diff --git a/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/rolf_files/example_model_run_pcrglobwb.ipynb b/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/rolf_files/example_model_run_pcrglobwb.ipynb
index 740c41e..9024204 100644
--- a/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/rolf_files/example_model_run_pcrglobwb.ipynb
+++ b/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/rolf_files/example_model_run_pcrglobwb.ipynb
@@ -296,7 +296,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "87144041",
    "metadata": {},
    "outputs": [],
@@ -314,10 +314,78 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "664b32b6-2b4c-49f1-be5a-b451fceb9ecc",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PCRGlobWB: Leven</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>time</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1997-08-01 00:00:00+00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1997-08-02 00:00:00+00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1997-08-03 00:00:00+00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1997-08-04 00:00:00+00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1997-08-05 00:00:00+00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          PCRGlobWB: Leven\n",
+       "time                                      \n",
+       "1997-08-01 00:00:00+00:00              NaN\n",
+       "1997-08-02 00:00:00+00:00              NaN\n",
+       "1997-08-03 00:00:00+00:00              NaN\n",
+       "1997-08-04 00:00:00+00:00              NaN\n",
+       "1997-08-05 00:00:00+00:00              NaN"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "time = pd.date_range(pcrglob.start_time_as_isostr, pcrglob.end_time_as_isostr)\n",
     "timeseries = pd.DataFrame(\n",
@@ -338,12 +406,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "403d55e6",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1997-08-31T00:00:00Z\r"
+     ]
+    }
+   ],
    "source": [
     "while pcrglob.time < pcrglob.end_time:\n",
     "    pcrglob.update()\n",
@@ -377,10 +453,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "id": "23d55863",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['upper_soil_transpiration',\n",
+       " 'snow_water_equivalent',\n",
+       " 'total_runoff',\n",
+       " 'transpiration_from_irrigation',\n",
+       " 'fraction_of_surface_water',\n",
+       " 'bottom_elevation_of_uppermost_layer',\n",
+       " 'industry_water_withdrawal',\n",
+       " 'relativeGroundwaterHead',\n",
+       " 'total_fraction_water_allocation',\n",
+       " 'groundwater_volume_estimate']"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "list(pcrglob.output_var_names)[-15:-5]"
    ]
@@ -395,10 +491,534 @@
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+   "execution_count": 16,
    "id": "b37943a9",
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-   "outputs": [],
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+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 4.91046339e-05, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 4.79916669e-02,\n",
+       "        1.93287036e-03, 6.66666683e-03, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "...\n",
+       "       [0.00000000e+00, 1.21594822e+00, 0.00000000e+00, 7.29166670e-03,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.28425926e-01,\n",
+       "        1.20161705e+01, 7.78807878e-01, 0.00000000e+00],\n",
+       "       [1.01527780e-01, 1.60752311e-01, 4.85277660e-02, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 5.28905272e-01,\n",
+       "        2.90231496e-01, 1.12500013e-04, 1.11747229e+00, 2.33097744e+01,\n",
+       "        8.62268545e-03, 2.06924324e+01, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 1.04861089e-03, 1.62048608e-01,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 1.94502492e-02, 0.00000000e+00, 0.00000000e+00,\n",
+       "        1.29629625e-02, 2.51620375e-02, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 1.62037031e-04, 0.00000000e+00, 1.97702385e-02,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        3.38425934e-02, 1.20212686e+00, 1.79245043e+00, 0.00000000e+00,\n",
+       "        2.29809731e-02, 6.91971600e-01, 4.77314815e-02],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 1.65740743e-01, 9.83796315e-04,\n",
+       "        1.47685185e-02, 1.91782415e-02, 0.00000000e+00]])\n",
+       "Coordinates:\n",
+       "  * latitude   (latitude) float64 120B -116.0 -115.5 -115.1 ... -110.5 -110.1\n",
