": 3,
   "id": "f246fd56-f7ef-4e74-be6b-b70cfe5b9503",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 155MB\n",
       "Dimensions:         (time: 1, reference_time: 1, feature_id: 2776734)\n",
       "Coordinates:\n",
       "  * time            (time) datetime64[ns] 8B 2024-02-14\n",
       "  * reference_time  (reference_time) datetime64[ns] 8B 2024-02-13T23:00:00\n",
       "  * feature_id      (feature_id) int64 22MB 101 179 ... 1180001803 1180001804\n",
       "Data variables:\n",
       "    crs             |S1 1B ...\n",
       "    streamflow      (feature_id) float64 22MB ...\n",
       "    nudge           (feature_id) float64 22MB ...\n",
       "    velocity        (feature_id) float64 22MB ...\n",
       "    qSfcLatRunoff   (feature_id) float64 22MB ...\n",
       "    qBucket         (feature_id) float64 22MB ...\n",
       "    qBtmVertRunoff  (feature_id) float64 22MB ...\n",
       "Attributes: (12/19)\n",
       "    TITLE:                      OUTPUT FROM NWM v3.0\n",
       "    featureType:                timeSeries\n",
       "    proj4:                      +proj=lcc +units=m +a=6370000.0 +b=6370000.0 ...\n",
       "    model_initialization_time:  2024-02-13_23:00:00\n",
       "    station_dimension:          feature_id\n",
       "    model_output_valid_time:    2024-02-14_00:00:00\n",
       "    ...                         ...\n",
       "    model_configuration:        short_range\n",
       "    dev_OVRTSWCRT:              1\n",
       "    dev_NOAH_TIMESTEP:          3600\n",
       "    dev_channel_only:           0\n",
       "    dev_channelBucket_only:     0\n",
       "    dev:                        dev_ prefix indicates development/internal me...</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-61fcc3f6-32de-452d-ae5e-fbfa603c9c0d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-61fcc3f6-32de-452d-ae5e-fbfa603c9c0d' 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'>time</span>: 1</li><li><span class='xr-has-index'>reference_time</span>: 1</li><li><span class='xr-has-index'>feature_id</span>: 2776734</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-cff5bd48-dc6d-44fd-8deb-b1124931f2d9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cff5bd48-dc6d-44fd-8deb-b1124931f2d9' class='xr-section-summary' >Coordinates: <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 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'>2024-02-14</div><input id='attrs-eba70e4f-27e3-43d8-a281-7698e5fcb9aa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eba70e4f-27e3-43d8-a281-7698e5fcb9aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b955f387-8c98-4eeb-9108-fccc5b3f93f0' class='xr-var-data-in' type='checkbox'><label for='data-b955f387-8c98-4eeb-9108-fccc5b3f93f0' 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>valid output time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>valid_min :</span></dt><dd>28464480</dd><dt><span>valid_max :</span></dt><dd>28465500</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-02-14T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>reference_time</span></div><div class='xr-var-dims'>(reference_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-02-13T23:00:00</div><input id='attrs-7e38f618-2dbe-450c-a690-e78e5de8f47d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e38f618-2dbe-450c-a690-e78e5de8f47d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4ba2b57-75f2-4772-872b-785f7bf2d257' class='xr-var-data-in' type='checkbox'><label for='data-e4ba2b57-75f2-4772-872b-785f7bf2d257' 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>model initialization time</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-02-13T23:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>feature_id</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>101 179 ... 1180001803 1180001804</div><input id='attrs-cff9b86d-c900-49a7-b262-0f7f12c6fc1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cff9b86d-c900-49a7-b262-0f7f12c6fc1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93b2d55e-0bc1-4134-b7c8-4a50fe094d71' class='xr-var-data-in' type='checkbox'><label for='data-93b2d55e-0bc1-4134-b7c8-4a50fe094d71' 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>Reach ID</dd><dt><span>comment :</span></dt><dd>NHDPlusv2 ComIDs within CONUS, arbitrary Reach IDs outside of CONUS</dd><dt><span>cf_role :</span></dt><dd>timeseries_id</dd></dl></div><div class='xr-var-data'><pre>array([       101,        179,        181, ..., 1180001802, 1180001803,\n",
       "       1180001804])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c3abf717-3365-4d55-a9bf-e1c8679f3594' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c3abf717-3365-4d55-a9bf-e1c8679f3594' 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>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-12c6f78e-bee6-4ad9-b1aa-5fdca06839fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12c6f78e-bee6-4ad9-b1aa-5fdca06839fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e53993b-f7e6-4344-9974-fce789f5fafb' class='xr-var-data-in' type='checkbox'><label for='data-4e53993b-f7e6-4344-9974-fce789f5fafb' 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>transform_name :</span></dt><dd>latitude longitude</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude longitude</dd><dt><span>esri_pe_string :</span></dt><dd>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8.98315284119521E-09;0.001;0.001;IsHighPrecision</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8.98315284119521E-09;0.001;0.001;IsHighPrecision</dd><dt><span>long_name :</span></dt><dd>CRS definition</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>_CoordinateAxes :</span></dt><dd>latitude longitude</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.5</dd><dt><span>inverse_flattening :</span></dt><dd>298.25723</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S1]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>streamflow</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1510802b-c662-4d55-9446-c13ce96328e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1510802b-c662-4d55-9446-c13ce96328e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b92beb02-ea97-42c7-980f-faba403ee747' class='xr-var-data-in' type='checkbox'><label for='data-b92beb02-ea97-42c7-980f-faba403ee747' 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>River Flow</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>valid_range :</span></dt><dd>[      0 5000000]</dd></dl></div><div class='xr-var-data'><pre>[2776734 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nudge</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1534cf2b-c156-4746-b3d8-ff9d058e7c8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1534cf2b-c156-4746-b3d8-ff9d058e7c8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5456f372-ee24-4bbe-94b6-a42fea576ea1' class='xr-var-data-in' type='checkbox'><label for='data-5456f372-ee24-4bbe-94b6-a42fea576ea1' 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>Amount of stream flow alteration</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>valid_range :</span></dt><dd>[-5000000  5000000]</dd></dl></div><div class='xr-var-data'><pre>[2776734 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>velocity</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2bc0b05a-2d5b-4b70-9ef6-c1aec8755c68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bc0b05a-2d5b-4b70-9ef6-c1aec8755c68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c24c502-0496-4c6a-a159-079ace102d18' class='xr-var-data-in' type='checkbox'><label for='data-6c24c502-0496-4c6a-a159-079ace102d18' 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>River Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>valid_range :</span></dt><dd>[      0 5000000]</dd></dl></div><div class='xr-var-data'><pre>[2776734 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qSfcLatRunoff</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-88bdd0af-15ba-460d-acec-d7964d595c46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88bdd0af-15ba-460d-acec-d7964d595c46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c10b461-db48-41a8-a6b5-37fce6463d9e' class='xr-var-data-in' type='checkbox'><label for='data-3c10b461-db48-41a8-a6b5-37fce6463d9e' 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>Runoff from terrain routing</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>valid_range :</span></dt><dd>[         0 2000000000]</dd></dl></div><div class='xr-var-data'><pre>[2776734 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qBucket</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-acf938e4-641a-403b-b98b-c7090937a891' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acf938e4-641a-403b-b98b-c7090937a891' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c17e861-ad4f-4e94-a084-f77e6b4927de' class='xr-var-data-in' type='checkbox'><label for='data-3c17e861-ad4f-4e94-a084-f77e6b4927de' 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>Flux from gw bucket</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>valid_range :</span></dt><dd>[         0 2000000000]</dd></dl></div><div class='xr-var-data'><pre>[2776734 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qBtmVertRunoff</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e8a57164-2026-493f-ade1-459ed4bbf26b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8a57164-2026-493f-ade1-459ed4bbf26b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da69e71f-e4b2-4ef9-a55d-b46b0bc890be' class='xr-var-data-in' type='checkbox'><label for='data-da69e71f-e4b2-4ef9-a55d-b46b0bc890be' 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>Runoff from bottom of soil to bucket</dd><dt><span>units :</span></dt><dd>m3</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>valid_range :</span></dt><dd>[       0 20000000]</dd></dl></div><div class='xr-var-data'><pre>[2776734 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-af2a201e-3eb4-41b8-9f2e-71597b9d34a5' class='xr-section-summary-in' type='checkbox'  ><label for='section-af2a201e-3eb4-41b8-9f2e-71597b9d34a5' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-eea25f38-59a8-441a-9f4f-4f2c2945041f' class='xr-index-data-in' type='checkbox'/><label for='index-eea25f38-59a8-441a-9f4f-4f2c2945041f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-02-14&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>reference_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a95c856b-d8ab-4ab9-8ab3-a560f8c47fc3' class='xr-index-data-in' type='checkbox'/><label for='index-a95c856b-d8ab-4ab9-8ab3-a560f8c47fc3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-02-13 23:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;reference_time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>feature_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-670a115b-54a8-4962-ab2a-5c2b490ceee9' class='xr-index-data-in' type='checkbox'/><label for='index-670a115b-54a8-4962-ab2a-5c2b490ceee9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([       101,        179,        181,        183,        185,        843,\n",
