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   "id": "a334d0e4-acce-4de0-9678-cd3e8cfe8107",
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   "source": [
    "import geopandas as gpd\n",
    "from pathlib import Path\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import folium\n",
    "import seaborn as sns\n",
    "import datetime as dt\n",
    "import numpy as np\n",
    "from branca.colormap import linear"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "66c1c682-a9bc-4a5c-92b7-72590667df0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "city = 'Luanda'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "18389ca3-54a2-40f4-abec-07c9380d5308",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Owner\\AppData\\Local\\Temp\\ipykernel_17852\\119210925.py:4: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
      "\n",
      "  centroid = cat.centroid\n"
     ]
    }
   ],
   "source": [
    "# read catchment AOI\n",
    "cat = gpd.read_file('AOI/luanda_catchment_level4.shp').to_crs(epsg = 4326)\n",
    "aoi = gpd.read_file('AOI/luanda.shp').to_crs(epsg = 4326)\n",
    "centroid = cat.centroid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4c7cc4db-f74f-4514-a042-3524c91d9478",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_folder = Path('output')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4dfce44c-7634-4ecc-9bd8-ce32eb92e082",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Dams and reservoirs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3cc8fdc1-f999-4ad5-9e6b-a55443fd055e",
   "metadata": {},
   "outputs": [],
   "source": [
    "dams = gpd.read_file(output_folder / f'{city.lower()}_dams.shp')\n",
    "reservoirs = gpd.read_file(output_folder / f'{city.lower()}_reservoirs.shp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7d1533af-f632-4421-9821-4b3bda4f0c75",
   "metadata": {},
   "outputs": [],
   "source": [
    "dams['DAM_ID'] = dams['DAM_ID'].astype('int').astype('string')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1a2f6a7f-c9d9-4a25-abf3-74f553092b72",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
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0, &quot;glc_pc_s07&quot;: 0, &quot;glc_pc_s08&quot;: 0, &quot;glc_pc_s09&quot;: 0, &quot;glc_pc_s10&quot;: 0, &quot;glc_pc_s11&quot;: 0, &quot;glc_pc_s12&quot;: 38, &quot;glc_pc_s13&quot;: 41, &quot;glc_pc_s14&quot;: 0, &quot;glc_pc_s15&quot;: 0, &quot;glc_pc_s16&quot;: 0, &quot;glc_pc_s17&quot;: 0, &quot;glc_pc_s18&quot;: 0, &quot;glc_pc_s19&quot;: 2, &quot;glc_pc_s20&quot;: 2, &quot;glc_pc_s21&quot;: 0, &quot;glc_pc_s22&quot;: 0, &quot;glc_pc_u01&quot;: 0, &quot;glc_pc_u02&quot;: 0, &quot;glc_pc_u03&quot;: 0, &quot;glc_pc_u04&quot;: 0, &quot;glc_pc_u05&quot;: 0, &quot;glc_pc_u06&quot;: 0, &quot;glc_pc_u07&quot;: 0, &quot;glc_pc_u08&quot;: 0, &quot;glc_pc_u09&quot;: 0, &quot;glc_pc_u10&quot;: 0, &quot;glc_pc_u11&quot;: 0, &quot;glc_pc_u12&quot;: 12, &quot;glc_pc_u13&quot;: 74, &quot;glc_pc_u14&quot;: 0, &quot;glc_pc_u15&quot;: 0, &quot;glc_pc_u16&quot;: 0, &quot;glc_pc_u17&quot;: 0, &quot;glc_pc_u18&quot;: 0, &quot;glc_pc_u19&quot;: 14, &quot;glc_pc_u20&quot;: 0, &quot;glc_pc_u21&quot;: 0, &quot;glc_pc_u22&quot;: 0, &quot;gwt_cm_sav&quot;: 317, &quot;hdi_ix_sav&quot;: 