+       "  * longitude  (longitude) float64 176B 25.04 25.46 25.88 ... 32.96 33.38 33.79</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>longitude</span>: 22</li><li><span class='xr-has-index'>latitude</span>: 15</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f20208ad-9152-4b62-9b50-63b22f957a2d' class='xr-array-in' type='checkbox' checked><label for='section-f20208ad-9152-4b62-9b50-63b22f957a2d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.1657 0.0009838 0.01477 0.01918 0.0</span></div><div class='xr-array-data'><pre>array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 3.47660831e-03, 1.15564466e-01,\n",
+       "        3.52053237e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.03169656e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 1.83333326e-02, 4.51157391e-02,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 4.91046339e-05, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 4.79916669e-02,\n",
+       "        1.93287036e-03, 6.66666683e-03, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "...\n",
+       "       [0.00000000e+00, 1.21594822e+00, 0.00000000e+00, 7.29166670e-03,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.28425926e-01,\n",
+       "        1.20161705e+01, 7.78807878e-01, 0.00000000e+00],\n",
+       "       [1.01527780e-01, 1.60752311e-01, 4.85277660e-02, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 5.28905272e-01,\n",
+       "        2.90231496e-01, 1.12500013e-04, 1.11747229e+00, 2.33097744e+01,\n",
+       "        8.62268545e-03, 2.06924324e+01, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 1.04861089e-03, 1.62048608e-01,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 1.94502492e-02, 0.00000000e+00, 0.00000000e+00,\n",
+       "        1.29629625e-02, 2.51620375e-02, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 1.62037031e-04, 0.00000000e+00, 1.97702385e-02,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        3.38425934e-02, 1.20212686e+00, 1.79245043e+00, 0.00000000e+00,\n",
+       "        2.29809731e-02, 6.91971600e-01, 4.77314815e-02],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 1.65740743e-01, 9.83796315e-04,\n",
+       "        1.47685185e-02, 1.91782415e-02, 0.00000000e+00]])</pre></div></div></li><li class='xr-section-item'><input id='section-c21259fb-324d-4c2f-bea2-7a1896053ba6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c21259fb-324d-4c2f-bea2-7a1896053ba6' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-116.0 -115.5 ... -110.5 -110.1</div><input id='attrs-2dd495a2-73c5-41db-adc6-15fa86eef720' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2dd495a2-73c5-41db-adc6-15fa86eef720' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a67fc518-3a6e-4725-84c1-711a54e59db3' class='xr-var-data-in' type='checkbox'><label for='data-a67fc518-3a6e-4725-84c1-711a54e59db3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-115.958333, -115.541667, -115.125   , -114.708333, -114.291667,\n",
+       "       -113.875   , -113.458333, -113.041667, -112.625   , -112.208333,\n",
+       "       -111.791667, -111.375   , -110.958333, -110.541667, -110.125   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.04 25.46 25.88 ... 33.38 33.79</div><input id='attrs-e8404daa-77ed-4823-8553-353ca53b1a4e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8404daa-77ed-4823-8553-353ca53b1a4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f48356f-cb66-4379-92b8-0fec0b09b14a' class='xr-var-data-in' type='checkbox'><label for='data-4f48356f-cb66-4379-92b8-0fec0b09b14a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([25.041667, 25.458333, 25.875   , 26.291667, 26.708333, 27.125   ,\n",
+       "       27.541667, 27.958333, 28.375   , 28.791667, 29.208333, 29.625   ,\n",
+       "       30.041667, 30.458333, 30.875   , 31.291667, 31.708333, 32.125   ,\n",
+       "       32.541667, 32.958333, 33.375   , 33.791667])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea894f31-2e59-41b4-928c-59e315105a69' class='xr-section-summary-in' type='checkbox'  ><label for='section-ea894f31-2e59-41b4-928c-59e315105a69' 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>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-94faa792-4933-470f-8a2c-d2ece1cfc734' class='xr-index-data-in' type='checkbox'/><label for='index-94faa792-4933-470f-8a2c-d2ece1cfc734' 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([-115.95833333335896, -115.54166666669246, -115.12500000002596,\n",
+       "       -114.70833333335946, -114.29166666669296, -113.87500000002646,\n",
+       "       -113.45833333335996, -113.04166666669346, -112.62500000002696,\n",
+       "       -112.20833333336046, -111.79166666669396, -111.37500000002746,\n",
+       "       -110.95833333336095, -110.54166666669445, -110.12500000002795],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e319d7ce-c79b-491f-85b1-338d44be41a1' class='xr-index-data-in' type='checkbox'/><label for='index-e319d7ce-c79b-491f-85b1-338d44be41a1' 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([25.041666666692656, 25.458333333359157, 25.875000000025654,\n",
