diff --git a/CHANGELOG.md b/CHANGELOG.md
index 767cecd8..e4bb22b1 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -6,6 +6,11 @@ Formatted as described on [https://keepachangelog.com](https://keepachangelog.co
 
 ## [Unreleased]
 
+### Added
+
+- 2020.1.2 version of wflow model ([#268](https://github.com/eWaterCycle/ewatercycle/pull/268))
+- Document how to add a new version of a model ([#266](https://github.com/eWaterCycle/ewatercycle/pull/266))
+
 ## [1.1.2] (2021-09-29)
 
 ### Added
diff --git a/docs/examples/wflow.ipynb b/docs/examples/wflow.ipynb
index 83313d8e..ef580d5d 100644
--- a/docs/examples/wflow.ipynb
+++ b/docs/examples/wflow.ipynb
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "source": [
     "import ewatercycle.forcing\n",
     "import ewatercycle.models\n",
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "source": [
     "parameter_set = ewatercycle.parameter_sets.get_parameter_set(\"wflow_rhine_sbm_nc\")\n",
     "print(parameter_set)"
@@ -63,7 +63,7 @@
       "config=/home/verhoes/git/eWaterCycle/ewatercycle/docs/examples/parameter-sets/wflow_rhine_sbm_nc/wflow_sbm_NC.ini\n",
       "doi=N/A\n",
       "target_model=wflow\n",
-      "supported_model_versions={'2020.1.1'}\n"
+      "supported_model_versions={'2020.1.2', '2020.1.1'}\n"
      ]
     }
    ],
@@ -71,7 +71,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "source": [
     "forcing = ewatercycle.forcing.load_foreign(\n",
     "    directory=str(parameter_set.directory),\n",
@@ -119,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "source": [
     "ewatercycle.models.Wflow.available_versions"
    ],
@@ -128,21 +128,21 @@
      "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "('2020.1.1',)"
+       "('2020.1.1', '2020.1.2')"
       ]
      },
      "metadata": {},
-     "execution_count": 4
+     "execution_count": 5
     }
    ],
    "metadata": {}
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "source": [
     "model = ewatercycle.models.Wflow(\n",
-    "    version=\"2020.1.1\", parameter_set=parameter_set, forcing=forcing\n",
+    "    version=\"2020.1.2\", parameter_set=parameter_set, forcing=forcing\n",
     ")"
    ],
    "outputs": [
@@ -159,7 +159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 7,
    "source": [
     "print(model)"
    ],
@@ -170,7 +170,7 @@
      "text": [
       "eWaterCycle Wflow\n",
       "-------------------\n",
-      "Version = 2020.1.1\n",
+      "Version = 2020.1.2\n",
       "Parameter set = \n",
       "  Parameter set\n",
       "  -------------\n",
@@ -179,7 +179,7 @@
       "  config=/home/verhoes/git/eWaterCycle/ewatercycle/docs/examples/parameter-sets/wflow_rhine_sbm_nc/wflow_sbm_NC.ini\n",
       "  doi=N/A\n",
       "  target_model=wflow\n",
-      "  supported_model_versions={'2020.1.1'}\n",
+      "  supported_model_versions={'2020.1.2', '2020.1.1'}\n",
       "Forcing = \n",
       "  Forcing data for Wflow\n",
       "  ----------------------\n",
@@ -207,7 +207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "source": [
     "model.parameters"
    ],
@@ -220,14 +220,14 @@
       ]
      },
      "metadata": {},
-     "execution_count": 6
+     "execution_count": 8
     }
    ],
    "metadata": {}
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
    "source": [
     "cfg_file, cfg_dir = model.setup(end_time=\"1991-02-28T00:00:00Z\")"
    ],
@@ -238,7 +238,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "source": [
     "print(cfg_file)\n",
     "print(cfg_dir)"
@@ -248,8 +248,8 @@
      "output_type": "stream",
      "name": "stdout",
      "text": [
-      "/home/verhoes/git/eWaterCycle/ewatercycle/docs/examples/output/wflow_20210714_073455/wflow_ewatercycle.ini\n",
-      "/home/verhoes/git/eWaterCycle/ewatercycle/docs/examples/output/wflow_20210714_073455\n"
+      "/home/verhoes/git/eWaterCycle/ewatercycle/docs/examples/output/wflow_20211008_084304/wflow_ewatercycle.ini\n",
+      "/home/verhoes/git/eWaterCycle/ewatercycle/docs/examples/output/wflow_20211008_084304\n"
      ]
     }
    ],
@@ -264,7 +264,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "source": [
     "model.initialize(cfg_file)"
    ],
@@ -280,7 +280,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "source": [
     "while model.time < model.end_time:\n",
     "    model.update()\n",
@@ -366,7 +366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "source": [
     "da = model.get_value_as_xarray(\"RiverRunoff\")\n",
     "da"
@@ -740,13 +740,13 @@
        "  * latitude   (latitude) float64 45.89 45.93 45.97 46.0 ... 51.98 52.02 52.05\n",
        "    time       object 1991-02-28 00:00:00\n",
        "Attributes:\n",