       "              845,        847,        849,        851,\n",
       "       ...\n",
       "       1180001795, 1180001796, 1180001797, 1180001798, 1180001799, 1180001800,\n",
       "       1180001801, 1180001802, 1180001803, 1180001804],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;feature_id&#x27;, length=2776734))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7f1a2fc4-17e4-495a-9466-7b5f177b433f' class='xr-section-summary-in' type='checkbox'  ><label for='section-7f1a2fc4-17e4-495a-9466-7b5f177b433f' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>TITLE :</span></dt><dd>OUTPUT FROM NWM v3.0</dd><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>proj4 :</span></dt><dd>+proj=lcc +units=m +a=6370000.0 +b=6370000.0 +lat_1=30.0 +lat_2=60.0 +lat_0=40.0 +lon_0=-97.0 +x_0=0 +y_0=0 +k_0=1.0 +nadgrids=@</dd><dt><span>model_initialization_time :</span></dt><dd>2024-02-13_23:00:00</dd><dt><span>station_dimension :</span></dt><dd>feature_id</dd><dt><span>model_output_valid_time :</span></dt><dd>2024-02-14_00:00:00</dd><dt><span>model_total_valid_times :</span></dt><dd>18</dd><dt><span>stream_order_output :</span></dt><dd>1</dd><dt><span>cdm_datatype :</span></dt><dd>Station</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>code_version :</span></dt><dd>v5.3.0-alpha1</dd><dt><span>NWM_version_number :</span></dt><dd>v3.0</dd><dt><span>model_output_type :</span></dt><dd>channel_rt</dd><dt><span>model_configuration :</span></dt><dd>short_range</dd><dt><span>dev_OVRTSWCRT :</span></dt><dd>1</dd><dt><span>dev_NOAH_TIMESTEP :</span></dt><dd>3600</dd><dt><span>dev_channel_only :</span></dt><dd>0</dd><dt><span>dev_channelBucket_only :</span></dt><dd>0</dd><dt><span>dev :</span></dt><dd>dev_ prefix indicates development/internal meta data</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 155MB\n",
       "Dimensions:         (time: 1, reference_time: 1, feature_id: 2776734)\n",
       "Coordinates:\n",
       "  * time            (time) datetime64[ns] 8B 2024-02-14\n",
       "  * reference_time  (reference_time) datetime64[ns] 8B 2024-02-13T23:00:00\n",
       "  * feature_id      (feature_id) int64 22MB 101 179 ... 1180001803 1180001804\n",
       "Data variables:\n",
       "    crs             |S1 1B ...\n",
       "    streamflow      (feature_id) float64 22MB ...\n",
       "    nudge           (feature_id) float64 22MB ...\n",
       "    velocity        (feature_id) float64 22MB ...\n",
       "    qSfcLatRunoff   (feature_id) float64 22MB ...\n",
       "    qBucket         (feature_id) float64 22MB ...\n",
       "    qBtmVertRunoff  (feature_id) float64 22MB ...\n",
       "Attributes: (12/19)\n",
       "    TITLE:                      OUTPUT FROM NWM v3.0\n",
       "    featureType:                timeSeries\n",
       "    proj4:                      +proj=lcc +units=m +a=6370000.0 +b=6370000.0 ...\n",
       "    model_initialization_time:  2024-02-13_23:00:00\n",
       "    station_dimension:          feature_id\n",
       "    model_output_valid_time:    2024-02-14_00:00:00\n",
       "    ...                         ...\n",
       "    model_configuration:        short_range\n",
       "    dev_OVRTSWCRT:              1\n",
       "    dev_NOAH_TIMESTEP:          3600\n",
       "    dev_channel_only:           0\n",
       "    dev_channelBucket_only:     0\n",
       "    dev:                        dev_ prefix indicates development/internal me..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_sr_nc = xr.open_dataset(\"files/nwm.t23z.short_range.channel_rt.f001.conus.nc\")\n",
    "ds_sr_nc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15a70f21-08f7-4bdc-9cef-6193e7af0fd2",
   "metadata": {
    "tags": []
   },
   "source": [
    "**Open the equivalent 'NWM_Best_CONUS_Short_Range' dataset** \n",
    "\n",
    "Open the kerchunked virtual dataset from the Intake catalog to illustrate the added attribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f84793c5-dda6-4e7a-a9e4-5b1e84954ae2",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 97GB\n",
       "Dimensions:         (feature_id: 2776734, time: 726, reference_time: 1)\n",
       "Coordinates:\n",
       "  * feature_id      (feature_id) int64 22MB 101 179 ... 1180001803 1180001804\n",
       "    latitude        (feature_id) float32 11MB dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;\n",
       "    longitude       (feature_id) float32 11MB dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;\n",
       "  * reference_time  (reference_time) datetime64[ns] 8B 2024-08-06T23:00:00\n",
       "  * time            (time) datetime64[ns] 6kB 2024-08-07 ... 2024-09-06T05:00:00\n",
       "Data variables:\n",
       "    altitude        (feature_id) float32 11MB dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;\n",
       "    crs             (time) object 6kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    from_link_id    (feature_id) float64 22MB dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;\n",
       "    link_id         (feature_id) float64 22MB dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;\n",
       "    nudge           (time, feature_id) float64 16GB dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;\n",
       "    qBtmVertRunoff  (time, feature_id) float64 16GB dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;\n",
       "    qBucket         (time, feature_id) float64 16GB dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;\n",
       "    qSfcLatRunoff   (time, feature_id) float64 16GB dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;\n",
       "    streamflow      (time, feature_id) float64 16GB dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;\n",
       "    terminal_node   (feature_id) float64 22MB dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;\n",
       "    to_link_id      (feature_id) float64 22MB dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;\n",
       "    velocity        (time, feature_id) float64 16GB dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;\n",
       "Attributes: (12/19)\n",
       "    Conventions:                CF-1.6\n",
       "    NWM_version_number:         v3.0\n",
       "    TITLE:                      OUTPUT FROM NWM v3.0\n",
       "    cdm_datatype:               Station\n",
       "    code_version:               v5.3.0-alpha1\n",
       "    dev:                        dev_ prefix indicates development/internal me...\n",
       "    ...                         ...\n",
       "    model_output_type:          channel_rt\n",
       "    model_output_valid_time:    2024-08-07_00:00:00\n",
       "    model_total_valid_times:    18\n",
       "    proj4:                      +proj=lcc +units=m +a=6370000.0 +b=6370000.0 ...\n",
       "    station_dimension:          feature_id\n",
       "    stream_order_output:        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-60b88cca-9b03-4b83-8116-7cb88ed0e15b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-60b88cca-9b03-4b83-8116-7cb88ed0e15b' 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'>feature_id</span>: 2776734</li><li><span class='xr-has-index'>time</span>: 726</li><li><span class='xr-has-index'>reference_time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5ce6f65f-0aac-4034-8ee2-bba29f891aa1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5ce6f65f-0aac-4034-8ee2-bba29f891aa1' 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'>feature_id</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>101 179 ... 1180001803 1180001804</div><input id='attrs-b01f0fcc-9414-4da1-988c-38ab1c7c09f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b01f0fcc-9414-4da1-988c-38ab1c7c09f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d830ef6-e6db-48f0-aa01-d1dd7e181a2a' class='xr-var-data-in' type='checkbox'><label for='data-1d830ef6-e6db-48f0-aa01-d1dd7e181a2a' 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><dt><span>comment :</span></dt><dd>NHDPlusv2 ComIDs within CONUS, arbitrary Reach IDs outside of CONUS</dd><dt><span>long_name :</span></dt><dd>Reach ID</dd></dl></div><div class='xr-var-data'><pre>array([       101,        179,        181, ..., 1180001802, 1180001803,\n",
       "       1180001804])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;</div><input id='attrs-dd20953c-6a3a-412f-bc3c-ce6c7cb9f276' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dd20953c-6a3a-412f-bc3c-ce6c7cb9f276' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ced0c39-81ca-4837-8e96-7e0bb4b10d50' class='xr-var-data-in' type='checkbox'><label for='data-3ced0c39-81ca-4837-8e96-7e0bb4b10d50' 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'><table>\n",
       "    <tr>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 10.59 MiB </td>\n",
       "                        <td> 10.59 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (2776734,) </td>\n",
       "                        <td> (2776734,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;</div><input id='attrs-940edeeb-b21d-49a7-8b47-5cfb84f512cb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-940edeeb-b21d-49a7-8b47-5cfb84f512cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b69796d1-fcf5-4e57-b604-8a825601a1d5' class='xr-var-data-in' type='checkbox'><label for='data-b69796d1-fcf5-4e57-b604-8a825601a1d5' 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'><table>\n",
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       "                        <td> 10.59 MiB </td>\n",
       "                        <td> 10.59 MiB </td>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>reference_time</span></div><div class='xr-var-dims'>(reference_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-08-06T23:00:00</div><input id='attrs-ba92d02b-6834-4b18-8a6e-b757361a8f00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba92d02b-6834-4b18-8a6e-b757361a8f00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-954e4ebf-8019-4316-9f72-6af49558dc11' class='xr-var-data-in' type='checkbox'><label for='data-954e4ebf-8019-4316-9f72-6af49558dc11' 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>model initialization time</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-08-06T23:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</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'>2024-08-07 ... 2024-09-06T05:00:00</div><input id='attrs-6b00a411-c7e6-4386-b6a6-c6c011b23049' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b00a411-c7e6-4386-b6a6-c6c011b23049' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc9cd286-0b8a-46e0-a302-205b7e479ddd' class='xr-var-data-in' type='checkbox'><label for='data-cc9cd286-0b8a-46e0-a302-205b7e479ddd' 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>valid output time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>valid_max :</span></dt><dd>28717500</dd><dt><span>valid_min :</span></dt><dd>28716480</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-08-07T00:00:00.000000000&#x27;, &#x27;2024-08-07T01:00:00.000000000&#x27;,\n",