+       "       26.291666666692155, 26.708333333358656, 27.125000000025157,\n",
+       "       27.541666666691654, 27.958333333358155, 28.375000000024656,\n",
+       "       28.791666666691157, 29.208333333357658, 29.625000000024155,\n",
+       "       30.041666666690656, 30.458333333357157, 30.875000000023654,\n",
+       "       31.291666666690155, 31.708333333356656,  32.12500000002316,\n",
+       "        32.54166666668966,  32.95833333335616,  33.37500000002265,\n",
+       "        33.79166666668915],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-81cf528a-2c23-4f33-97e6-f97dac521853' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-81cf528a-2c23-4f33-97e6-f97dac521853' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray (longitude: 22, latitude: 15)> Size: 3kB\n",
+       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 3.47660831e-03, 1.15564466e-01,\n",
+       "        3.52053237e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.03169656e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 1.83333326e-02, 4.51157391e-02,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 4.91046339e-05, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 4.79916669e-02,\n",
+       "        1.93287036e-03, 6.66666683e-03, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "...\n",
+       "       [0.00000000e+00, 1.21594822e+00, 0.00000000e+00, 7.29166670e-03,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.28425926e-01,\n",
+       "        1.20161705e+01, 7.78807878e-01, 0.00000000e+00],\n",
+       "       [1.01527780e-01, 1.60752311e-01, 4.85277660e-02, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 5.28905272e-01,\n",
+       "        2.90231496e-01, 1.12500013e-04, 1.11747229e+00, 2.33097744e+01,\n",
+       "        8.62268545e-03, 2.06924324e+01, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 1.04861089e-03, 1.62048608e-01,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 1.94502492e-02, 0.00000000e+00, 0.00000000e+00,\n",
+       "        1.29629625e-02, 2.51620375e-02, 0.00000000e+00],\n",
+       "       [0.00000000e+00, 1.62037031e-04, 0.00000000e+00, 1.97702385e-02,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        3.38425934e-02, 1.20212686e+00, 1.79245043e+00, 0.00000000e+00,\n",
+       "        2.29809731e-02, 6.91971600e-01, 4.77314815e-02],\n",
+       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "        0.00000000e+00, 0.00000000e+00, 1.65740743e-01, 9.83796315e-04,\n",
+       "        1.47685185e-02, 1.91782415e-02, 0.00000000e+00]])\n",
+       "Coordinates:\n",
+       "  * latitude   (latitude) float64 120B -116.0 -115.5 -115.1 ... -110.5 -110.1\n",
+       "  * longitude  (longitude) float64 176B 25.04 25.46 25.88 ... 32.96 33.38 33.79"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "da = pcrglob.get_value_as_xarray(\"discharge\")\n",
     "da.thin(5)  # only show every 5th value in each dim"
@@ -414,10 +1034,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "f30ab9b3",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7f281255fda0>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 768x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "fig = plt.figure(dpi=120)\n",
     "ax = fig.add_subplot(111, projection=crs.PlateCarree())\n",
@@ -442,10 +1083,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "id": "eb8a054b-44dc-4bdc-8179-c3796af26c2e",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='time'>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "#extra\n",
     "timeseries.plot()"
@@ -461,25 +1123,46 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "f62de858-940c-46d2-b5ac-5b5268609911",
    "metadata": {},
    "outputs": [],
    "source": [
     "prepared_forcing_path_caravan_central = \"/home/rhut/forcing/caravan/camelsgb_73010\"\n",
-    "camelsgb_forcing = ewatercycle.forcing.sources['CaravanForcing'].load(directory=prepared_forcing_path_caravan_central)\n",
-    "xr_camelsgb_forcing = xr.open_dataset(camelsgb_forcing['Q'])\n"
+    "caravan_forcing = ewatercycle.forcing.sources['CaravanForcing'].load(directory=\"/home/rhut/forcing/caravan/hysets_09488650\")\n",
+    "xr_caravan_forcing = xr.open_dataset(caravan_forcing['Q'])\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "05522b52-eb4a-458e-a44d-cda10229e0be",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f2816f12210>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "timeseries.plot()\n",
-    "xr_camelsgb_forcing[\"Q\"].plot(label=\"Observed discharge\")\n",
+    "xr_caravan_forcing[\"Q\"].plot(label=\"Observed discharge\")\n",
     "\n",
     "plt.legend()"
    ]
@@ -496,7 +1179,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "id": "b5846be2",
    "metadata": {},
    "outputs": [],