diff --git a/docs/model.ipynb b/docs/model.ipynb
index ce35beb..fb32344 100644
--- a/docs/model.ipynb
+++ b/docs/model.ipynb
@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "b973913f-9472-4c00-bc4b-a170e42710ed",
    "metadata": {},
    "outputs": [],
@@ -45,7 +45,9 @@
     "\n",
     "import ewatercycle.forcing\n",
     "import ewatercycle.models\n",
-    "import ewatercycle.parameter_sets"
+    "import ewatercycle.parameter_sets\n",
+    "\n",
+    "data_dir = \"/mnt/data/\" # on Surf Research Cloud (dcache)."
    ]
   },
   {
@@ -64,6 +66,26 @@
   {
    "cell_type": "code",
    "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ForcingSources['GenericDistributedForcing', 'GenericLumpedForcing', 'LisfloodForcing', 'MarrmotForcing', 'HypeForcing', 'WflowForcing', 'PCRGlobWBForcing']"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ewatercycle.forcing.sources"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
    "id": "54344de9",
    "metadata": {},
    "outputs": [
@@ -71,23 +93,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "eWaterCycle forcing\n",
-      "-------------------\n",
-      "start_time=1990-01-01T00:00:00Z\n",
-      "end_time=1990-12-31T00:00:00Z\n",
-      "directory=/mnt/data/forcing/lisflood_ERA5_1990_global-masked\n",
-      "shape=None\n",
-      "PrefixPrecipitation=lisflood_ERA5_pr_1990_1990.nc\n",
-      "PrefixTavg=lisflood_ERA5_tas_1990_1990.nc\n",
-      "PrefixE0=lisflood_ERA5_e0_1990_1990.nc\n",
-      "PrefixES0=lisflood_ERA5_es0_1990_1990.nc\n",
-      "PrefixET0=lisflood_ERA5_et0_1990_1990.nc\n"
+      "start_time='1990-01-01T00:00:00Z' end_time='1990-12-31T00:00:00Z' directory=PosixPath('/home/bart/Data/ewatercycle/forcing/lisflood_ERA5_1990_global-masked') shape=None PrefixPrecipitation='lisflood_ERA5_pr_1990_1990.nc' PrefixTavg='lisflood_ERA5_tas_1990_1990.nc' PrefixE0='lisflood_ERA5_e0_1990_1990.nc' PrefixES0='lisflood_ERA5_es0_1990_1990.nc' PrefixET0='lisflood_ERA5_et0_1990_1990.nc'\n"
      ]
     }
    ],
    "source": [
     "forcing = ewatercycle.forcing.sources[\"LisfloodForcing\"](\n",
-    "    directory=\"/mnt/data/forcing/lisflood_ERA5_1990_global-masked\",\n",
+    "    directory= data_dir + \"/forcing/lisflood_ERA5_1990_global-masked\",\n",
     "    start_time=\"1990-01-01T00:00:00Z\",\n",
     "    end_time=\"1990-12-31T00:00:00Z\",\n",
     "    PrefixPrecipitation=\"lisflood_ERA5_pr_1990_1990.nc\",\n",
@@ -116,12 +128,12 @@
     "tags": []
    },
    "source": [
-    "This example uses parameter set from SURF dCache storage."
+    "This example uses a parameter set from SURF dCache storage."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "b5047917-8fcc-4672-9652-aa705b938c89",
    "metadata": {
     "tags": []
@@ -134,19 +146,20 @@
       "Parameter set\n",
       "-------------\n",
       "name=Lisflood01degree_masked\n",
-      "directory=/mnt/data/parameter-sets/lisflood_global-masked_01degree\n",
-      "config=/mnt/data/parameter-sets/lisflood_global-masked_01degree/settings_lisflood_ERA5.xml\n",
+      "directory=/home/bart/Data/ewatercycle/parameter-sets/lisflood_global-masked_01degree\n",
+      "config=/home/bart/Data/ewatercycle/parameter-sets/lisflood_global-masked_01degree/settings_lisflood_ERA5.xml\n",
       "doi=N/A\n",
       "target_model=lisflood\n",
-      "supported_model_versions=set()\n"
+      "supported_model_versions=set()\n",
+      "downloader=None\n"
      ]
     }
    ],
    "source": [
     "parameterset = ewatercycle.parameter_sets.ParameterSet(\n",
     "    name=\"Lisflood01degree_masked\",\n",
-    "    directory=\"/mnt/data/parameter-sets/lisflood_global-masked_01degree\",\n",
-    "    config=\"settings_lisflood_ERA5.xml\",\n",
+    "    directory=data_dir + \"/parameter-sets/lisflood_global-masked_01degree\",\n",
+    "    config=data_dir + \"/parameter-sets/lisflood_global-masked_01degree/settings_lisflood_ERA5.xml\",\n",
     "    target_model=\"lisflood\",\n",
     ")\n",
     "print(parameterset)"
@@ -172,27 +185,6 @@
     "To create the model object, we need to select a version."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "2fe222cb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "('20.10',)"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ewatercycle.models.Lisflood.available_versions"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -203,37 +195,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Model version 20.10 is not explicitly listed in the supported model versions of this parameter set. This can lead to compatibility issues.\n",
-      "eWaterCycle Lisflood\n",
-      "-------------------\n",
-      "Version = 20.10\n",
-      "Parameter set = \n",
-      "  Parameter set\n",
-      "  -------------\n",
-      "  name=Lisflood01degree_masked\n",