       "       &#x27;2024-08-07T02:00:00.000000000&#x27;, ..., &#x27;2024-09-06T03:00:00.000000000&#x27;,\n",
       "       &#x27;2024-09-06T04:00:00.000000000&#x27;, &#x27;2024-09-06T05:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fa8262a5-44ca-46a0-ac30-d4f625f8e923' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fa8262a5-44ca-46a0-ac30-d4f625f8e923' 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>altitude</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;</div><input id='attrs-4747b98a-9c86-4f27-91ab-cc4de4a5a79a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4747b98a-9c86-4f27-91ab-cc4de4a5a79a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65c113bb-2c44-49e7-8b87-2df0ae7e3e55' class='xr-var-data-in' type='checkbox'><label for='data-65c113bb-2c44-49e7-8b87-2df0ae7e3e55' 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'><table>\n",
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       "        <td>\n",
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       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 10.59 MiB </td>\n",
       "                        <td> 10.59 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (2776734,) </td>\n",
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       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-978aaaf4-57bc-48c0-9b6d-4cb8fa1e2223' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-978aaaf4-57bc-48c0-9b6d-4cb8fa1e2223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3f17b16-d9ec-4c50-afea-327185aa4066' class='xr-var-data-in' type='checkbox'><label for='data-b3f17b16-d9ec-4c50-afea-327185aa4066' 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>_CoordinateAxes :</span></dt><dd>latitude longitude</dd><dt><span>esri_pe_string :</span></dt><dd>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8.98315284119521E-09;0.001;0.001;IsHighPrecision</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.2572326660156</dd><dt><span>long_name :</span></dt><dd>CRS definition</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.5</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8.98315284119521E-09;0.001;0.001;IsHighPrecision</dd><dt><span>transform_name :</span></dt><dd>latitude longitude</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 5.67 kiB </td>\n",
       "                        <td> 8 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1,) </td>\n",
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       "                        <td colspan=\"2\"> 726 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "                <tbody>\n",
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       "                        <td> 21.18 MiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
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       "                        <td> (2776734,) </td>\n",
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       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>link_id</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;</div><input id='attrs-7ccca45e-6fa9-4d8f-bb71-3e56cdbeb57d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ccca45e-6fa9-4d8f-bb71-3e56cdbeb57d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64e667b5-b7cd-4370-9784-0387df06ac0e' class='xr-var-data-in' type='checkbox'><label for='data-64e667b5-b7cd-4370-9784-0387df06ac0e' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (2776734,) </td>\n",
       "                        <td> (2776734,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nudge</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;</div><input id='attrs-93054c80-6bfe-4485-8f93-175066415940' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93054c80-6bfe-4485-8f93-175066415940' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e505ca8-c49b-4d73-8263-1236ecf185ad' class='xr-var-data-in' type='checkbox'><label for='data-3e505ca8-c49b-4d73-8263-1236ecf185ad' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Amount of stream flow alteration</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[-5000000, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 15.02 GiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (726, 2776734) </td>\n",
       "                        <td> (1, 2776734) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 726 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qBtmVertRunoff</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;</div><input id='attrs-38ac8f04-67cd-42f0-8bb3-7efd1c51ae9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38ac8f04-67cd-42f0-8bb3-7efd1c51ae9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62ae5185-f8a5-4daf-ac5a-632bdcc50951' class='xr-var-data-in' type='checkbox'><label for='data-62ae5185-f8a5-4daf-ac5a-632bdcc50951' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Runoff from bottom of soil to bucket</dd><dt><span>units :</span></dt><dd>m3</dd><dt><span>valid_range :</span></dt><dd>[0, 20000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 15.02 GiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (726, 2776734) </td>\n",
       "                        <td> (1, 2776734) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 726 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "  <line x1=\"0\" y1=\"14\" x2=\"120\" y2=\"14\" />\n",
       "  <line x1=\"0\" y1=\"16\" x2=\"120\" y2=\"16\" />\n",
       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
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       "  <line x1=\"0\" y1=\"22\" x2=\"120\" y2=\"22\" />\n",
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       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
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       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qBucket</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;</div><input id='attrs-e6f360ab-4b38-4c26-ba89-2a7fa1690915' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6f360ab-4b38-4c26-ba89-2a7fa1690915' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c9afcba-278d-471e-9339-886fc8a9f122' class='xr-var-data-in' type='checkbox'><label for='data-4c9afcba-278d-471e-9339-886fc8a9f122' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Flux from gw bucket</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 2000000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 15.02 GiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (726, 2776734) </td>\n",
       "                        <td> (1, 2776734) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 726 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"0\" y1=\"14\" x2=\"120\" y2=\"14\" />\n",
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       "\n",
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       "\n",
       "  <!-- Colored Rectangle -->\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qSfcLatRunoff</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;</div><input id='attrs-d280fc0e-f499-4bb8-9085-d993fd7ac2d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d280fc0e-f499-4bb8-9085-d993fd7ac2d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-913ec28a-c06c-4fec-af97-321b08340476' class='xr-var-data-in' type='checkbox'><label for='data-913ec28a-c06c-4fec-af97-321b08340476' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Runoff from terrain routing</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 2000000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 15.02 GiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (726, 2776734) </td>\n",
       "                        <td> (1, 2776734) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 726 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>streamflow</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;</div><input id='attrs-f4935037-2546-4135-b4f1-28aa6e0bf1ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4935037-2546-4135-b4f1-28aa6e0bf1ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98d429d0-20c2-411a-93e9-0648a2a60855' class='xr-var-data-in' type='checkbox'><label for='data-98d429d0-20c2-411a-93e9-0648a2a60855' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>River Flow</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 15.02 GiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (726, 2776734) </td>\n",
       "                        <td> (1, 2776734) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 726 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>terminal_node</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;</div><input id='attrs-ef1acc77-483a-410b-b9d6-37e28eb5177d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ef1acc77-483a-410b-b9d6-37e28eb5177d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e60bd95-eee3-4f1f-80b6-754132be728a' class='xr-var-data-in' type='checkbox'><label for='data-3e60bd95-eee3-4f1f-80b6-754132be728a' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (2776734,) </td>\n",
       "                        <td> (2776734,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>to_link_id</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2776734,), meta=np.ndarray&gt;</div><input id='attrs-a0ae1208-a262-44fa-923d-003f233eee12' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a0ae1208-a262-44fa-923d-003f233eee12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c2e2b20-e0d3-4d18-bb5c-df605cd8c021' class='xr-var-data-in' type='checkbox'><label for='data-3c2e2b20-e0d3-4d18-bb5c-df605cd8c021' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (2776734,) </td>\n",
       "                        <td> (2776734,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
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       "\n",
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       "\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>velocity</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2776734), meta=np.ndarray&gt;</div><input id='attrs-9b594260-b265-4797-bd67-bb298d2bce83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b594260-b265-4797-bd67-bb298d2bce83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-121052dd-c4bf-4d11-b322-b8f8169795b8' class='xr-var-data-in' type='checkbox'><label for='data-121052dd-c4bf-4d11-b322-b8f8169795b8' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>River Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 15.02 GiB </td>\n",