-       "    units:     m/s</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'RiverRunoff'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 169</li><li><span class='xr-has-index'>longitude</span>: 187</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2507ea47-d47d-4446-9845-28de691b1bd2' class='xr-array-in' type='checkbox' checked><label for='section-2507ea47-d47d-4446-9845-28de691b1bd2' 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 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "    units:     m/s</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'RiverRunoff'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 169</li><li><span class='xr-has-index'>longitude</span>: 187</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7f13eeb7-ea6c-4c66-bfee-336882119dda' class='xr-array-in' type='checkbox' checked><label for='section-7f13eeb7-ea6c-4c66-bfee-336882119dda' 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 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
        "       [0., 0., 0., ..., 0., 0., 0.],\n",
        "       [0., 0., 0., ..., 0., 0., 0.],\n",
        "       ...,\n",
        "       [0., 0., 0., ..., 0., 0., 0.],\n",
        "       [0., 0., 0., ..., 0., 0., 0.],\n",
-       "       [0., 0., 0., ..., 0., 0., 0.]])</pre></div></div></li><li class='xr-section-item'><input id='section-7eec07ca-fea8-4e20-9925-5387b3bf50b4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7eec07ca-fea8-4e20-9925-5387b3bf50b4' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.227 5.264 5.3 ... 12.01 12.05</div><input id='attrs-1eede325-39df-4357-8f36-cb96de8b29d9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1eede325-39df-4357-8f36-cb96de8b29d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-462d9747-5b50-41d6-9f16-b88be7dd2f16' class='xr-var-data-in' type='checkbox'><label for='data-462d9747-5b50-41d6-9f16-b88be7dd2f16' 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([ 5.227163,  5.26383 ,  5.300497,  5.337163,  5.37383 ,  5.410497,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]])</pre></div></div></li><li class='xr-section-item'><input id='section-a86ae63d-e499-4ea7-b0b9-33639f840bff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a86ae63d-e499-4ea7-b0b9-33639f840bff' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.227 5.264 5.3 ... 12.01 12.05</div><input id='attrs-e916e07d-942f-42e1-aa56-2ed097de8c88' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e916e07d-942f-42e1-aa56-2ed097de8c88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-946e2fdc-d8c8-412e-8885-0e23262fa387' class='xr-var-data-in' type='checkbox'><label for='data-946e2fdc-d8c8-412e-8885-0e23262fa387' 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([ 5.227163,  5.26383 ,  5.300497,  5.337163,  5.37383 ,  5.410497,\n",
        "        5.447163,  5.48383 ,  5.520497,  5.557163,  5.59383 ,  5.630497,\n",
        "        5.667163,  5.70383 ,  5.740497,  5.777164,  5.81383 ,  5.850497,\n",
        "        5.887163,  5.92383 ,  5.960497,  5.997163,  6.03383 ,  6.070497,\n",
@@ -777,7 +777,7 @@
        "       11.387163, 11.42383 , 11.460497, 11.497164, 11.53383 , 11.570497,\n",
        "       11.607163, 11.64383 , 11.680496, 11.717163, 11.75383 , 11.790497,\n",
        "       11.827164, 11.86383 , 11.900496, 11.937163, 11.97383 , 12.010497,\n",
-       "       12.047163])</pre></div></li><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'>45.89 45.93 45.97 ... 52.02 52.05</div><input id='attrs-8ddcdff9-b795-42bc-b6c8-bbfff7473b89' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ddcdff9-b795-42bc-b6c8-bbfff7473b89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02cd53b2-3295-4f5d-b7f5-5b8714cd7af3' class='xr-var-data-in' type='checkbox'><label for='data-02cd53b2-3295-4f5d-b7f5-5b8714cd7af3' 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([45.894268, 45.930935, 45.967602, 46.004265, 46.040932, 46.077599,\n",
+       "       12.047163])</pre></div></li><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'>45.89 45.93 45.97 ... 52.02 52.05</div><input id='attrs-a82698a7-def2-44b2-ada7-336b5ba68229' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a82698a7-def2-44b2-ada7-336b5ba68229' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2ee3590-5952-42c3-8066-9b166b49349f' class='xr-var-data-in' type='checkbox'><label for='data-d2ee3590-5952-42c3-8066-9b166b49349f' 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([45.894268, 45.930935, 45.967602, 46.004265, 46.040932, 46.077599,\n",
        "       46.114265, 46.150932, 46.187599, 46.224266, 46.260933, 46.2976  ,\n",
        "       46.334267, 46.370934, 46.4076  , 46.444267, 46.480934, 46.517601,\n",
        "       46.554268, 46.590935, 46.627602, 46.664268, 46.700932, 46.737598,\n",
@@ -805,7 +805,7 @@
        "       51.394268, 51.430935, 51.467602, 51.504265, 51.540932, 51.577599,\n",
        "       51.614265, 51.650932, 51.687599, 51.724266, 51.760933, 51.7976  ,\n",