533, &quot;hft_ix_s09&quot;: 56, &quot;hft_ix_s93&quot;: 52, &quot;hft_ix_u09&quot;: 76, &quot;hft_ix_u93&quot;: 67, &quot;inu_pc_slt&quot;: 7, &quot;inu_pc_smn&quot;: 1, &quot;inu_pc_smx&quot;: 5, &quot;inu_pc_ult&quot;: 97, &quot;inu_pc_umn&quot;: 14, &quot;inu_pc_umx&quot;: 83, &quot;ire_pc_sse&quot;: 0, &quot;ire_pc_use&quot;: 0, &quot;kar_pc_sse&quot;: 0, &quot;kar_pc_use&quot;: 0, &quot;lit_cl_smj&quot;: 3, &quot;lka_pc_sse&quot;: 0, &quot;lka_pc_use&quot;: 0, &quot;lkv_mc_usu&quot;: 0, &quot;nli_ix_sav&quot;: 25, &quot;nli_ix_uav&quot;: 0, &quot;pac_pc_sse&quot;: 98, &quot;pac_pc_use&quot;: 64, &quot;pet_mm_s01&quot;: 130, &quot;pet_mm_s02&quot;: 121, &quot;pet_mm_s03&quot;: 129, &quot;pet_mm_s04&quot;: 113, &quot;pet_mm_s05&quot;: 101, &quot;pet_mm_s06&quot;: 90, &quot;pet_mm_s07&quot;: 86, &quot;pet_mm_s08&quot;: 94, &quot;pet_mm_s09&quot;: 104, &quot;pet_mm_s10&quot;: 117, &quot;pet_mm_s11&quot;: 119, &quot;pet_mm_s12&quot;: 125, &quot;pet_mm_syr&quot;: 1330, &quot;pet_mm_uyr&quot;: 1334, &quot;pnv_cl_smj&quot;: 12, &quot;pnv_pc_s01&quot;: 0, &quot;pnv_pc_s02&quot;: 0, &quot;pnv_pc_s03&quot;: 0, &quot;pnv_pc_s04&quot;: 0, &quot;pnv_pc_s05&quot;: 0, &quot;pnv_pc_s06&quot;: 0, &quot;pnv_pc_s07&quot;: 0, &quot;pnv_pc_s08&quot;: 0, &quot;pnv_pc_s09&quot;: 37, &quot;pnv_pc_s10&quot;: 12, &quot;pnv_pc_s11&quot;: 0, &quot;pnv_pc_s12&quot;: 51, &quot;pnv_pc_s13&quot;: 0, &quot;pnv_pc_s14&quot;: 0, &quot;pnv_pc_s15&quot;: 0, &quot;pnv_pc_u01&quot;: 0, &quot;pnv_pc_u02&quot;: 0, &quot;pnv_pc_u03&quot;: 0, &quot;pnv_pc_u04&quot;: 0, &quot;pnv_pc_u05&quot;: 0, &quot;pnv_pc_u06&quot;: 0, &quot;pnv_pc_u07&quot;: 0, &quot;pnv_pc_u08&quot;: 0, &quot;pnv_pc_u09&quot;: 24, &quot;pnv_pc_u10&quot;: 0, &quot;pnv_pc_u11&quot;: 0, &quot;pnv_pc_u12&quot;: 76, &quot;pnv_pc_u13&quot;: 0, &quot;pnv_pc_u14&quot;: 0, &quot;pnv_pc_u15&quot;: 0, &quot;pop_ct_ssu&quot;: 3.08, &quot;pop_ct_usu&quot;: 0.035, &quot;ppd_pk_sav&quot;: 0.989, &quot;ppd_pk_uav&quot;: 0.995, &quot;pre_mm_s01&quot;: 51, &quot;pre_mm_s02&quot;: 73, &quot;pre_mm_s03&quot;: 177, &quot;pre_mm_s04&quot;: 215, &quot;pre_mm_s05&quot;: 19, &quot;pre_mm_s06&quot;: 0, &quot;pre_mm_s07&quot;: 0, &quot;pre_mm_s08&quot;: 0, &quot;pre_mm_s09&quot;: 2, &quot;pre_mm_s10&quot;: 22, &quot;pre_mm_s11&quot;: 106, &quot;pre_mm_s12&quot;: 63, &quot;pre_mm_syr&quot;: 727, &quot;pre_mm_uyr&quot;: 691, &quot;prm_pc_sse&quot;: 0, &quot;prm_pc_use&quot;: 0, &quot;pst_pc_sse&quot;: 38, &quot;pst_pc_use&quot;: 32, &quot;rdd_mk_sav&quot;: 95, &quot;rdd_mk_uav&quot;: 0, &quot;rev_mc_usu&quot;: 0, &quot;ria_ha_ssu&quot;: 489.438, &quot;ria_ha_usu&quot;: 1.884, &quot;riv_tc_ssu&quot;: 2095.88, &quot;riv_tc_usu&quot;: 1.831, &quot;run_mm_syr&quot;: 189, &quot;sgr_dk_sav&quot;: 47, &quot;slp_dg_sav&quot;: 15, &quot;slp_dg_uav&quot;: 49, &quot;slt_pc_sav&quot;: 22, &quot;slt_pc_uav&quot;: 24, &quot;snd_pc_sav&quot;: 49, &quot;snd_pc_uav&quot;: 49, &quot;snw_pc_s01&quot;: 0, &quot;snw_pc_s02&quot;: 0, &quot;snw_pc_s03&quot;: 0, &quot;snw_pc_s04&quot;: 0, &quot;snw_pc_s05&quot;: 0, &quot;snw_pc_s06&quot;: 0, &quot;snw_pc_s07&quot;: 0, &quot;snw_pc_s08&quot;: 0, &quot;snw_pc_s09&quot;: 0, &quot;snw_pc_s10&quot;: 0, &quot;snw_pc_s11&quot;: 0, &quot;snw_pc_s12&quot;: 0, &quot;snw_pc_smx&quot;: 