       "                        <td> 21.18 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (726, 2776734) </td>\n",
       "                        <td> (1, 2776734) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 726 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"0\" y1=\"2\" x2=\"120\" y2=\"2\" />\n",
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       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
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       "  <line x1=\"0\" y1=\"18\" x2=\"120\" y2=\"18\" />\n",
       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
       "  <line x1=\"0\" y1=\"22\" x2=\"120\" y2=\"22\" />\n",
       "  <line x1=\"0\" y1=\"24\" x2=\"120\" y2=\"24\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2776734</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,12.706308)\">726</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2c0c9f85-2114-421e-8680-aba9bca413f7' class='xr-section-summary-in' type='checkbox'  ><label for='section-2c0c9f85-2114-421e-8680-aba9bca413f7' class='xr-section-summary' >Indexes: <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-index-name'><div>feature_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e9120071-24ed-4880-a3fa-c5487585fa0c' class='xr-index-data-in' type='checkbox'/><label for='index-e9120071-24ed-4880-a3fa-c5487585fa0c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([       101,        179,        181,        183,        185,        843,\n",
       "              845,        847,        849,        851,\n",
       "       ...\n",
       "       1180001795, 1180001796, 1180001797, 1180001798, 1180001799, 1180001800,\n",
       "       1180001801, 1180001802, 1180001803, 1180001804],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;feature_id&#x27;, length=2776734))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>reference_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f94b35a2-f58c-438c-8973-27486a9f3bef' class='xr-index-data-in' type='checkbox'/><label for='index-f94b35a2-f58c-438c-8973-27486a9f3bef' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-08-06 23:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;reference_time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-835c7d8a-bd6d-416a-a048-c4903fffccd6' class='xr-index-data-in' type='checkbox'/><label for='index-835c7d8a-bd6d-416a-a048-c4903fffccd6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-08-07 00:00:00&#x27;, &#x27;2024-08-07 01:00:00&#x27;,\n",
       "               &#x27;2024-08-07 02:00:00&#x27;, &#x27;2024-08-07 03:00:00&#x27;,\n",
       "               &#x27;2024-08-07 04:00:00&#x27;, &#x27;2024-08-07 05:00:00&#x27;,\n",
       "               &#x27;2024-08-07 06:00:00&#x27;, &#x27;2024-08-07 07:00:00&#x27;,\n",
       "               &#x27;2024-08-07 08:00:00&#x27;, &#x27;2024-08-07 09:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2024-09-05 20:00:00&#x27;, &#x27;2024-09-05 21:00:00&#x27;,\n",
       "               &#x27;2024-09-05 22:00:00&#x27;, &#x27;2024-09-05 23:00:00&#x27;,\n",
       "               &#x27;2024-09-06 00:00:00&#x27;, &#x27;2024-09-06 01:00:00&#x27;,\n",
       "               &#x27;2024-09-06 02:00:00&#x27;, &#x27;2024-09-06 03:00:00&#x27;,\n",
       "               &#x27;2024-09-06 04:00:00&#x27;, &#x27;2024-09-06 05:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=726, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3932c330-d38f-423a-bbaa-8f4f1a06c9bd' class='xr-section-summary-in' type='checkbox'  ><label for='section-3932c330-d38f-423a-bbaa-8f4f1a06c9bd' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>NWM_version_number :</span></dt><dd>v3.0</dd><dt><span>TITLE :</span></dt><dd>OUTPUT FROM NWM v3.0</dd><dt><span>cdm_datatype :</span></dt><dd>Station</dd><dt><span>code_version :</span></dt><dd>v5.3.0-alpha1</dd><dt><span>dev :</span></dt><dd>dev_ prefix indicates development/internal meta data</dd><dt><span>dev_NOAH_TIMESTEP :</span></dt><dd>3600</dd><dt><span>dev_OVRTSWCRT :</span></dt><dd>1</dd><dt><span>dev_channelBucket_only :</span></dt><dd>0</dd><dt><span>dev_channel_only :</span></dt><dd>0</dd><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>model_configuration :</span></dt><dd>short_range</dd><dt><span>model_initialization_time :</span></dt><dd>2024-08-06_23:00:00</dd><dt><span>model_output_type :</span></dt><dd>channel_rt</dd><dt><span>model_output_valid_time :</span></dt><dd>2024-08-07_00:00:00</dd><dt><span>model_total_valid_times :</span></dt><dd>18</dd><dt><span>proj4 :</span></dt><dd>+proj=lcc +units=m +a=6370000.0 +b=6370000.0 +lat_1=30.0 +lat_2=60.0 +lat_0=40.0 +lon_0=-97.0 +x_0=0 +y_0=0 +k_0=1.0 +nadgrids=@</dd><dt><span>station_dimension :</span></dt><dd>feature_id</dd><dt><span>stream_order_output :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
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       "<xarray.Dataset> Size: 97GB\n",
       "Dimensions:         (feature_id: 2776734, time: 726, reference_time: 1)\n",
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       "  * feature_id      (feature_id) int64 22MB 101 179 ... 1180001803 1180001804\n",
       "    latitude        (feature_id) float32 11MB dask.array<chunksize=(2776734,), meta=np.ndarray>\n",
       "    longitude       (feature_id) float32 11MB dask.array<chunksize=(2776734,), meta=np.ndarray>\n",
       "  * reference_time  (reference_time) datetime64[ns] 8B 2024-08-06T23:00:00\n",
       "  * time            (time) datetime64[ns] 6kB 2024-08-07 ... 2024-09-06T05:00:00\n",
       "Data variables:\n",
       "    altitude        (feature_id) float32 11MB dask.array<chunksize=(2776734,), meta=np.ndarray>\n",
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       "    qSfcLatRunoff   (time, feature_id) float64 16GB dask.array<chunksize=(1, 2776734), meta=np.ndarray>\n",
       "    streamflow      (time, feature_id) float64 16GB dask.array<chunksize=(1, 2776734), meta=np.ndarray>\n",
       "    terminal_node   (feature_id) float64 22MB dask.array<chunksize=(2776734,), meta=np.ndarray>\n",
       "    to_link_id      (feature_id) float64 22MB dask.array<chunksize=(2776734,), meta=np.ndarray>\n",
       "    velocity        (time, feature_id) float64 16GB dask.array<chunksize=(1, 2776734), meta=np.ndarray>\n",
       "Attributes: (12/19)\n",
       "    Conventions:                CF-1.6\n",
       "    NWM_version_number:         v3.0\n",
       "    TITLE:                      OUTPUT FROM NWM v3.0\n",
       "    cdm_datatype:               Station\n",
       "    code_version:               v5.3.0-alpha1\n",
       "    dev:                        dev_ prefix indicates development/internal me...\n",
       "    ...                         ...\n",
       "    model_output_type:          channel_rt\n",
       "    model_output_valid_time:    2024-08-07_00:00:00\n",
       "    model_total_valid_times:    18\n",
       "    proj4:                      +proj=lcc +units=m +a=6370000.0 +b=6370000.0 ...\n",
       "    station_dimension:          feature_id\n",
       "    stream_order_output:        1"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat = catalog['NWM_Best_CONUS_Short_Range']\n",
    "ds_sr = cat.to_dask()\n",
    "ds_sr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9feaa38e-b7cd-47ea-8a42-844136484806",
   "metadata": {},
   "source": [
    "\n",
    "### Select the catalog entry to open for plotting\n",
    "\n",
    "\n",
    "&nbsp;\n",
    "Open the 'NWM_Best_Alaska_Medium_Range' Intake entry, and return an Xarray dataset, similar to Short Range above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cd1bf9a8-6f1c-4a79-913a-d7e9d822421e",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "  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",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 17GB\n",
       "Dimensions:         (feature_id: 391528, time: 907, reference_time: 1)\n",
       "Coordinates:\n",
       "  * feature_id      (feature_id) int64 3MB 11 12 ... 75005400047364\n",
       "    latitude        (feature_id) float32 2MB dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;\n",
       "    longitude       (feature_id) float32 2MB dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;\n",
       "  * reference_time  (reference_time) datetime64[ns] 8B 2024-03-25T12:00:00\n",
       "  * time            (time) datetime64[ns] 7kB 2024-03-25T18:00:00 ... 2024-05...\n",
       "Data variables:\n",
       "    altitude        (feature_id) float32 2MB dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;\n",
       "    crs             (time) object 7kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    from_link_id    (feature_id) float64 3MB dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;\n",
       "    link_id         (feature_id) float64 3MB dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;\n",
       "    nudge           (time, feature_id) float64 3GB dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;\n",
       "    qBtmVertRunoff  (time, feature_id) float64 3GB dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;\n",
       "    qBucket         (time, feature_id) float64 3GB dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;\n",
       "    qSfcLatRunoff   (time, feature_id) float64 3GB dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;\n",
       "    streamflow      (time, feature_id) float64 3GB dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;\n",
       "    terminal_node   (feature_id) float64 3MB dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;\n",
       "    to_link_id      (feature_id) float64 3MB dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;\n",
       "    velocity        (time, feature_id) float64 3GB dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;\n",
       "Attributes: (12/20)\n",
       "    Conventions:                CF-1.6\n",
       "    NWM_version_number:         v3.0\n",
       "    TITLE:                      OUTPUT FROM NWM v3.0\n",
       "    cdm_datatype:               Station\n",
       "    code_version:               v5.3.0-alpha1\n",
       "    dev:                        dev_ prefix indicates development/internal me...\n",
       "    ...                         ...\n",
       "    model_output_type:          channel_rt\n",
       "    model_output_valid_time:    2024-03-25_18:00:00\n",
       "    model_total_valid_times:    240\n",
       "    proj4:                      +proj=stere +lat_0=90 +lat_ts=60 +lon_0=-135 ...\n",
       "    station_dimension:          feature_id\n",