        "       51.834267, 51.870934, 51.9076  , 51.944267, 51.980934, 52.017601,\n",
-       "       52.054268])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1991-02-28 00:00:00</div><input id='attrs-5ca57799-123a-4240-9a80-a0e76556d1f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5ca57799-123a-4240-9a80-a0e76556d1f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3359d5b1-b245-4141-81b4-3f29500cd399' class='xr-var-data-in' type='checkbox'><label for='data-3359d5b1-b245-4141-81b4-3f29500cd399' 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(cftime.DatetimeGregorian(1991, 2, 28, 0, 0, 0, 0), dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb4ccb62-0766-4818-bdb8-10e690da5027' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eb4ccb62-0766-4818-bdb8-10e690da5027' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd> m/s</dd></dl></div></li></ul></div></div>"
+       "       52.054268])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1991-02-28 00:00:00</div><input id='attrs-8a92aa88-df90-4d70-8433-48531aa15882' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a92aa88-df90-4d70-8433-48531aa15882' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b727b7a-9cb8-4a87-a9c7-333d6b71a123' class='xr-var-data-in' type='checkbox'><label for='data-6b727b7a-9cb8-4a87-a9c7-333d6b71a123' 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(cftime.DatetimeGregorian(1991, 2, 28, 0, 0, 0, 0), dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd5c9cd3-a18c-4995-8006-35570d70b349' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fd5c9cd3-a18c-4995-8006-35570d70b349' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd> m/s</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'RiverRunoff' (latitude: 169, longitude: 187)>\n",
@@ -825,14 +825,14 @@
       ]
      },
      "metadata": {},
-     "execution_count": 14
+     "execution_count": 13
     }
    ],
    "metadata": {}
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 14,
    "source": [
     "print(da)"
    ],
@@ -877,7 +877,7 @@
      "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7fae85f616d0>"
+       "<matplotlib.collections.PathCollection at 0x7fc7fd4816d0>"
       ]
      },
      "metadata": {},
@@ -886,7 +886,7 @@
     {
      "output_type": "display_data",
      "data": {
-      "image/png": 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",
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0Sbd3A6VLUNGxpGW4bQ54FwDLzts70flDVeq9bvOFPxS2t9thAgDhb0y9fon748K3V7dzIiI1HpBtZlcA+wGTzOw54Mvu/uNS57r7MjO7ClgOdAKnuntXev3tTcGRiIiI1Jy7HzfA8VlFz78BfKOafYooOJKyKl14NhrwHD9/sIvXljq/3KDl6Nj6xWf09KdMDf2NzRsAmPvtewv7WlujrE3w9f7P71lBjyu36oL39XvsttX39ntMRCRdaY85Sq+pLCg4EhERaXZaeLYXDcgWERERiVHmSMoqNZg6jfJYNZUrpcWNGTYagIfO3qvPsXd9P5h/zGPTaFiN88T7T+3bLxGR6tDCs3EKjkRERJqdkfuAJk0KjqSswQ6mzrs7T90d6MkgAYwe0w7ALSfumkmfRESkNhQciYiINL2qzJCdWxqQLSIiIhKjzJGUlcaA7DyLymsAm7s3A3Dw5X8t7Nt6SlBqa2sJBm5f/P7tCsdKLXYrIlKXDGjRgOyIgiMREZGml3JZLee/FKqsJiIiIhKjzJFIQsNahgFw4/E79XvOvz6wrLC916TXgZ5fxj4w7Z2FY0nnYhIRqRktH1KgzJGIiIhIjDJHksjS3xxV2I4PzgZYf0tsode8/7owRP+yx279Hntuw/OF7emjp9WiOyIiyVjKM2Tn/GeBgiMREZFml/bCs2m2lQGV1URERERilDmSgvgiq8+8vhLoGTi87ZiZhWPF8xzFy2wv3HQKAMNbh1etn3mlUpqI1DXdyl+g4EhERKTppTzmKOd35Co4Ep4NBwq7dxf2zRq7beLr45mkZl2oVkREGoeCIxERkWZn5D7bkyYNyBYRERGJUeZIaA3rzNukMGB4/eJgzqNmXahWRCSfLN3b73Oehapq5sjMnjazh81sqZndF+47xsyWmVm3mc2v5uuLiIhIAkYwIDu1R76Do1pkjvZ393Wx548AHwZ+VIPXlgTcBz4nqejW/1KDtKOsktYVExGRelbzspq7Pwr6ASkiIlI/LPfZnjRVe0C2Azeb2RIzW1jl1xIREREZsmpnjvZ191VmNgVYbGYr3P2OJBeGwdRCgBkzZ1Szj0KKdbUSohKb5kASEalPwZ386WWO8l4dqmrmyN1XhV/XANcAe1dw7SJ3n+/u8ydP3rJaXRQREZGwqpbWI+erh1QvODKz0WY2NtoGDiIYjC0iIiJSt6pZVtsKuCZMrbUBl7v7jWZ2FPCfwGTgd2a21N0/UMV+yACmjd4GgNVvvljYN3XUVll1R0REas6wFOc5yntZrWrBkbs/CexeYv81BCU2ERERqQOW9hyQ6TWVCc2QLQXxbNGLG9cCMG7YGABGto3MpE8iIiK1puBIRERE0i2F5Tx1pIVnRURERGKUOZKStho5GQAP50Da3L25cGxYy7BBtVk83xHA+lvCJUXy/muGiEiOBfMcpdtenik4EhERaXaWdlkt3+GRgiMpK8rotFhPBdbDlWor/YekGbIbz389ej8AXzz9j4V9N17+PgDmTNypsG9026jadkxEZAgUHImIiDQ9S3n5kNSayoSCIxERkSanMUe9KTiSRFqtdchtrF8cDL6OD8guV2Lb53tLAbjl0zsW9o0eFpRn0hjAffLvnwrabO8s7Gtv7QbgwnftnKiNx199AoAtR0wK+9VjwvDxQ+5jversDj6zqJxW6u9x+cvLC9uzJ8yuTcdERFKg4EhERKTZaUB2LwqOpGaif3jxLEM8i1QsOu+o3zzVp41SawBF/xZbWnoGjxef1tLihe3LP7BdnzaiqQu+cv8yAKaN3lg41mrBsemjugv7Dpy+d/DauU8iV2byQd8Hymf+lC0SkbxScCQiItLkzMBSnBY654kjBUciIiKSclkt5xQcSaaiskxUzgKYuOCiXudcc2Tf8le1ROWxr7xjt5q9Zl4kHUgvIpJ3Co5EREQk3Vv5c56E0sKzIiIiIjHKHEldiN/tVbxArUo4IiLVZWa0pDlDdoI7eM3sEuBQYI27zwn3XQAcBnQAfwM+6e6vhMfOA04GuoAz3P2m1DpcRJkjERERwcxSeySc3eSnwMFF+xYDc9x9LvBX4Lywb7OBY4Hdwmt+YJbC7MT9UHAkdc9jf0REpDG4+x3A+qJ9N7t7tGzBXcD0cPsI4Ep33+TuTwFPAHtXq28KjkRERJpctLZamo8UnATcEG5PA56NHXsu3FcVGnMkIiLS7FJePiQcc7S/mX0utnuRuy9KdL3Zl4BO4LKeHvZRtXKCgiOpW8UDs+P7pHaizz9aOFhEJKHb3P3kSi8ysxMJBmof4O5RAPQcMCN22nRg1dC7WJrKaiIiIpJuSW2QSSgzOxg4Bzjc3d+MHboWONbMhpvZdsCOwD1DfMv9UuZI6t5j132ssK3b+9NTbtHfUrS0gIikycyuAPYDJpnZc8CXCe5OGw4sDv/PucvdT3H3ZWZ2FbCcoNx2qrt3VatvCo5ERESanJlhLSmOOUrwy5S7H1di94/LnP8N4BtD6FZiCo5EREQk90t+pEnBkdS9KSMnFbY1SLuvSstjkWb/3ERE+qPgSERERNK9lT/nWSgFR5JLa27+bGG7WQdpN+v7FpH0pThxY0PQrfwiIiIiMcociYiISMpltXynoRQcSS4NaxlW2C4epN3IZaaeyWJFRKRaFByJiIg0PUs325PvxJGCIxERkWZnBinOAZn7Ac0KjqRhPHvDp4Dy8/7kveSW9zq+iEgeKDgSERGRVJcPyfu8AAqOpGGMGTYaKJ0dcoKBzKWySusWn1bYbrEgGWw1KpgPdnZryH8WTESkXik4EhERaXJpTwKZ88SRgiMRERHRmMY4BUfSFKIyWalSVLy0tf6WM6rWh1IlNJXGZLBe3vRKYXt463AARrWNzKg3Io1FwZGIiEiTU1mtNwVH0lQGGgBdPBB7oPOLMz+NPI2A1IcX3lwDwNajpvQ51tG9ubDdGt5c0GqttemY5FzKk0DmfBbIvM/TJCIiIpIqZY5EREQk5YVnU2sqEwqOpCkkXZS2uCyW9vmNptu7gZ75oWRoooWFn3rjaaB3SSxabHnqqK37vb49tiCziAyegiMREZEml/aA7JwPOVJwJCJSdZ2d0DaI/24He53IIKS5fEje50zSvzppaEnLaZHovKTLejRbGS0SldNUVhtYy9W/oe1bF9JxwzUwZXLZc1e8ugKAXcfvCmvW0n7IUXSedxbdRx9Zg56KSET/o4mIVEtnJ23fupCWBx+hfcFhsGZtsuvWrKV9wWG0PPgIbd+6MMggiVST9ZTWUnlk/X6GSJkjaTjxrM/am08d1LXNmhFKKppPZ0Q4M7P0o62NjhuuCQKd5StoX3AYHbdc128GqdudtrXraT/6k7QsX0H37F2CjJNKayI1pcyRiEg1TZlMxy3X0T17l0KA1F8GqW3tenY66vSewKhMICWSJsNosfQeeR9zpOBIRKTakgRIa9ay01GnM/KxpxQYSSYsDGrSeOSdcrWSK9E8MBMPvKjfc9Yv7lk8ttJ/pOUGZDdTqa2zu2eMy7pN64Heg66njJhU8z7lXhgglSyxRWOMHnuKDTvNolWBUVlrNq4DYMsRE4Dey/7o5gBJg76LRERqpUQGyR5ZXgiYNuw0i4d/9R8KjKTmUh2MnfacSRlQ5kjqVqnB0VHGaCjZoSRKZYmaabD26o0vFrZnjJ6WYU8ay+Ln7wag/Wdf5e+OO5vRy1cwfN67Adiw07a03r6YeQ0UGDlBprd4Qediz29Y3ev5QP+kt2jfAoC3ujYBMLpt1CB7KD0s1XmO8h4dKXMkIlJjHZPGs+yHX+61b/kPv6yMkUidUHAk0ggGOw+O5s/JRPu6V9jtlK/22jf7lK8mnwdJJG2W7oDsnCeOVFaT+lNcvooPjl5/S1BOGyhNX01RqSDrfkQqmYG5l9gMzFv88JnqdTCmUUqSi1YsAWDSiE2FfdF3Qqv1fH+0hD8h2lqC30MPnr5P8LmfcBgtf32G7tm7sPnySxh2/EmMXr6C7gHmQWokz254vrA9fdQ2wOBL5Bu73ipst4WL9Ub/NuNtxhfyFSlHmSORPEtpBubW7q7q9lMC0ecem8fI58xOPA+SSLUYGowdp8yR1L16yTaUymRl3rcKZ2AG8BfXMPzAw2lZvoLloyZz8OhDWPf7z9eku9FnF2UAoT6yb+X83Y8eLmy3tgW/T/7h5D0rb6hEYFT4eyp3m3+eRUm02F/xs288B8CMMdNTe5mRrSNSa6uZpXlzS97nOlLmSCTvKpiBmTVrewdG8z7B2vYxte1vMyoXGEUq+XsUkapScCTSCBLOwBz/Aa3AqEaSBEYRBUiSFQtu5U/tke/EUXXLamb2NPA60AV0uvt8M5sI/AKYBTwNfMTdX65mP0TSFC+lFc+knUaZrdu7AdjywP8se966xacBsUGmSWZgjjJG4w/jr3d8ach9rVQeZyB/a+PmwvZ9n3sHAI+sfwSAORPnlL+4s5P2Q46qbK204r/HQ46i4+7bC4vPdnkwPuyOF+4vXNIa1q3eM7Wn3JekXHnXmgcK2++cMi/xdUlFpZVoZnvofUOD1I9GGSuUllpkjvZ393nuPj98fi5wq7vvCNwaPheRNAwwA7MyRjXW1kbneWfRvfucysYQRX+Pu8+h87yzCoGRiNRGFmW1I4BLw+1LgSMz6INI4yoKkIbPe3chMNq0+FoFRjXWffSRQean0sHVUybTcfftdB99ZDW6JdJHuvMc5TsNVe1fRxy42cwc+JG7LwK2cvfVAO6+2symlLrQzBYCCwFmzJxR5W6KDE5xKSjpnWylykoDtT1QG73KfcdfzuxR72cJKwr79hr1fpZ/7Iq6KF+VK01mbeev3QnA2LHDgZ5SGvSUhLorbXSwmZ8S1/3vs8ESJIfNfHefY396YUlhu9t7l6/iP6yirb/buqcMd+/apQAMbw1eszV2/uwJs8PrBvcDb+WGZwvb246ZOag2RGqp2pmjfd39HcAhwKlm9t6kF7r7Inef7+7zJ0/esno9FGlAkzve4GfLf9lr38+W/5LJHW9k1CMRqWdGMGlpWo98542qnDly91Xh1zVmdg2wN/CimU0Ns0ZTgTXV7IPUj9c2vw7AqNgikdFstvHswYs3faa2HUtR0oxIGtmb/rJWkzve4OlXrqPlzbW9ZmCevXwFT79yHR1rFtbV/DnlBmmvuunTQG3nsYkyLPGMUeFY+F/+3HAgdjQwGxIMzh6i61f+BSidMYrEM0GV2mvyvH6PPfrKo0DxwOrAbmFWqZRn3lgJKFuUC2kPyM55dFS1zJGZjTazsdE2cBDwCHAtcGJ42onAb6vVB5FmM7njDW5c+lPNwCwiMgTVLKttBfzJzB4E7gF+5+43AucDB5rZ48CB4XMRGaIoMJodZoxKzcCsAElESjHSnuco36mjqpXV3P1JYPcS+18CDqjW6+ZBZzhPSav1xKb5r9AObNtDLun3WD0MEk7b1y4KhtidNnuP6r/YmrW9Smmzxh/G2uMv7/251vkSFaXKa/W+LES8lJZ47qNBiv9/UWu7jt+132PLXl4OgHvPMPVoKxrAvm3VeiZSHZohWyTvSszA3O/t+sogiUgpplv54zSzWAaiQcibu3tm3m0JfysszHYcc8fq+wA44oQ/9zlWrxmX+Cy4ExdcBPQsNhrPkjXybLktVoP3VoUZmLNWalB7Lb/PuzorvlEfgE6v7t93a53+sCk3IDvySsdrhe3x7eOq2R0Zglp/i5nZJcChwBp3nxPu63cVDTM7DziZYNWNM9z9pmr1TZkjkTzTDMwikl8/BQ4u2ldyFQ0zmw0cC+wWXvMDsxLZhJTof0SRnOs++kg6jjy08gAnnIFZgZGIGKRaCkvSlLvfYWazinYfAewXbl8K3A6cE+6/0t03AU+Z2RME0wPdmUqHi+h/xQwNaxlW2N7hX4KSWTwzv7kzGLj9xtOrgNKlhXpYwDNaCBN6yoJRKW2g/jTaQPT/erRnMdDP7tp3npyqSXEG5mZnLYP7npy35dsBWPrSw332paGlTstqScRLadF8Z+OGjc2qO1KK2aC/9/trb5D6W0VjGnBX7Lznwn1VobKaiIiIVMP+ZnZf7LFwCG2ViraqNtBPvzbWiW9+Isi4fHT7fSq6bv3icJBzLEovNzNzqUHR5by4MbiTaZfDLu9zLMoITTrwe32OPXvDpxK1X2svvNkzIftrm18FYKctdkx0bXd4q/JP/np/n2Md3cHvGafsWoPb9qWuxbNF9619EIA9J88FhpYpXTBtbwBuW30vAPtP3WvQbWUpyhhFGaT4PslWmsnJsK3b3P3kCi/tbxWN54D4QqvTgVVD7mg/lDkSERGRetHfKhrXAsea2XAz2w7YkWCC6apQ5khERKTJmaU7IDvZa9oVBIOvJ5nZc8CXCVbNuMrMTgZWAscAuPsyM7sKWA50Aqe6xwa8pkzBUZ2otJwWKfXNXG4AdNJ5Y4pLc+UGg0elvf76U0+2HjWlsL0VwW3vS9Y9WNjXHY6I7wq//u31jsKxru7gvZ28895V7+dQlVvMtV7nxiqn1KD/UsqVlJMau3cwkD5aZHUo39PzJweLBETfY/EbLqJjSd0ezne239T5g+5PPYmX0jZ1bQJgeOvwrLojpH232sBtuftx/RwquYqGu38D+MYQupWYymoiIiIiMcociYiINDkDUr2TP72mMqHgSAriJYkkpZc8lmfiojuH9pzUf3ljzoQNhe0xw0ZXvU9pK7UUR56UKg8Wf9/Fj71482cBaI/NIVbO068/A8CssdVdGrXU99i9a5cCsNfkeRW1lfe5wUotGRSV06I7QlsyXGS3aaU8z1Gdj7AYkL4DRURERGKUOWoSxVmDUgvD5j0TlKa3wgGio4eNyrgnAuUzYEP5vt127EwAntvwfGFflJnZZvTUXs/TFmWM7lzzQGHfu6b0nifrjy8sKWzX+0DspItIl/s86/2GjkaX6uef879LZY5EREREYpQ5EhERaXLBPEcptpdeU5lQcNTAkg5ilR4dXcG8RiMaZL6V+N/zS4tPz7An6Umz/BuVeKaP7rt+5fMbVgMwLSyvVcs+U+YVtqMyWvSDpZ5/wBSX0YZSfozayvtg87xLt6yWXlNZUFlNREREJEaZoyaV91u809TRvbmw3d7anmFPqku3R1cmyhi9sLFnseKtR07