0, &quot;snw_pc_syr&quot;: 0, &quot;snw_pc_uyr&quot;: 0, &quot;soc_th_sav&quot;: 23, &quot;soc_th_uav&quot;: 29, &quot;swc_pc_s01&quot;: 38, &quot;swc_pc_s02&quot;: 39, &quot;swc_pc_s03&quot;: 52, &quot;swc_pc_s04&quot;: 77, &quot;swc_pc_s05&quot;: 81, &quot;swc_pc_s06&quot;: 63, &quot;swc_pc_s07&quot;: 49, &quot;swc_pc_s08&quot;: 38, &quot;swc_pc_s09&quot;: 29, &quot;swc_pc_s10&quot;: 24, &quot;swc_pc_s11&quot;: 30, &quot;swc_pc_s12&quot;: 38, &quot;swc_pc_syr&quot;: 47, &quot;swc_pc_uyr&quot;: 44, &quot;tbi_cl_smj&quot;: 7, &quot;tec_cl_smj&quot;: 35, &quot;tmp_dc_s01&quot;: 258, &quot;tmp_dc_s02&quot;: 262, &quot;tmp_dc_s03&quot;: 265, &quot;tmp_dc_s04&quot;: 263, &quot;tmp_dc_s05&quot;: 249, &quot;tmp_dc_s06&quot;: 220, &quot;tmp_dc_s07&quot;: 204, &quot;tmp_dc_s08&quot;: 204, &quot;tmp_dc_s09&quot;: 220, &quot;tmp_dc_s10&quot;: 241, &quot;tmp_dc_s11&quot;: 253, &quot;tmp_dc_s12&quot;: 255, &quot;tmp_dc_smn&quot;: 204, &quot;tmp_dc_smx&quot;: 265, &quot;tmp_dc_syr&quot;: 241, &quot;tmp_dc_uyr&quot;: 241, &quot;urb_pc_sse&quot;: 0, &quot;urb_pc_use&quot;: 0, &quot;wet_cl_smj&quot;: 4, &quot;wet_pc_s01&quot;: 0, &quot;wet_pc_s02&quot;: 0, &quot;wet_pc_s03&quot;: 0, &quot;wet_pc_s04&quot;: 1, &quot;wet_pc_s05&quot;: 0, &quot;wet_pc_s06&quot;: 0, &quot;wet_pc_s07&quot;: 0, &quot;wet_pc_s08&quot;: 0, &quot;wet_pc_s09&quot;: 0, &quot;wet_pc_sg1&quot;: 1, &quot;wet_pc_sg2&quot;: 1, &quot;wet_pc_u01&quot;: 0, &quot;wet_pc_u02&quot;: 0, &quot;wet_pc_u03&quot;: 0, &quot;wet_pc_u04&quot;: 2, &quot;wet_pc_u05&quot;: 0, &quot;wet_pc_u06&quot;: 0, &quot;wet_pc_u07&quot;: 0, &quot;wet_pc_u08&quot;: 0, &quot;wet_pc_u09&quot;: 0, &quot;wet_pc_ug1&quot;: 2, &quot;wet_pc_ug2&quot;: 2}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "        function geo_json_45597d525ff0369e069ac0cbc5a15b85_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;color&quot;: &quot;blue&quot;, &quot;fillColor&quot;: &quot;blue&quot;, &quot;weight&quot;: 1};\n",
       "            }\n",
       "        }\n",
       "        function geo_json_45597d525ff0369e069ac0cbc5a15b85_highlighter(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;fillOpacity&quot;: 0.7};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_45597d525ff0369e069ac0cbc5a15b85_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "                mouseout: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        geo_json_45597d525ff0369e069ac0cbc5a15b85.resetStyle(e.target);\n",
       "                    }\n",
       "                },\n",
       "                mouseover: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        const highlightStyle = geo_json_45597d525ff0369e069ac0cbc5a15b85_highlighter(e.target.feature)\n",
       "                        e.target.setStyle(highlightStyle);\n",
       "                    }\n",
       "                },\n",
       "                click: function(e) {\n",
       "                    if (typeof e.target.getBounds === &#x27;function&#x27;) {\n",
       "                        map_eb4977ee5d2ea01a122d4197f30e63e6.fitBounds(e.target.getBounds());\n",
       "                    }\n",
       "                    else if (typeof e.target.getLatLng === &#x27;function&#x27;){\n",