       "    stream_order_output:        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-107919ff-d05e-4f08-8932-e843a3be2509' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-107919ff-d05e-4f08-8932-e843a3be2509' 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'>feature_id</span>: 391528</li><li><span class='xr-has-index'>time</span>: 907</li><li><span class='xr-has-index'>reference_time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b6b7c0b0-1cbb-4a6d-8669-f19d15a05a8e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b6b7c0b0-1cbb-4a6d-8669-f19d15a05a8e' 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'>feature_id</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>11 12 ... 75005400047364</div><input id='attrs-e7eda08c-e90b-44f4-a7a6-7715f7432cff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7eda08c-e90b-44f4-a7a6-7715f7432cff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffac9e66-a5ec-41b5-9fac-b969b5b55593' class='xr-var-data-in' type='checkbox'><label for='data-ffac9e66-a5ec-41b5-9fac-b969b5b55593' 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><dt><span>comment :</span></dt><dd>NHDPlusv2 ComIDs within CONUS, arbitrary Reach IDs outside of CONUS</dd><dt><span>long_name :</span></dt><dd>Reach ID</dd></dl></div><div class='xr-var-data'><pre>array([            11,             12,             13, ..., 75005400047362,\n",
       "       75005400047363, 75005400047364])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;</div><input id='attrs-56344e90-ecdb-48ac-a5ea-7f1f226f21e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56344e90-ecdb-48ac-a5ea-7f1f226f21e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d2bade7-bb34-4a02-8461-c0271ed6a72c' class='xr-var-data-in' type='checkbox'><label for='data-6d2bade7-bb34-4a02-8461-c0271ed6a72c' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.49 MiB </td>\n",
       "                        <td> 1.49 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (391528,) </td>\n",
       "                        <td> (391528,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
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       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >391528</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;</div><input id='attrs-a4572a4f-cd32-4df1-bc52-b41f932720f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a4572a4f-cd32-4df1-bc52-b41f932720f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01f2cc05-a95f-49ae-8287-81e92711433e' class='xr-var-data-in' type='checkbox'><label for='data-01f2cc05-a95f-49ae-8287-81e92711433e' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.49 MiB </td>\n",
       "                        <td> 1.49 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (391528,) </td>\n",
       "                        <td> (391528,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "\n",
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       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
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       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >391528</text>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>reference_time</span></div><div class='xr-var-dims'>(reference_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-03-25T12:00:00</div><input id='attrs-e0992459-2fe1-43dd-92c8-06500774e850' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0992459-2fe1-43dd-92c8-06500774e850' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1227542-4787-47a3-bc35-611d9b385c89' class='xr-var-data-in' type='checkbox'><label for='data-b1227542-4787-47a3-bc35-611d9b385c89' 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>model initialization time</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-03-25T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</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'>2024-03-25T18:00:00 ... 2024-05-...</div><input id='attrs-47b818b7-aa10-45f8-bcbe-fa8d82805d8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47b818b7-aa10-45f8-bcbe-fa8d82805d8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4836ec6f-e857-4850-9c64-cf729d9ed04b' class='xr-var-data-in' type='checkbox'><label for='data-4836ec6f-e857-4850-9c64-cf729d9ed04b' 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>valid output time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>valid_max :</span></dt><dd>28537200</dd><dt><span>valid_min :</span></dt><dd>28522860</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-03-25T18:00:00.000000000&#x27;, &#x27;2024-03-25T19:00:00.000000000&#x27;,\n",
       "       &#x27;2024-03-25T20:00:00.000000000&#x27;, ..., &#x27;2024-05-02T10:00:00.000000000&#x27;,\n",
       "       &#x27;2024-05-02T11:00:00.000000000&#x27;, &#x27;2024-05-02T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a90254ff-ef1c-4897-8cfa-442c468b3f46' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a90254ff-ef1c-4897-8cfa-442c468b3f46' 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>altitude</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;</div><input id='attrs-c372fa70-1c04-4406-a6ff-110e762288c7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c372fa70-1c04-4406-a6ff-110e762288c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bfac47c-3c90-4902-aebe-063bf92401ca' class='xr-var-data-in' type='checkbox'><label for='data-7bfac47c-3c90-4902-aebe-063bf92401ca' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.49 MiB </td>\n",
       "                        <td> 1.49 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (391528,) </td>\n",
       "                        <td> (391528,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-d910a043-04c3-4f55-9e28-60f1b25322de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d910a043-04c3-4f55-9e28-60f1b25322de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-817cf909-ce82-46e7-bf38-4251ee2fefcd' class='xr-var-data-in' type='checkbox'><label for='data-817cf909-ce82-46e7-bf38-4251ee2fefcd' 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>_CoordinateAxes :</span></dt><dd>latitude longitude</dd><dt><span>esri_pe_string :</span></dt><dd>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8.98315284119521E-09;0.001;0.001;IsHighPrecision</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.2572326660156</dd><dt><span>long_name :</span></dt><dd>CRS definition</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.5</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8.98315284119521E-09;0.001;0.001;IsHighPrecision</dd><dt><span>transform_name :</span></dt><dd>latitude longitude</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 7.09 kiB </td>\n",
       "                        <td> 8 B </td>\n",
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       "                    <tr>\n",
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       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 907 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                        <td> 2.99 MiB </td>\n",
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       "                    <tr>\n",
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       "                        <td> (391528,) </td>\n",
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       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nudge</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;</div><input id='attrs-c773bfcb-627c-4ac0-af27-95869a8fc5bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c773bfcb-627c-4ac0-af27-95869a8fc5bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25112d2f-4941-4bdf-a06a-b8fab0855976' class='xr-var-data-in' type='checkbox'><label for='data-25112d2f-4941-4bdf-a06a-b8fab0855976' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Amount of stream flow alteration</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[-5000000, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.65 GiB </td>\n",
       "                        <td> 2.99 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (907, 391528) </td>\n",
       "                        <td> (1, 391528) </td>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> 907 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qBtmVertRunoff</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;</div><input id='attrs-97a263f5-b852-404c-886e-619e9eba2206' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97a263f5-b852-404c-886e-619e9eba2206' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e39d338-3a0a-4973-8084-06114ee73c56' class='xr-var-data-in' type='checkbox'><label for='data-7e39d338-3a0a-4973-8084-06114ee73c56' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Runoff from bottom of soil to bucket</dd><dt><span>units :</span></dt><dd>m3</dd><dt><span>valid_range :</span></dt><dd>[0, 20000000]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.65 GiB </td>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (907, 391528) </td>\n",
       "                        <td> (1, 391528) </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qBucket</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;</div><input id='attrs-ee2fdd97-dc16-40e8-8b11-6b01b7a4a73d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee2fdd97-dc16-40e8-8b11-6b01b7a4a73d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99b2561e-f2b5-473b-a626-523ca3dc301b' class='xr-var-data-in' type='checkbox'><label for='data-99b2561e-f2b5-473b-a626-523ca3dc301b' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Flux from gw bucket</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 2000000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.65 GiB </td>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (907, 391528) </td>\n",
       "                        <td> (1, 391528) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 907 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qSfcLatRunoff</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;</div><input id='attrs-df4ebef9-9637-4612-a6db-e0cfd7b8ce72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df4ebef9-9637-4612-a6db-e0cfd7b8ce72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4f9415d-d18e-428e-8267-550c2a9315e6' class='xr-var-data-in' type='checkbox'><label for='data-d4f9415d-d18e-428e-8267-550c2a9315e6' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Runoff from terrain routing</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 2000000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.65 GiB </td>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (907, 391528) </td>\n",