p7/RBi2dL3rP1nqm3n4ZSg62HmuWJt6mMUR1I/Vb+fP+d6n9LERERkRhljkRERJqckfLd9/lOHCk4ahQbOzcWtrc5eBGQbAFa6L1wbDNKOpuyNKdJI7YsbL/W8ToA49rH9nd6w1DZq8lYygvP5vx7RsGRiIiINAwzeyjBaWvd/YD+Dio4ahBRtggqXxctyiJphmyRvtqstbA9sm1Ehj2prbz/5i+VCcpqDXMrfyvwwTLHDbi2XAMKjkRERIQUb1bL+m6vT7v7M+VOMLPPljuuu9VERESkYbj7n4r3mdkEM5tb7pw4ZY6kUE4rN6O2iMAwDd6XBhUsH5Js8eBkDabX1KC7YHY7cDhBrLMUWGtmf3D3zw90rTJHIiIi0oi2cPfXgA8DP3H3PYEFSS5UcCQiIiKFxWdTeWT9ZgJtZjYV+AhwfUUXVqc/kie6W61xlbsrsdyyMfpeEGkuBrSkWFZLtUQ3eP8K3AT8yd3vNbPtgceTXKjgSERERBqGmR0H3OzuvwR+Ge139yeBv0/ShoKjnIt++x/KLNcakN1ckmQK0/heSLqgsb7XROpDnZTC0rAt8EszGwbcCtwA3OPuidNZGnMkIiIiDcPdz3f39xNMBPkgcBJwv5ldbmb/YGZbDdSGMkciIiJNzswbbsyRu78OXBM+MLPZwCHA/wAfKHetgqMcKVWmiMppaUz7vv6WntJcJYO0n3z9qcL29mO3G3I/pDqSDMQuPneg80t9fxRKvbHvp+KlKOLZ7eLScKpLGEjdin9PRIvcasmSbDXO6iE9wokfZ9ET7zzl7mUDI1BwJCIiIg3IzC4B5gLLgO5wtwO/HuhaBUd1rPg39jU39ywFU42ZeuO/tS3677179aFUhuCxV/8KwNvG7ZB6X6R+JB24neT8SDw7VJzR0gDt5hP936MMUrZSzRzVx1/hPu4+ezAXKjgSERFpcmYpz3OUWktDcqeZzXb35ZVeqOBIREREGtGlBAHSC8AmgpjN3X1u+csUHOVCNcoMm7s3F7Z/9+w9AHR298zscMx27wLg6Fv2AXqXT3532XsAePdW70i9X5IvaX5var4tkWzVSbYnTZcAJwAP0zPmKBEFRyIiItKIVrr7tYO5UMFRk7l1VZAl6o7dSn3ktvv2e340MLL0Gl3KHOVJGrOp10K8f9UepN3pXQDcsfr+wr72liCDGg0ab4mNLH3XlD2q0g8JFA/Mju+T6mrQtdVWmNnlwHUEZTUA3F13q4mIiMjAGnCeo5EEQdFBsX26lV9ERESak7t/crDXKjjKQNIFOdP013BOovdsHZQF2ocwT9KzN3wKKD0T8sQFFwHVH0gbn2H5f564F4B/eNtegGZYjouXJyL1/vkk7V9HeFNBm7UW9rVY/8tF/vyJuwEYM6yzsG9Ua/Bf4EHT35noNZesexCA0W3DAdh5/M6FYyr/SJ6ZebqlsJz/c1BwJCIi0uSMdFeiz/uq9nnvv4iIiEiqlDmqsq7wbhiASQd+D0i+wGaa5beRbaOBoZXTImOGBW2VmpfmxXCJk3J9X3vzqYXttpbKvgWjctplf7unsO/EHYOSyBubN/Tqn/SUOSGfcwaV+h57+0cPAGCH7ccAMHP8m32ua23pKQ+0tQTTm5y529sBGN02atD92XPS7r2eP/PGysL2tmNmDrpdCWj5kGyle4dZdnermdmh7n79UM5RcCQiIiKN5AIze57yI5++CQwtODKznYD/ArZy9zlmNhc43N2/XklvG91bXYVpFJh65KXBxsaNhX1Z/uY+uq162ZRS7yvpYqWVfiYXLQ8GxJ65W98BtMoYNa5S82zdUQeZsNFtY7LuQkNQxih7wTxHKbaX7V/li8C/D3DO4+UOJs0c/TfwBeBHAO7+UDixkoIjERGRvLN0y2pZBkfuvt9Q20g6IHuUu99TtK+z5JkiIiIiOZY0c7TOzHYgHGFlZkcDq6vWq5x5fsMqAC5YuqGw7+XrFmbVnYKOro7C9sTh47PryBB988GHC9vnzd29zJnSqErN1ySNQ+W07KVeVkuvqUwkzRydSlBS2yUc5PQ54DPV6pSIiIjIYJjZMeHX7QbbRqLMkbs/CSwws9FAi7u/PtgXbETTRm8DwHf6X781sV63xd80tPizvbV9qN2pilKDa4/50mGFfd0eLfgZZAsW7f/2GvauMVR7wdZaq9cpCSaNmJh1F0RS4liqGdpMs73nAb8EfgUMaoX0ssGRmX2+n/0AuPtAo8FFRESgsxPaBjF7zGCvk8pYygvPZltXW29mtwHbmdm1xQfd/fCBGhiorDY2fMwnKKNNCx+nALMr7q6IiDSdlqt/Q/s794M1ayu7cM1a2t+5Hy1X/6Ya3ZI6YGb/ZGbLzOwRM7vCzEaY2UQzW2xmj4dfJ1TY7AcJskfrgP9X4jGgsuG4u3817PzNwDuicpqZfYUgZSVDEB9kWqsFW+tN9H4P/NmKwr7FJ+ySVXdybSjzR9WrRisPNqXOTtq+dSEtDz5C+4LD6LjlOpgyeeDr1qylfcFhtCxfQdu3LqTjyEOVQaqiYEB2irfyJznHbBpwBjDb3Tea2VXAsQTJl1vd/XwzOxc4Fzingpf/sbufYGb/7e5/qLjzJB+QPRPoiD3vAGYN5gVFRKSJtLXRccM1dM/ehZblK2hfcNjAGaRYYNQ9exc6brhGgVENmKX7SKgNGGlmbcAoYBVwBBDOpMylwJEVvpU9zWxb4GNmNiHMRBUeSTuVxM+Ae8zsGoJRVkcB/1NhZ6VIvQ4yzcLYcSMK290erIXVYloXOYkou/LS4tMz7olIP6ZMpuOW6woBT9kMUnFglDTTJLnj7s+b2YXASmAjcLO732xmW7n76vCc1WY2pcKmfwjcCGwPLKF3IsvD/WUl+unj7t8APgm8DLwCfNLdv5nkWjNrNbMHzOz68PnuZnanmT1sZteZ2bgk7YiISI6FAVLZDJICo8yYBWW1tB7hnW/7m9l9scfC3q9pEwiyRNsB2wCjzezjQ30v7n6Ru+8KXOLu27v7drHHgIERJAyOzGwmwcCma8LHS+G+JM4EHo09vxg4193fHrb1hYTtiIhInpULkBQYNaLb3H1+7LGo6PgC4Cl3X+vum4FfA+8GXjSzqQDh1zWDeXF3/0yYkDktfMxNem3Sstrv6Jm0YCRBlPcYsFu5i8xsOvAh4BtANC3AzsAd4fZi4Cbg/ybtcCNo9kGm6ze9Uti++LGVAPzoA9MK+1ROS6bZv48kp0qU2DZffgnDjj9JgVHGMrj7fiWwj5mNIiirHQDcB2wATgTOD7/+djCNm9kZwEKCoAvgMjNb5O7/OdC1SSeB7DULn5m9A/h0gku/A5xNMB1A5BHgcII3ewwwI0kfRESkQRQFSMPnvRtAgVGGjNrPc+Tud5vZ1cD9BOu1PgAsAsYAV5nZyQQB1DGD7MangHe6+4agT/ZvwJ3AgMHRoH5Fd/f7gb3KnWNmhwJr3H1J0aGTgFPNbAlB0NTR5+Lg+oVRnXLt2pcG000REalXUyaz+fJLeu3afPklCoyajLt/2d13cfc57n6Cu29y95fc/QB33zH8un6QzRvQFXveRcIEWaLMUdFM2S0E03EPNJvXvsDhZvZBYAQwzsx+7u4fBw4K292JoOzWR1ibXASw5/w9tOpkA4kvgnv23PH9nidSisqJDWLNWoYdf1KvXcOOP0mZo8x4yvMc1cWP7Z8Ad4d32kMwJcCPk1yYNHM0NvYYTjAG6YhyF7j7ee4+3d1nEUzq9Ht3/3h0S56ZtQD/THDLnYiINIuiwdeblv6lsnmQRBIIlzg7CVhPcLf9J939O0muTToge7m795oRO1z1djCzZB9nZqeG278miOxEpIz47NeRdYtPy6Anvd215gGg9xKTb3ZuBmBzd3dhX7cHZ7y2Ochod3lPZjs8xMauVgA2dPb8txRlh0q9/2hgfzwTKTnQz11piedBkqqocOLGRO3ViaXAasJ4x8xmuvvKgS5Kmjk6L+G+ktz9dnc/NNz+rrvvFD7Odfe6yL2JiEiVlbtdP8k8SFI1BrTgqT3qITYys9OBFwnujL+eoOp1fZJry2aOzOwQggXcppnZRbFD4whGlouIiAwsyTxGyiBJus4Ednb3iu/qGqistopgzoHDCabgjrwO/FOlLyaBUqUCDS6VYvXy/bGh800A4kneFzauBmCfKXtU1FbUhlWYcy/1/jUwO0cqmeBRAVJmUi2F1UPqCJ4FXh3MhWWDI3d/EHjQzC5zd2WKRESkMp2dtB9yVGUTPBYHSIccRcfdt2vx2Sqzxrtb7UngdjP7HbAp2hkO1C5roLLaVe7+EeABK/GpuXviqbhFpLziQcf1MOAaYHTbqD773jbsbYNqq9KMkTSAtjY6zzuLtm9dSMcN1yTPAEUB0iFH0XneWQqMZDBWho/28JHYQN9tUb760EF0SkREhO6jj6TjyEMrD3CmTFbGqEaChWfTbS9r7v7VwV47UFltdbj5WXc/J34snIb7nL5XiYiIFBlsgKPASAbJzG6DvvU9d3//QNcm/a47kL6B0CEl9kkF1t9yRmFbg0ubU70Mus4T/VsRqQZPecxRXTgrtj0C+HsS3mk/0JijzwCfBbY3s4dih8YCf66wkyIiIlKHgnmO0m0vayXWdv2zmf0hybUDZY4uB24AvgWcG9v/+hAWgpOQlfj2USahcenvVkSkdsxsYuxpC7AnsHWSawcac/QqwRwBx4UvNIUgNTXGzMYkmYJbRERE6l+aZTXSbGvwlhCMOTKCctpTwMlJLkw05sjMDgP+HdgGWANsCzwK7DaIzoqIiEgdadCy2nbF+8xs3yTXJh2Q/XVgH+AWd9/DzPYnzCZJcqUWz4xEg7MnLuhZpcXDQfalym9S/4r/vl9afHqfY2vrZC6jPCmeYT5+Y4P+rYiImbUCHwGmATe4+zIzOxT4IjASGHBq/6TB0WZ3f8nMWsysxd1vC2/lFxERkbyztGfIztSPgRnAPcB/mtkzwLuAc939N0kaSBocvWJmY4A7gMvMbA1aeFZERETqz3xgrrt3m9kIYB3wNnd/IWkDSYOjI4C3CBab/RiwBfCvFXa2KVV6h1L8HM3nkj/xv++n//eTAGzRPg6Abu8uHNPf6dCVWsC5+JiIJGNknu1JU4d78B+uu79lZn+tJDCChMGRu2+IPb20khcQERGReue0pFhWS7OtQdglNjejATuEzw3wJOvCDjQJ5OuUmHo79gLjKuxwQ3Pv+ahe2LhmyO0V/2as34brV/R3FGWLoCdjFGmxNO8FkUipfxfxbNLam08FoK1Fy1CINIldh9rAQPMcjR3qC4iIiEh9a6Symrs/E96xdpO7LxhMG/pVVkRERBqKu3cBb5rZFoO5XnnmFL206eXC9tRRWwGlB1hHkpbJonlcSg08XRfOk9NqrZV1VlKhkmd90d+HyOClOU6oTrJQbwEPm9lioDB22t3P6P+SgIIjERGRJmcWPNJsrw78LnxUTMFRiiaNmFj2ePFvs+VmzI6fH836W27gqX5TlmZT6t9PNPhaRMTdLzWzkcBMd3+skms15khEREQKg7LTeNSDcF3YpcCN4fN5ZnZtkmuVORIREWlylvI8R2kuRTIEXwH2Bm4HcPelZtZnMdpSFBxlaKBSWJIB3KVmCT75awcDvWu+F+yz82C7KaGByqBSGyoli0hCne7+qvUeAJUoalNwJCIiIqmWw+qktPaImR0PtJrZjsAZwF+SXKjgqI6VG8C9fnFwJ2IUEeu36Op4cePaPvvKTc8gg5f0s9T3uogkdDrwJWATcDlwE/D1JBcqOBIREWlyRtrzHNXFmKOd3f1LBAFSRXS3moiIiKR6t1qdlNX+3cxWmNnXzGy3Si5U5ihHSpVzVGKojvWbXgFgl8MuL+zTZz1008+5A4Curu7CvreWPgjA3353IgATh4+veb9EpPG4+/5mtjXwEWCRmY0DfuHuA5bWlDkSERFpcsEM2Z7ao15SR+7+grtfBJxCMOfRvyS5TpkjERERSTVbUg+xkZntCnwUOBp4CbgS+D9JrlVwJFJCudJO/K6qZi213brqHgC6PRh02eU9gy+jzRWvjijsW7p6PADP/dt7S7S2XzW6KCLyE+AK4CB3X1XJhQqOREREmpzhqc5qXQ93q7n7PoO9VsFRjngdfLM1Cw14L++AbfYe8JxDZsSezKleX0RE4szsKnf/iJk9TO8ZsQ1wd587UBsKjkRERKSRxhxFv9UeOtgGFByJiIg0uehutTTby4q7rw6/PhPfb2atwLHAM6Wui1NwJBJTrpymUpuISP0L5zM6FZgGXAssBk4DziK4nf+ygdpQcCQiIiKNVFb7GfAycCfwKeALQDtwhLsvTdKAgqMcsdi320uLTwd6shnRc4AW09yeldCt+SIiDWV7d387gJldDKwDZrr760kbUHAkIiLS5Ix0xxyR7d3Vmwu9cO8ys6cqCYxAwZGIiIiQbiks47La7mb2WrhtwMjweXQr/7iBGlBwlFNR6SwqA8VLQ+sXnwGAZXm7QA4kGWAd/1z/eNUBVe+TiIgMjbu3DrUNDU4RERFpcobTYuk9kv5ubmbjzexqM1thZo+a2bvMbKKZLTazx8OvE6r77vtS5qhBxLMfuuW8OuZMDKZ5fnD9w4V9u098e1bdERFJj6U8N1Hytr4L3OjuR5tZOzAK+CJwq7ufb2bnAucC56TYuwEpcyQiIiI1F85H9F7gxwDu3uHurwBHAJeGp10KHFnrvik4EhERaXIGtOCpPoD9zey+2GNh0ctuD6wFfmJmD5jZxWY2GtgqNsv1amBKLT8LUFmtIZUapK0SW2DdW+uH3EZ7y7AUeiIi0vBuc/eTyxxvA94BnO7ud5vZdwlKaJlT5khERETC9dXSeST0HPCcu98dPr+aIFh60cymBn2yqcCatN/rQBQciYiINDmrwmMg7v4C8KyZ7RzuOgBYTrAe2onhvhOB3w7t3VVOZTVpCvESYyTJ/Ealzun27vQ6JiLS3E4HLgvvVHsS+CRB4uYqMzsZWAkcU+tOKTgSERERWlJcPiRpaS1cCHZ+iUOZzrqr4KiBrbyhZxxcs859VOks2JFy53cpcyQi0tAUHImIiDS5pOOEmoWCIxERkWYXLvuRlnCeo9xScNTAxg4bU9h+/sZg7q1KS0h5dP+6hwZ9bZLPYm64jIiIiDQmBUciIiJNTmW13hQcNYlRbSOB0pmR21ffB8B+U0vdMJA/75g0N/bstsz6ISKSJ5bq3Wr5LqtpEkgRERGRGGWOREREmlyw8Gy67eWZgiNpmHJapMu7su6CiIjkWNXLambWamYPmNn14fN5ZnaXmS01s/vMbO9q90FERETKM7PUHnnPHdVizNGZwKOx598Gvuru84B/CZ+LpKaru6vwEBGRZGq98Gw9q2pwZGbTgQ8BF8d2OzAu3N4CWFXNPoiIiIhUotpjjr4DnA2Mje37HHCTmV1IEJy9u8p9EBERkTJ6ymGpNZheWxmoWnBkZocCa9x9iZntFzv0GeCf3P1XZvYR4MfAghLXLwQWAsyYOaNa3ZQG1N7anui8UovSvvDmGgC2HjUl/Y6JiNSxNMOZfIdG1S2r7QscbmZPA1cC7zeznwMnAr8Oz/klUHJAtrsvcvf57j5/8uQtq9hNERERkR5VC47c/Tx3n+7us4Bjgd+7+8cJxhi9Lzzt/cDj1eqDiIiIDCwYRJ3mn3zLYp6jfwS+a2ZtwFuEpTORtMQX1123+LSKrlU5TUREahIcufvtwO3h9p+APWvxuiIiIpJMzsdQp0ozZEvDiDJG6xefUdiX6t0XIiINKlg+JL3/L/NeWNPCsyIiIiIxyhyJiIhIqmW1vCftFRxJw1EpTUREhkLBkYiISNNrhBvw06PgSEREpMmZqawWpwHZIiIiIjHKHImIiEjKZbV8p44UHImIiEi6ZbX0msqEymoiIiIiMcocSe5NOOFqAF5afPqA53Z7d7W7IyKSO9HCs2m2l2fKHImIiIjEKHMkIiIiqWZL8p45UnAkufe3ixcA0GID/9NOco7UluNA/heqFMkzw9JdXSDnEx3pJ4WIiIhIjDJHIiIiolmOYhQcSS7F7zob1z428XUTFny3sP3yLWem2qdG4B6UuCYeeNGg2yj3ucY//6G2JSIpMi3aHaeymoiIiEiMMkeSS/GB1Yrw0xNljIaSsSmXHYrmoko6ML7STFM50Xvq8q7Cvre6NgEwum1Uaq8jkkeGympx+rkiIiIiEqPMkYiIiOhW/hgFR9JU4uWiUiWbehoAvOrN1YXt3Q6/Cijd/2dv+BQAY4aNrko/rnzyLgC2Gdnz38V7p87v9/w0P8NybVU6P1L0ecXb1NxKIj1UVuuhspqIiIhIjDJH0rSiDEJ8WoBS2YVykgwYLtdWZ2xw8OQDvzdgG6WmIkhz0HLk0sfvKWyfuOM+AGzu3lzYd+/apcFrDx8DwJhh4wrH2iz4b6W1pbWwb0L7Fqn3sdKsT6Wf1/pbzhjU64jkkYV/0mwvz5Q5EhEREYlR5khERKTJmUFLmuOx02sqEwqOpOnF59yJSilJSy8v3vQZANpb2/sciwYMJy7jLA7LOBXe5ZHGAOhoZuxyrz2sZVhhe6/J84b8mrX2xuYNAKy+6ZTCvhGtw/s9P/p7W3vzqYV9bS36L1MaV95LYWlSWU1EREQkRsGRiIiIYJbuI9lrWquZPWBm14fPJ5rZYjN7PPw6oZrvuT/KEYvERGnlNEpVabZVbc2w4GSl80CVu0NQpNGkfbdaBaOOzgQeBaJbXs8FbnX3883s3PD5OSl2LBFljkRERKTmzGw68CHg4tjuI4BLw+1LgSNr3C1AmSORuhUNkoaeBWFFRKol1dVDkp32HeBsYGxs31buvhrA3Veb2ZT0epWcMkciIiJSDfub2X2xx8LogJkdCqxx9yUZ9q9fyhyJiIhINW7lv83dT+7n2L7A4Wb2QWAEMM7Mfg68aGZTw6zRVGBN2p1KQsGRSJ2Kl9JKDQSudKkTqUw0T5VIM6jkDrOk7ZXj7ucB5wXn2n7AWe7+cTO7ADgROD/8+tv0epWcymoiIiJSL84HDjSzx4EDw+c1p8yRSAaSzJr90uLTyx5ft/i0Xm0pg5SOKGM0cUGQudPnKs0iq4Vn3f124PZw+yXggNQ6MkjKHImIiIjEKHMkIiLS5Ix0syV5n1ZWwZFIlRSXZ+JeCBc/HV5m4dOBtFprydcDLSA5FCqnSXOydGfKz/l/QSqriYiIiMQocySSonj2plYZiFJrgK1ffAbQHGumpaHTu7LugkgdyGRttbqk4EhEREQUGsWorCYiIiISo8yRSApKzVtU6wG98dfT3EfJRIv7Tj7we4V9+sykGRkqw8cpcyQiIiISo8yRiIhI0zM06qiHgiOREqK7l1pjydUNnW8CMOOQi/ucHy310WL1lYztit2FVTwvkvQs7qtSmohCo7j6+p9cREREJGPKHElTiAbeRpmCochDlqHU3Ed56HctxD+TVTd9OsOeiNSXdGfWz3fuSMGRiIhIswtuV0u3vRxTWU1EREQkRpkjaTil5hyKqLQkmg9KpC/dq9abMkciIiIiMcocSa683PEqAK93vFbYN3PMDEBZgLjos4gWoBURKU+5ozgFRyIiIpLq3Wr5Do1UVhMRERHpRZkjqVtOODfRgp65iQrz97RvUdjX7OW0aDZvLZ4qIkOhdWd7KHMkIiIiEqPMkWSqVHaoWKlbr/s73kw6ujcDsNVBPwCa93NIqtQs6RqwLhKnAdkRBUciIiJNzsI/6bWXb1UPjsysFbgPeN7dDzWzXwA7h4fHA6+4+7xq90NEREQkiVpkjs4EHgXGAbj7R6MDZvb/gFdr0AepIxs7Nxa2t/nYr4HKS0Lrb1E5pL1lGNBTGio3Mzio7Pb4a4/32ReV2Jr9sxGB/Gd70lTVAdlmNh34EHBxiWMGfAS4opp9EBERkQTM0n3kWLXvVvsOcDbQXeLYe4AX3b3vr3MiIiIiGalaWc3MDgXWuPsSM9uvxCnHUSZrZGYLgYUAM2bOqEYXJSOHX/FMz5PxEwfVRqUDB7vCuYBarXVQr1fPLPwN7YWbTinsG946HIBu7/m9pFB2mzot+LrF+D5ttbQEbb100QFV6Gm2dtpiJwBevmWnwr43wxJvvCSpEps0o2DxEA3IjlQzc7QvcLiZPQ1cCbzfzH4OYGZtwIeBX/R3sbsvcvf57j5/8uQtq9hNERERkR5Vyxy5+3nAeQBh5ugsd/94eHgBsMLdn6vW60v9eOr1pwH48WPBb+mLT9i1cGzj8bMG1eZAg4/708hZgShbFNdiPb//RO89yqJF8/4AtLU056weo9pGZt0FkTqR7q38ec8dZTVD9rFoILaIiIjUoZr8uujutwO3x55/ohavKyIiIlKp5sylS01tOTwYM/b1+WP7HBvZOqKitoZaFtPA29ig9HxnvUUkTdZzc0c6zeX7PxgFRyIiIoJ+Y+qh4Eiqblx734xRVuIza0dZpGbNIEnPwsciInEKjkRERJqckW7eKO85qKzuVhMRERGpS8ocSVOJDxKMymkapN0cys2Npb93Ec1zFKfgSERERNJdLDbfsZGCIxHJt6SzpSs7JCJJKTgSERERFdViNCBbREREJEaZI5GYjq4OANpb2zPuifRn0YolADyybhwwcLlssIsUizQT04DsXhQciYiICHkPaNKkspqIiIhIjDJH0vTiZZmoBBMtM5L3xRMb0cJd9qzo/MJ8VoctCp5ftzD1Pok0At3J30OZIxEREaFnEZG0HgO8mtkMM7vNzB41s2Vmdma4f6KZLTazx8OvE9J9nwNT5kgkptSs2f2dU0p8IVNlnerL7A/tA8DxN60s7Gu14O/rZwdtm0mfRJpcJ/B/3P1+MxsLLDGzxcAngFvd/XwzOxc4Fzinlh1T5khERKTpWap/kmSO3H21u98fbr8OPApMA44ALg1PuxQ4sipvuQwFRyIiIpIpM5sF7AHcDWzl7qshCKCAKbXuj8pqIiWUKp3dtvpeoHfJ7fBzjgBgZHtXcGzk5sKxb+29SzW7KBX68ylz++xzD8pq337oocK+43fYEoDpo6fVpmMidSDI9aQ3FCBsaX8z+1xs9yJ3X9TnXLMxwK+Az7n7a5bmyPBBUnAkIiLS7JJVwiprD25z95PLnmY2jCAwuszdfx3uftHMprr7ajObCqxJsWeJKDgSSWj/qXsB8PIte2XcE0lL9Bvq2XP7ZpVEpLos+Af4Y+BRd//32KFrgROB88Ovv6113xQciYiISBbLh+wLnAA8bGZLw31fJAiKrjKzk4GVwDEpdiwRBUciIiJSc+7+J/qPog6oZV+KKTgSERFpeukuPJv9kOqhUXAkIiIi1RiQnVua50hEREQkRpkjERGRJpf+PEf5Th0pOBIREZHcBzRpUllNREREJEaZIxEREdF47BhljkRERERilDkSERFpegapLvia79yRgiMREZEml/bdanmnspqIiIhIjDJHIiIiogHZMQqOREREmp2R7pijVMcv1Z7KaiIiIiIxyhyJiIg0OQv/pNlinilzJCIiIhKjzJGIiIgobxSj4EhEREQ0z1GMymoiIiIiMcociYiISP5rYSlS5khEREQkRpkjERGRJpf22mp5H7+k4EhERKTppTvPUb5DI5XVRERERHpRcCQiIiISo7KaiIiIYFp4tkCZIxEREZEYZY5ERESaXNoLz+Y7b6TMkYiIiEgvyhyJiIhI7rM9aVJwJCIi0uyMlAdR5zvUUllNREREJEaZIxEREdGA7BhljkRERERilDkSERFpckb+sz1pUnAkIiLS9NKe5yjfoZbKaiIiIiIxyhyJiIhIurfya2218sys1cweMLPrY/tON7PHzGyZmX272n0QERGR8izFR97VInN0JvAoMA7AzPYHjgDmuvsmM5tSgz6IiIiIJFLVzJGZTQc+BFwc2/0Z4Hx33wTg7muq2QcREREpL8j4pPkn36pdVvsOcDbQHdu3E/AeM7vbzP5gZntVuQ8iIiIiiVUtODKzQ4E17r6k6FAbMAHYB/gCcJVZ35FbZrbQzO4zs/vWrn2pWt0UERERs3QfOc8dVXPM0b7A4Wb2QWAEMM7Mfg48B/za3R24x8y6gUnA2vjF7r4IWASw5/w9vIr9FBERaXpadrZH1TJH7n6eu09391nAscDv3f3jwG+A9wOY2U5AO7CuWv0QERERqUQW8xxdAlxiZo8AHcCJYRZJREREMpL/YdTpqUlw5O63A7eH2x3Ax2vxuiIiIjKw6G619NrLd6Cl5UNEREQkE2Z2cDgp9BNmdm7W/YkoOBIREZF0p8hOkDgys1bg+8AhwGzgODObneI7GjQFRyIiIpKFvYEn3P3JcMjNlQQraGROC8+KiIg0t8777r2f0075XGoNPvzQMoDNA5w2DXg29vw54J2pdWIIchEc3b9k6bqRbeOfybofKZmEpi4AfQ6gzwD0GYA+A9BnAH0/g21r9cLu/qSZvf3Jvz01POWm9zKz+2LPF4VzGEZKFd/q4u71XARH7j456z6kxczuc/f5Wfcja/oc9BmAPgPQZwD6DCD7z8DdH6lCs0uAH5Y5/hwwI/Z8OrCqCv2omMYciYiISBbuBXY0s+3MrJ1gwuhrM+4TkJPMkYiIiDQWd+80s9OAm4BW4BJ3X5ZxtwAFR1lYNPApTUGfgz4D0GcA+gxAnwE06Wfg7v8L/G/W/ShmWrlDREREpIfGHImIiIjEKDiqITMbb2ZXm9kKM3vUzN6VdZ9qycx2NrOlscdrZva5rPtVa2b2T2a2zMweMbMrzGxE1n2qNTM7M3z/y5rpe8DMLjGzNeHC29G+iWa22MweD79OyLKP1dbPZ3BM+L3QbWYNf9daP5/BBeHPhofM7BozG59hF5uegqPa+i5wo7vvAuwOPJpxf2rK3R9z93nuPg/YE3gTuCbbXtWWmU0DzgDmu/scgkGIx2bbq9oysznAPxLMjrs7cKiZ7Zhtr2rmp8DBRfvOBW519x2BW8Pnjeyn9P0MHgE+DNxR895k46f0/QwWA3PcfS7wV+C8WndKeig4qhEzGwe8F/gxgLt3uPsrmXYqWwcAf3P3RpncsxJtwEgzawNGUSfzetTQrsBd7v6mu3cCfwCOyrhPNeHudwDri3YfAVwabl8KHFnLPtVaqc/A3R9198cy6lLN9fMZ3Bz+ewC4i2DOH8mIgqPa2R5YC/zEzB4ws4vNbHTWncrQscAVWXei1tz9eeBCYCWwGnjV3W/Otlc19wjwXjPb0sxGAR+k90RwzWYrd18NEH6dknF/JHsnATdk3YlmpuCodtqAdwD/5e57ABto/PR5SeFkX4cDv8y6L7UWjic5AtgO2AYYbWYfz7ZXteXujwL/RlBGuBF4EOgse5FIkzCzLxH8e7gs6740MwVHtfMc8Jy73x0+v5ogWGpGhwD3u/uLWXckAwuAp9x9rbtvBn4NvDvjPtWcu//Y3d/h7u8lKC88nnWfMvSimU0FCL+uybg/khEzOxE4FPiYa56dTCk4qhF3fwF41sx2DncdACzPsEtZOo4mLKmFVgL7mNkoMzOC74OmGpgPYGZTwq8zCQbiNuv3AwTLJZwYbp8I/DbDvkhGzOxg4BzgcHd/M+v+NDtNAllDZjYPuBhoB54EPunuL2faqRoLx5g8C2zv7q9m3Z8smNlXgY8SpM4fAD7l7puy7VVtmdkfgS2BzcDn3f3WjLtUE2Z2BbAfwQrsLwJfBn4DXAXMJAiej3H34kHbDaOfz2A98J/AZOAVYKm7fyCjLlZdP5/BecBw4KXwtLvc/ZRMOigKjkRERETiVFYTERERiVFwJCIiIhKj4EhEREQkRsGRiIiISIyCIxEREZEYBUciDcDM3qhCm4eb2bnh9pFmNnsQbdzeDKusi0hjUXAkIiW5+7Xufn749Eig4uBIRCSPFByJNBALXGBmj5jZw2b20XD/fmEW52ozW2Fml4UzdGNmHwz3/cnMLjKz68P9nzCz75nZuwnWwrvAzJaa2Q7xjJCZTTKzp8PtkWZ2pZk9ZGa/AEbG+naQmd1pZveb2S/NbExtPx0RkWTasu6AiKTqw8A8YHeC2XfvNbM7wmN7ALsBq4A/A/ua2X3Aj4D3uvtT4cy9vbj7X8zsWuB6d78aIIyrSvkM8Ka7zzWzucD94fmTgH8GFrj7BjM7B/g88K8pvGcRkVQpOBJpLH8HXOHuXQQLmv4B2At4DbjH3Z8DMLOlwCzgDeBJd38qvP4KYOEQXv+9wEUA7v6QmT0U7t+HoCz35zCwagfuHMLriIhUjYIjkcbSb0oHiK/f1kXw77/c+eV00lOWH1F0rNSaRAYsdvfjBvl6IiI1ozFHIo3lDuCjZtZqZpMJMjn3lDl/BbC9mc0Kn3+0n/NeB8bGnj8N7BluH130+h8DMLM5wNxw/10EZby3hcdGmdlOSd6QiEitKTgSaSzXAA8BDwK/B8529xf6O9ndNwKfBW40sz8RrBD+aolTrwS+YGYPmNkOwIXAZ8zsLwRjmyL/BYwJy2lnEwZm7r4W+ARwRXjsLmCXobxREZFqMfdSGXARaRZmNsbd3wjvXvs+8Li7/0fW/RIRyYoyRyLyj+EA7WXAFgR3r4mINC1ljkRERERilDkSERERiVFwJCIiIhKj4EhEREQkRsGRiIiISIyCIxEREZEYBUciIiIiMf8fV+FktRUAc2kAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 720x576 with 2 Axes>"