-      "  directory=/mnt/data/parameter-sets/lisflood_global-masked_01degree\n",
-      "  config=/mnt/data/parameter-sets/lisflood_global-masked_01degree/settings_lisflood_ERA5.xml\n",
-      "  doi=N/A\n",
-      "  target_model=lisflood\n",
-      "  supported_model_versions=set()\n",
-      "Forcing = \n",
-      "  eWaterCycle forcing\n",
-      "  -------------------\n",
-      "  start_time=1990-01-01T00:00:00Z\n",
-      "  end_time=1990-12-31T00:00:00Z\n",
-      "  directory=/mnt/data/forcing/lisflood_ERA5_1990_global-masked\n",
-      "  shape=None\n",
-      "  PrefixPrecipitation=lisflood_ERA5_pr_1990_1990.nc\n",
-      "  PrefixTavg=lisflood_ERA5_tas_1990_1990.nc\n",
-      "  PrefixE0=lisflood_ERA5_e0_1990_1990.nc\n",
-      "  PrefixES0=lisflood_ERA5_es0_1990_1990.nc\n",
-      "  PrefixET0=lisflood_ERA5_et0_1990_1990.nc\n"
+      "parameter_set=ParameterSet(name='Lisflood01degree_masked', directory=PosixPath('/home/bart/Data/ewatercycle/parameter-sets/lisflood_global-masked_01degree'), config=PosixPath('/home/bart/Data/ewatercycle/parameter-sets/lisflood_global-masked_01degree/settings_lisflood_ERA5.xml'), doi='N/A', target_model='lisflood', supported_model_versions=set(), downloader=None) forcing=LisfloodForcing(start_time='1990-01-01T00:00:00Z', end_time='1990-12-31T00:00:00Z', directory=PosixPath('/home/bart/Data/ewatercycle/forcing/lisflood_ERA5_1990_global-masked'), shape=None, PrefixPrecipitation='lisflood_ERA5_pr_1990_1990.nc', PrefixTavg='lisflood_ERA5_tas_1990_1990.nc', PrefixE0='lisflood_ERA5_e0_1990_1990.nc', PrefixES0='lisflood_ERA5_es0_1990_1990.nc', PrefixET0='lisflood_ERA5_et0_1990_1990.nc')\n"
      ]
     }
    ],
    "source": [
     "model = ewatercycle.models.Lisflood(\n",
-    "    version=\"20.10\", parameter_set=parameterset, forcing=forcing\n",
+    "    parameter_set=parameterset, forcing=forcing\n",
     ")\n",
     "print(model)"
    ]
@@ -247,10 +215,7 @@
     {
      "data": {
       "text/plain": [
-       "[('IrrigationEfficiency', '0.75'),\n",
-       " ('MaskMap', '/data/input/areamaps/model_mask'),\n",
-       " ('start_time', '1990-01-01T00:00:00Z'),\n",
-       " ('end_time', '1990-12-31T00:00:00Z')]"
+       "dict_items([('IrrigationEfficiency', '0.75'), ('MaskMap', '/data/input/areamaps/model_mask'), ('start_time', '1990-01-01T00:00:00Z'), ('end_time', '1990-12-31T00:00:00Z')])"
       ]
      },
      "execution_count": 7,
@@ -280,17 +245,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running /mnt/data/apptainer-images/ewatercycle-lisflood-grpc4bmi_20.10.sif apptainer container on port 41619\n",
-      "/home/vagrant/ewatercycle/docs/examples/ewatercycle_output/lisflood_20210930_093520/lisflood_setting.xml\n",
-      "/home/vagrant/ewatercycle/docs/examples/ewatercycle_output/lisflood_20210930_093520\n"
+      "/home/bart/ewatercycle/output/lisflood_20231212_080744/lisflood_setting.xml\n",
+      "/home/bart/ewatercycle/output/lisflood_20231212_080744\n"
      ]
     }
    ],
    "source": [
-    "model_mask = \"/mnt/data/climate-data/aux/LISFLOOD/model_mask.nc\"\n",
+    "model_mask = data_dir + \"/climate-data/aux/LISFLOOD/model_mask.nc\"\n",
     "\n",
     "config_file, config_dir = model.setup(\n",
-    "    IrrigationEfficiency=\"0.8\", end_time=\"1990-1-31T00:00:00Z\", MaskMap=model_mask\n",
+    "    IrrigationEfficiency=\"0.8\", end_time=\"1990-1-31T00:00:00Z\", MaskMap=model_mask,\n",
     ")\n",
     "print(config_file)\n",
     "print(config_dir)"
@@ -305,10 +269,7 @@
     {
      "data": {
       "text/plain": [
-       "[('IrrigationEfficiency', '0.8'),\n",
-       " ('MaskMap', '/mnt/data/climate-data/aux/LISFLOOD/model_mask'),\n",
-       " ('start_time', '1990-01-01T00:00:00Z'),\n",
-       " ('end_time', '1990-01-31T00:00:00Z')]"
+       "dict_items([('IrrigationEfficiency', '0.8'), ('MaskMap', '/home/bart/Data/ewatercycle/climate-data/aux/LISFLOOD/model_mask'), ('start_time', '1990-01-01T00:00:00Z'), ('end_time', '1990-12-31T00:00:00Z')])"
       ]
      },
      "execution_count": 9,
@@ -490,7 +451,7 @@
     {
      "data": {
       "text/plain": [
-       "<AxesSubplot:>"
+       "<Axes: >"
       ]
      },
      "execution_count": 15,
@@ -499,14 +460,12 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 864x576 with 1 Axes>"
+       "<Figure size 1200x800 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -534,7 +493,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7fa2c01215b0>"
+       "<matplotlib.collections.PathCollection at 0x7f5b87a59420>"
       ]
      },
      "execution_count": 16,
@@ -543,14 +502,12 @@
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 864x576 with 2 Axes>"
+       "<Figure size 1200x800 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -590,7 +547,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.10.0"
   }
  },
  "nbformat": 4,