       "                        <td> (1, 391528) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 907 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>streamflow</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;</div><input id='attrs-60304ae1-0781-47b8-99fa-759a7d252798' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60304ae1-0781-47b8-99fa-759a7d252798' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34c4e486-5af2-45b7-a1a7-fc83e925ab7c' class='xr-var-data-in' type='checkbox'><label for='data-34c4e486-5af2-45b7-a1a7-fc83e925ab7c' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>River Flow</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.65 GiB </td>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (907, 391528) </td>\n",
       "                        <td> (1, 391528) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 907 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "  <!-- Horizontal lines -->\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>terminal_node</span></div><div class='xr-var-dims'>(feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(391528,), meta=np.ndarray&gt;</div><input id='attrs-1dc56c64-1377-4644-a006-4ce4be476d0c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1dc56c64-1377-4644-a006-4ce4be476d0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-238a16af-19bc-4077-b293-d85c7a9a57ec' class='xr-var-data-in' type='checkbox'><label for='data-238a16af-19bc-4077-b293-d85c7a9a57ec' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (391528,) </td>\n",
       "                        <td> (391528,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                        <td> 2.99 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (391528,) </td>\n",
       "                        <td> (391528,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>velocity</span></div><div class='xr-var-dims'>(time, feature_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 391528), meta=np.ndarray&gt;</div><input id='attrs-24ce6dad-fc0b-4e44-801b-bb1158d3db76' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24ce6dad-fc0b-4e44-801b-bb1158d3db76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d5d24fc-1077-4798-a97b-f142071ef384' class='xr-var-data-in' type='checkbox'><label for='data-5d5d24fc-1077-4798-a97b-f142071ef384' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>River Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> 2.65 GiB </td>\n",
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       "                        <td> (1, 391528) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 907 chunks in 2 graph layers </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-e3e7fc14-878a-4cc3-9c67-95bf9a102b23' class='xr-section-summary-in' type='checkbox'  ><label for='section-e3e7fc14-878a-4cc3-9c67-95bf9a102b23' class='xr-section-summary' >Indexes: <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-index-name'><div>feature_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-787de3b9-e22f-47d3-ae5e-ed1ec4a501b5' class='xr-index-data-in' type='checkbox'/><label for='index-787de3b9-e22f-47d3-ae5e-ed1ec4a501b5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([            11,             12,             13,             14,\n",
       "                        15,             16, 19020190000001, 19020190000002,\n",
       "            19020190000003, 19020190000004,\n",
       "            ...\n",
       "            75005400047354, 75005400047355, 75005400047357, 75005400047358,\n",
       "            75005400047359, 75005400047360, 75005400047361, 75005400047362,\n",
       "            75005400047363, 75005400047364],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;feature_id&#x27;, length=391528))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>reference_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e398cc59-3be5-4d9e-98d3-ebe0ef7df0ac' class='xr-index-data-in' type='checkbox'/><label for='index-e398cc59-3be5-4d9e-98d3-ebe0ef7df0ac' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-03-25 12:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;reference_time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7c8f6e91-3acf-41f5-b4c0-1cbff8fe87f5' class='xr-index-data-in' type='checkbox'/><label for='index-7c8f6e91-3acf-41f5-b4c0-1cbff8fe87f5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-03-25 18:00:00&#x27;, &#x27;2024-03-25 19:00:00&#x27;,\n",
       "               &#x27;2024-03-25 20:00:00&#x27;, &#x27;2024-03-25 21:00:00&#x27;,\n",
       "               &#x27;2024-03-25 22:00:00&#x27;, &#x27;2024-03-25 23:00:00&#x27;,\n",
       "               &#x27;2024-03-26 00:00:00&#x27;, &#x27;2024-03-26 01:00:00&#x27;,\n",
       "               &#x27;2024-03-26 02:00:00&#x27;, &#x27;2024-03-26 03:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2024-05-02 03:00:00&#x27;, &#x27;2024-05-02 04:00:00&#x27;,\n",
       "               &#x27;2024-05-02 05:00:00&#x27;, &#x27;2024-05-02 06:00:00&#x27;,\n",
       "               &#x27;2024-05-02 07:00:00&#x27;, &#x27;2024-05-02 08:00:00&#x27;,\n",
       "               &#x27;2024-05-02 09:00:00&#x27;, &#x27;2024-05-02 10:00:00&#x27;,\n",
       "               &#x27;2024-05-02 11:00:00&#x27;, &#x27;2024-05-02 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=907, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1d5ec0fc-7794-4fa3-ad2b-1a231a2f659e' class='xr-section-summary-in' type='checkbox'  ><label for='section-1d5ec0fc-7794-4fa3-ad2b-1a231a2f659e' class='xr-section-summary' >Attributes: <span>(20)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>NWM_version_number :</span></dt><dd>v3.0</dd><dt><span>TITLE :</span></dt><dd>OUTPUT FROM NWM v3.0</dd><dt><span>cdm_datatype :</span></dt><dd>Station</dd><dt><span>code_version :</span></dt><dd>v5.3.0-alpha1</dd><dt><span>dev :</span></dt><dd>dev_ prefix indicates development/internal meta data</dd><dt><span>dev_NOAH_TIMESTEP :</span></dt><dd>3600</dd><dt><span>dev_OVRTSWCRT :</span></dt><dd>1</dd><dt><span>dev_channelBucket_only :</span></dt><dd>0</dd><dt><span>dev_channel_only :</span></dt><dd>0</dd><dt><span>ensemble_member_number :</span></dt><dd>1</dd><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>model_configuration :</span></dt><dd>medium_range</dd><dt><span>model_initialization_time :</span></dt><dd>2024-03-25_12:00:00</dd><dt><span>model_output_type :</span></dt><dd>channel_rt</dd><dt><span>model_output_valid_time :</span></dt><dd>2024-03-25_18:00:00</dd><dt><span>model_total_valid_times :</span></dt><dd>240</dd><dt><span>proj4 :</span></dt><dd>+proj=stere +lat_0=90 +lat_ts=60 +lon_0=-135 +x_0=0 +y_0=0 +R=6370000 +units=m +no_defs</dd><dt><span>station_dimension :</span></dt><dd>feature_id</dd><dt><span>stream_order_output :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 17GB\n",
       "Dimensions:         (feature_id: 391528, time: 907, reference_time: 1)\n",
       "Coordinates:\n",
       "  * feature_id      (feature_id) int64 3MB 11 12 ... 75005400047364\n",
       "    latitude        (feature_id) float32 2MB dask.array<chunksize=(391528,), meta=np.ndarray>\n",
       "    longitude       (feature_id) float32 2MB dask.array<chunksize=(391528,), meta=np.ndarray>\n",
       "  * reference_time  (reference_time) datetime64[ns] 8B 2024-03-25T12:00:00\n",
       "  * time            (time) datetime64[ns] 7kB 2024-03-25T18:00:00 ... 2024-05...\n",
       "Data variables:\n",
       "    altitude        (feature_id) float32 2MB dask.array<chunksize=(391528,), meta=np.ndarray>\n",
       "    crs             (time) object 7kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    from_link_id    (feature_id) float64 3MB dask.array<chunksize=(391528,), meta=np.ndarray>\n",
       "    link_id         (feature_id) float64 3MB dask.array<chunksize=(391528,), meta=np.ndarray>\n",
       "    nudge           (time, feature_id) float64 3GB dask.array<chunksize=(1, 391528), meta=np.ndarray>\n",
       "    qBtmVertRunoff  (time, feature_id) float64 3GB dask.array<chunksize=(1, 391528), meta=np.ndarray>\n",
       "    qBucket         (time, feature_id) float64 3GB dask.array<chunksize=(1, 391528), meta=np.ndarray>\n",
       "    qSfcLatRunoff   (time, feature_id) float64 3GB dask.array<chunksize=(1, 391528), meta=np.ndarray>\n",
       "    streamflow      (time, feature_id) float64 3GB dask.array<chunksize=(1, 391528), meta=np.ndarray>\n",
       "    terminal_node   (feature_id) float64 3MB dask.array<chunksize=(391528,), meta=np.ndarray>\n",
       "    to_link_id      (feature_id) float64 3MB dask.array<chunksize=(391528,), meta=np.ndarray>\n",
       "    velocity        (time, feature_id) float64 3GB dask.array<chunksize=(1, 391528), meta=np.ndarray>\n",
       "Attributes: (12/20)\n",
       "    Conventions:                CF-1.6\n",
       "    NWM_version_number:         v3.0\n",
       "    TITLE:                      OUTPUT FROM NWM v3.0\n",
       "    cdm_datatype:               Station\n",
       "    code_version:               v5.3.0-alpha1\n",
       "    dev:                        dev_ prefix indicates development/internal me...\n",
       "    ...                         ...\n",
       "    model_output_type:          channel_rt\n",
       "    model_output_valid_time:    2024-03-25_18:00:00\n",
       "    model_total_valid_times:    240\n",
       "    proj4:                      +proj=stere +lat_0=90 +lat_ts=60 +lon_0=-135 ...\n",
       "    station_dimension:          feature_id\n",
       "    stream_order_output:        1"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat = catalog['NWM_Best_Alaska_Medium_Range']\n",
    "ds = cat.to_dask()\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b252f5ec-27d7-4c6e-9e2f-1aa69d244076",
   "metadata": {},
   "source": [
    "\n",
    "&nbsp;\n",
    "\n",
    "**Set the set the feature ID and time bounds to extract**\n",
    "\n",
    "Use a two week time window (-7 days to +7 days from present) to plot streamflow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "94a99d8f-66c1-4368-a8a1-3c19cd75fcef",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "feature_id = 19020190088835\n",
    "\n",
    "# create a time window of +-1 week\n",
    "start_t = datetime.datetime.now() - datetime.timedelta(days=7)\n",
    "end_t = datetime.datetime.now() + datetime.timedelta(days=7)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43533c31-8fcb-4ca0-98cd-27bc5fa0e3f5",
   "metadata": {},
   "source": [
    "&nbsp;\n",
    "\n",
    "**Extract the data for the time slice and feature ID**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b51bdef6-fa37-4567-bffa-86a0896a1e9a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\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-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\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 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\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: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",
       "  padding-bottom: 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-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\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",
       "  margin-bottom: 0;\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",
       "}\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",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\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-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",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 22kB\n",
       "Dimensions:         (time: 336, reference_time: 1)\n",
       "Coordinates:\n",
       "    feature_id      int64 8B 19020190088835\n",
       "    latitude        float32 4B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
       "    longitude       float32 4B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
       "  * reference_time  (reference_time) datetime64[ns] 8B 2024-03-25T12:00:00\n",
       "  * time            (time) datetime64[ns] 3kB 2024-04-15T15:00:00 ... 2024-04...\n",
       "Data variables:\n",
       "    altitude        float32 4B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
       "    crs             (time) object 3kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    from_link_id    float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
       "    link_id         float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
       "    nudge           (time) float64 3kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    qBtmVertRunoff  (time) float64 3kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    qBucket         (time) float64 3kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    qSfcLatRunoff   (time) float64 3kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    streamflow      (time) float64 3kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    terminal_node   float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
       "    to_link_id      float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
       "    velocity        (time) float64 3kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "Attributes: (12/20)\n",
       "    Conventions:                CF-1.6\n",
       "    NWM_version_number:         v3.0\n",
       "    TITLE:                      OUTPUT FROM NWM v3.0\n",
       "    cdm_datatype:               Station\n",
       "    code_version:               v5.3.0-alpha1\n",
       "    dev:                        dev_ prefix indicates development/internal me...\n",
       "    ...                         ...\n",
       "    model_output_type:          channel_rt\n",
       "    model_output_valid_time:    2024-03-25_18:00:00\n",
       "    model_total_valid_times:    240\n",
       "    proj4:                      +proj=stere +lat_0=90 +lat_ts=60 +lon_0=-135 ...\n",
       "    station_dimension:          feature_id\n",
       "    stream_order_output:        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-f628fe3d-eada-4b73-a745-8ea718d0ad56' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f628fe3d-eada-4b73-a745-8ea718d0ad56' 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'>time</span>: 336</li><li><span class='xr-has-index'>reference_time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6dfcf605-1c11-483b-91e9-35d793bb41b1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6dfcf605-1c11-483b-91e9-35d793bb41b1' 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>feature_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>19020190088835</div><input id='attrs-f0fcfec2-3951-44a2-a3b7-20c0bf8c7f0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0fcfec2-3951-44a2-a3b7-20c0bf8c7f0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19701c28-3afd-4d4c-b163-26b53158219f' class='xr-var-data-in' type='checkbox'><label for='data-19701c28-3afd-4d4c-b163-26b53158219f' 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><dt><span>comment :</span></dt><dd>NHDPlusv2 ComIDs within CONUS, arbitrary Reach IDs outside of CONUS</dd><dt><span>long_name :</span></dt><dd>Reach ID</dd></dl></div><div class='xr-var-data'><pre>array(19020190088835)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-9dc7b9f7-80bf-4f58-bd61-590c5d9ee814' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9dc7b9f7-80bf-4f58-bd61-590c5d9ee814' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aa07121-25a0-4cd6-9ea5-ae980963fe1d' class='xr-var-data-in' type='checkbox'><label for='data-9aa07121-25a0-4cd6-9ea5-ae980963fe1d' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4 B </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-53fe29c0-3c8b-40ee-978f-82438425f7d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53fe29c0-3c8b-40ee-978f-82438425f7d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1788fa43-a229-4a50-92e4-87ee10d22a5a' class='xr-var-data-in' type='checkbox'><label for='data-1788fa43-a229-4a50-92e4-87ee10d22a5a' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4 B </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>reference_time</span></div><div class='xr-var-dims'>(reference_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-03-25T12:00:00</div><input id='attrs-27ae6f33-32ad-4bff-8d0f-45b9528b090f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27ae6f33-32ad-4bff-8d0f-45b9528b090f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc2bd0b1-4a0d-4518-8f4d-729c1e0eb46d' class='xr-var-data-in' type='checkbox'><label for='data-cc2bd0b1-4a0d-4518-8f4d-729c1e0eb46d' 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>model initialization time</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-03-25T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</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'>2024-04-15T15:00:00 ... 2024-04-...</div><input id='attrs-152d84f1-843d-4cfd-931f-3de1c289f74a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-152d84f1-843d-4cfd-931f-3de1c289f74a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7715f342-6153-4ac7-9395-03a9e1339508' class='xr-var-data-in' type='checkbox'><label for='data-7715f342-6153-4ac7-9395-03a9e1339508' 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>valid output time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>valid_max :</span></dt><dd>28537200</dd><dt><span>valid_min :</span></dt><dd>28522860</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-04-15T15:00:00.000000000&#x27;, &#x27;2024-04-15T16:00:00.000000000&#x27;,\n",
       "       &#x27;2024-04-15T17:00:00.000000000&#x27;, ..., &#x27;2024-04-29T12:00:00.000000000&#x27;,\n",
       "       &#x27;2024-04-29T13:00:00.000000000&#x27;, &#x27;2024-04-29T14:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-453eab26-2cb8-4858-8a4f-e567e013ab93' class='xr-section-summary-in' type='checkbox'  checked><label for='section-453eab26-2cb8-4858-8a4f-e567e013ab93' 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>altitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-8d3aa81f-212d-4907-8961-6e4e3a62d983' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8d3aa81f-212d-4907-8961-6e4e3a62d983' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ee14b5a-06b2-4a4f-8ebf-787dd6cc8cd5' class='xr-var-data-in' type='checkbox'><label for='data-5ee14b5a-06b2-4a4f-8ebf-787dd6cc8cd5' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4 B </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-bbee30f9-155c-4d8f-861a-fdd3b7446592' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbee30f9-155c-4d8f-861a-fdd3b7446592' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46c66b3f-ef3c-490f-85f0-3d80adabfd4b' class='xr-var-data-in' type='checkbox'><label for='data-46c66b3f-ef3c-490f-85f0-3d80adabfd4b' 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>_CoordinateAxes :</span></dt><dd>latitude longitude</dd><dt><span>esri_pe_string :</span></dt><dd>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8.98315284119521E-09;0.001;0.001;IsHighPrecision</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.2572326660156</dd><dt><span>long_name :</span></dt><dd>CRS definition</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.5</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8.98315284119521E-09;0.001;0.001;IsHighPrecision</dd><dt><span>transform_name :</span></dt><dd>latitude longitude</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.62 kiB </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (336,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 336 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>from_link_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-24b87068-fdd3-454c-b1d1-d5c65b1566b1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24b87068-fdd3-454c-b1d1-d5c65b1566b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ee561f3-0f4d-4fae-9cf0-8b0246645619' class='xr-var-data-in' type='checkbox'><label for='data-8ee561f3-0f4d-4fae-9cf0-8b0246645619' 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'><table>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>link_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-5f2c467a-8ead-40a8-b828-c5a560c07ecf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f2c467a-8ead-40a8-b828-c5a560c07ecf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88aee0f8-51a6-47cf-af68-bee1d00fc1a4' class='xr-var-data-in' type='checkbox'><label for='data-88aee0f8-51a6-47cf-af68-bee1d00fc1a4' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nudge</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-6a1dd078-2ff9-4b46-9853-9b03cb3f5e39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a1dd078-2ff9-4b46-9853-9b03cb3f5e39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee0a3574-1add-4d9c-84da-3d314e1d564f' class='xr-var-data-in' type='checkbox'><label for='data-ee0a3574-1add-4d9c-84da-3d314e1d564f' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Amount of stream flow alteration</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[-5000000, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.62 kiB </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (336,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 336 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qBtmVertRunoff</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-8a490b3f-9d07-45bb-9396-d23dc3cfbe44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a490b3f-9d07-45bb-9396-d23dc3cfbe44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-686b559a-079e-441e-ad6a-ada9eb70226e' class='xr-var-data-in' type='checkbox'><label for='data-686b559a-079e-441e-ad6a-ada9eb70226e' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Runoff from bottom of soil to bucket</dd><dt><span>units :</span></dt><dd>m3</dd><dt><span>valid_range :</span></dt><dd>[0, 