       ]
@@ -907,7 +907,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "source": [
     "model.get_value_at_coords(\"RiverRunoff\", lon=target_longitudes, lat=target_latitudes)"
    ],
@@ -916,11 +916,11 @@
      "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "array([200.80599976,  44.62182236,   0.        ])"
+       "array([200.49531555,  44.60787582,   0.        ])"
       ]
      },
      "metadata": {},
-     "execution_count": 15
+     "execution_count": 16
     }
    ],
    "metadata": {}
@@ -934,19 +934,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "source": [
     "model.finalize()"
    ],
    "outputs": [],
    "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "source": [],
+   "outputs": [],
+   "metadata": {}
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
+   "name": "python3",
+   "display_name": "Python 3.9.5 64-bit (conda)"
   },
   "language_info": {
    "codemirror_mode": {
@@ -958,7 +964,10 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.2"
+   "version": "3.9.5"
+  },
+  "interpreter": {
+   "hash": "4f63c3f017d58640bc2174e5f1b6c1610e3d96c1a3fe90d1d439f265cee739e3"
   }
  },
  "nbformat": 4,
diff --git a/docs/system_setup.rst b/docs/system_setup.rst
index 37fb4e6e..7675e6ab 100644
--- a/docs/system_setup.rst
+++ b/docs/system_setup.rst
@@ -242,6 +242,7 @@ Docker images will be downloaded with ``docker pull``:
     docker pull ewatercycle/marrmot-grpc4bmi:2020.11
     docker pull ewatercycle/pcrg-grpc4bmi:setters
     docker pull ewatercycle/wflow-grpc4bmi:2020.1.1
+    docker pull ewatercycle/wflow-grpc4bmi:2020.1.2
 
 Singularity
 ~~~~~~~~~~~
@@ -256,6 +257,7 @@ Singularity images should be stored in configured directory
     singularity build ewatercycle-marrmot-grpc4bmi_2020.11.sif docker://ewatercycle/marrmot-grpc4bmi:2020.11
     singularity build ewatercycle-pcrg-grpc4bmi_setters.sif docker://ewatercycle/pcrg-grpc4bmi:setters
     singularity build ewatercycle-wflow-grpc4bmi_2020.1.1.sif docker://ewatercycle/wflow-grpc4bmi:2020.1.1
+    singularity build ewatercycle-wflow-grpc4bmi_2020.1.2.sif docker://ewatercycle/wflow-grpc4bmi:2020.1.2
     cd -
 
 Download example parameter sets
diff --git a/src/ewatercycle/models/wflow.py b/src/ewatercycle/models/wflow.py
index a2feb89f..abc9a6eb 100644
--- a/src/ewatercycle/models/wflow.py
+++ b/src/ewatercycle/models/wflow.py
@@ -34,7 +34,7 @@ class Wflow(AbstractModel[WflowForcing]):
             If None, it is assumed that forcing is included with the parameter_set.
     """
 
-    available_versions = ("2020.1.1",)
+    available_versions = ("2020.1.1", "2020.1.2")
     """Show supported WFlow versions in eWaterCycle"""
 
     def __init__(  # noqa: D107
@@ -51,12 +51,14 @@ def _set_docker_image(self):
         images = {
             # "2019.1": "ewatercycle/wflow-grpc4bmi:2019.1", # no good ini file
             "2020.1.1": "ewatercycle/wflow-grpc4bmi:2020.1.1",
+            "2020.1.2": "ewatercycle/wflow-grpc4bmi:2020.1.2",
         }
         self.docker_image = images[self.version]
 
     def _singularity_image(self, singularity_dir):
         images = {
             "2020.1.1": "ewatercycle-wflow-grpc4bmi_2020.1.1.sif",
+            "2020.1.2": "ewatercycle-wflow-grpc4bmi_2020.1.2.sif",
         }
         image = singularity_dir / images[self.version]
         return str(image)
@@ -79,7 +81,7 @@ def _setup_default_config(self):
             cfg.set("inputmapstacks", "Temperature", forcing.Temperature)
             cfg.set("run", "starttime", _iso_to_wflow(forcing.start_time))
             cfg.set("run", "endtime", _iso_to_wflow(forcing.end_time))
-        if self.version == "2020.1.1":
+        if self.version in self.available_versions:
             if not cfg.has_section("API"):
                 logger.warning(
                     "Config file from parameter set is missing API section, "
diff --git a/src/ewatercycle/parameter_sets/_wflow.py b/src/ewatercycle/parameter_sets/_wflow.py
index 9fbad5f5..ee1cef3e 100644
--- a/src/ewatercycle/parameter_sets/_wflow.py
+++ b/src/ewatercycle/parameter_sets/_wflow.py
@@ -16,6 +16,6 @@ def example_parameter_sets() -> Iterable[ExampleParameterSet]:
             config_url="https://github.com/openstreams/wflow/raw/master/examples/wflow_rhine_sbm_nc/wflow_sbm_NC.ini",  # noqa: E501
             doi="N/A",
             target_model="wflow",
-            supported_model_versions={"2020.1.1"},
+            supported_model_versions={"2020.1.1", "2020.1.2"},
         )
     ]