20000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.62 kiB </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (336,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 336 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qBucket</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-31e41080-4102-470f-a30a-4dc9fc567477' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31e41080-4102-470f-a30a-4dc9fc567477' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37ebb208-83ee-4e85-9dde-6b3824674f10' class='xr-var-data-in' type='checkbox'><label for='data-37ebb208-83ee-4e85-9dde-6b3824674f10' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Flux from gw bucket</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 2000000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.62 kiB </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (336,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 336 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qSfcLatRunoff</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-e39fe5f5-abdf-4cb4-a54d-16d5c195fee0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e39fe5f5-abdf-4cb4-a54d-16d5c195fee0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdd2a3b7-5281-4ad0-be65-3d56363aff13' class='xr-var-data-in' type='checkbox'><label for='data-fdd2a3b7-5281-4ad0-be65-3d56363aff13' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Runoff from terrain routing</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 2000000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.62 kiB </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (336,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 336 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>streamflow</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-669c168e-d84d-4065-8d0b-b6e8f88aa04d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-669c168e-d84d-4065-8d0b-b6e8f88aa04d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c8de667-6358-414a-9ee8-54f5639a4094' class='xr-var-data-in' type='checkbox'><label for='data-9c8de667-6358-414a-9ee8-54f5639a4094' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>River Flow</dd><dt><span>units :</span></dt><dd>m3 s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.62 kiB </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (336,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 336 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>terminal_node</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-f3ef2975-e2fc-400b-a331-d496efd3b651' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3ef2975-e2fc-400b-a331-d496efd3b651' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c25acec-4f2e-4e0f-8625-c739232534c3' class='xr-var-data-in' type='checkbox'><label for='data-8c25acec-4f2e-4e0f-8625-c739232534c3' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>to_link_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-53e14d40-677e-4aa0-a01c-4daacaa924b8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53e14d40-677e-4aa0-a01c-4daacaa924b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-495abdc7-a4af-42dc-a114-e24530d09c56' class='xr-var-data-in' type='checkbox'><label for='data-495abdc7-a4af-42dc-a114-e24530d09c56' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>velocity</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-ec086d23-54bd-44b8-adb3-975210d8f6bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec086d23-54bd-44b8-adb3-975210d8f6bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00b7fc24-b35d-46f5-83da-92c1312611e2' class='xr-var-data-in' type='checkbox'><label for='data-00b7fc24-b35d-46f5-83da-92c1312611e2' 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>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>River Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>valid_range :</span></dt><dd>[0, 5000000]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.62 kiB </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (336,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 336 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "\n",
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       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
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       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
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       "\n",
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       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >336</text>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-80711548-af5b-4e86-8f54-bd1633816714' class='xr-section-summary-in' type='checkbox'  ><label for='section-80711548-af5b-4e86-8f54-bd1633816714' class='xr-section-summary' >Indexes: <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-index-name'><div>reference_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d35acab0-11b3-4639-835e-676484438cd5' class='xr-index-data-in' type='checkbox'/><label for='index-d35acab0-11b3-4639-835e-676484438cd5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-03-25 12:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;reference_time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-735246a1-f1a7-459e-afdc-1697251ec09a' class='xr-index-data-in' type='checkbox'/><label for='index-735246a1-f1a7-459e-afdc-1697251ec09a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-04-15 15:00:00&#x27;, &#x27;2024-04-15 16:00:00&#x27;,\n",
       "               &#x27;2024-04-15 17:00:00&#x27;, &#x27;2024-04-15 18:00:00&#x27;,\n",
       "               &#x27;2024-04-15 19:00:00&#x27;, &#x27;2024-04-15 20:00:00&#x27;,\n",
       "               &#x27;2024-04-15 21:00:00&#x27;, &#x27;2024-04-15 22:00:00&#x27;,\n",
       "               &#x27;2024-04-15 23:00:00&#x27;, &#x27;2024-04-16 00:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2024-04-29 05:00:00&#x27;, &#x27;2024-04-29 06:00:00&#x27;,\n",
       "               &#x27;2024-04-29 07:00:00&#x27;, &#x27;2024-04-29 08:00:00&#x27;,\n",
       "               &#x27;2024-04-29 09:00:00&#x27;, &#x27;2024-04-29 10:00:00&#x27;,\n",
       "               &#x27;2024-04-29 11:00:00&#x27;, &#x27;2024-04-29 12:00:00&#x27;,\n",
       "               &#x27;2024-04-29 13:00:00&#x27;, &#x27;2024-04-29 14:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=336, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2b264332-d460-4260-97b1-0c4634412dd0' class='xr-section-summary-in' type='checkbox'  ><label for='section-2b264332-d460-4260-97b1-0c4634412dd0' class='xr-section-summary' >Attributes: <span>(20)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>NWM_version_number :</span></dt><dd>v3.0</dd><dt><span>TITLE :</span></dt><dd>OUTPUT FROM NWM v3.0</dd><dt><span>cdm_datatype :</span></dt><dd>Station</dd><dt><span>code_version :</span></dt><dd>v5.3.0-alpha1</dd><dt><span>dev :</span></dt><dd>dev_ prefix indicates development/internal meta data</dd><dt><span>dev_NOAH_TIMESTEP :</span></dt><dd>3600</dd><dt><span>dev_OVRTSWCRT :</span></dt><dd>1</dd><dt><span>dev_channelBucket_only :</span></dt><dd>0</dd><dt><span>dev_channel_only :</span></dt><dd>0</dd><dt><span>ensemble_member_number :</span></dt><dd>1</dd><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>model_configuration :</span></dt><dd>medium_range</dd><dt><span>model_initialization_time :</span></dt><dd>2024-03-25_12:00:00</dd><dt><span>model_output_type :</span></dt><dd>channel_rt</dd><dt><span>model_output_valid_time :</span></dt><dd>2024-03-25_18:00:00</dd><dt><span>model_total_valid_times :</span></dt><dd>240</dd><dt><span>proj4 :</span></dt><dd>+proj=stere +lat_0=90 +lat_ts=60 +lon_0=-135 +x_0=0 +y_0=0 +R=6370000 +units=m +no_defs</dd><dt><span>station_dimension :</span></dt><dd>feature_id</dd><dt><span>stream_order_output :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 22kB\n",
       "Dimensions:         (time: 336, reference_time: 1)\n",
       "Coordinates:\n",
       "    feature_id      int64 8B 19020190088835\n",
       "    latitude        float32 4B dask.array<chunksize=(), meta=np.ndarray>\n",
       "    longitude       float32 4B dask.array<chunksize=(), meta=np.ndarray>\n",
       "  * reference_time  (reference_time) datetime64[ns] 8B 2024-03-25T12:00:00\n",
       "  * time            (time) datetime64[ns] 3kB 2024-04-15T15:00:00 ... 2024-04...\n",
       "Data variables:\n",
       "    altitude        float32 4B dask.array<chunksize=(), meta=np.ndarray>\n",
       "    crs             (time) object 3kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    from_link_id    float64 8B dask.array<chunksize=(), meta=np.ndarray>\n",
       "    link_id         float64 8B dask.array<chunksize=(), meta=np.ndarray>\n",
       "    nudge           (time) float64 3kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    qBtmVertRunoff  (time) float64 3kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    qBucket         (time) float64 3kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    qSfcLatRunoff   (time) float64 3kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    streamflow      (time) float64 3kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    terminal_node   float64 8B dask.array<chunksize=(), meta=np.ndarray>\n",
       "    to_link_id      float64 8B dask.array<chunksize=(), meta=np.ndarray>\n",
       "    velocity        (time) float64 3kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "Attributes: (12/20)\n",
       "    Conventions:                CF-1.6\n",
       "    NWM_version_number:         v3.0\n",
       "    TITLE:                      OUTPUT FROM NWM v3.0\n",
       "    cdm_datatype:               Station\n",
       "    code_version:               v5.3.0-alpha1\n",
       "    dev:                        dev_ prefix indicates development/internal me...\n",
       "    ...                         ...\n",
       "    model_output_type:          channel_rt\n",
       "    model_output_valid_time:    2024-03-25_18:00:00\n",
       "    model_total_valid_times:    240\n",
       "    proj4:                      +proj=stere +lat_0=90 +lat_ts=60 +lon_0=-135 ...\n",
       "    station_dimension:          feature_id\n",
       "    stream_order_output:        1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "ts_ds = ds.sel(time=slice(start_t, end_t),feature_id=feature_id)\n",
    "ts_ds\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed2346da-cb6d-427e-87a2-8e208d7b743d",
   "metadata": {},
   "source": [
    "&nbsp;\n",
    "\n",
    "\n",
    "**Plot the timeseries data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5dd39036-71a8-4c3b-bf22-1ca7067c7a8f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(ts_ds.time, ts_ds.streamflow[:]*35.3147)\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}