       "                        let zoom = map_eb4977ee5d2ea01a122d4197f30e63e6.getZoom()\n",
       "                        zoom = zoom &gt; 12 ? zoom : zoom + 1\n",
       "                        map_eb4977ee5d2ea01a122d4197f30e63e6.flyTo(e.target.getLatLng(), zoom)\n",
       "                    }\n",
       "                }\n",
       "            });\n",
       "        };\n",
       "        var geo_json_45597d525ff0369e069ac0cbc5a15b85 = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_45597d525ff0369e069ac0cbc5a15b85_onEachFeature,\n",
       "            \n",
       "                style: geo_json_45597d525ff0369e069ac0cbc5a15b85_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_45597d525ff0369e069ac0cbc5a15b85_add (data) {\n",
       "            geo_json_45597d525ff0369e069ac0cbc5a15b85\n",
       "                .addData(data)\n",
       "                .addTo(map_eb4977ee5d2ea01a122d4197f30e63e6);\n",
       "        }\n",
       "            geo_json_45597d525ff0369e069ac0cbc5a15b85_add({&quot;bbox&quot;: [13.789724934895844, -9.020275065103874, 14.094719509548554, -8.896391601562414], &quot;features&quot;: [{&quot;bbox&quot;: [13.789724934895844, -9.020275065103874, 14.094719509548554, -8.896391601562414], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.045305853949685, -8.896745605468709], [14.04585381401904, -8.897809244791574], [14.043095431857637, -8.897753092447601], [14.041919216579856, -8.898624945746462], [14.043683810763866, -8.900320366753363], [14.043074951171832, -8.902196180555165], [14.042508273654505, -8.902786187065772], [14.040607367621476, -8.903708224826346], [14.03599867078998, -8.908136393228801], [14.03719129774305, -8.910145670572888], [14.038355984157988, -8.909580620659654], [14.038324924045128, -8.908058268229126], [14.040290798611068, -8.909170464409613], [14.03917005750867, -8.910247124565672], [14.039163411458276, -8.910573730468684], [14.039798041449615, 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123.16, &quot;CAP_MAX&quot;: -99.0, &quot;CAP_MCM&quot;: 1560.0, &quot;CAP_MIN&quot;: -99.0, &quot;CAP_REP&quot;: 1560.0, &quot;CATCH_REP&quot;: -99, &quot;CATCH_SKM&quot;: 7474, &quot;COMMENTS&quot;: null, &quot;COUNTRY&quot;: &quot;Angola&quot;, &quot;DAM_HGT_M&quot;: 41, &quot;DAM_LEN_M&quot;: -99, &quot;DAM_NAME&quot;: &quot;Quiminha&quot;, &quot;DATA_INFO&quot;: null, &quot;DEPTH_M&quot;: 12.7, &quot;DIS_AVG_LS&quot;: 43630, &quot;DOR_PC&quot;: 113.4, &quot;EDITOR&quot;: &quot;McGill-BL&quot;, &quot;ELEV_MASL&quot;: 51, &quot;GRAND_ID&quot;: 3676, &quot;LAKE_CTRL&quot;: null, &quot;LAT_DD&quot;: -8.963743, &quot;LONG_DD&quot;: 13.790871, &quot;MAIN_BASIN&quot;: &quot;South West Coast&quot;, &quot;MAIN_USE&quot;: &quot;Irrigation&quot;, &quot;MULTI_DAMS&quot;: null, &quot;NEAR_CITY&quot;: &quot;Catete&quot;, &quot;POLY_SRC&quot;: &quot;SWBD&quot;, &quot;QUALITY&quot;: &quot;3: Fair&quot;, &quot;REM_YEAR&quot;: -99, &quot;RES_NAME&quot;: null, &quot;RIVER&quot;: &quot;Bengo&quot;, &quot;SEC_ADMIN&quot;: null, &quot;SEC_CNTRY&quot;: null, &quot;SUB_BASIN&quot;: &quot;Bengo&quot;, &quot;TIMELINE&quot;: null, &quot;URL&quot;: null, &quot;USE_ELEC&quot;: null, &quot;USE_FCON&quot;: null, &quot;USE_FISH&quot;: null, &quot;USE_IRRI&quot;: &quot;Main&quot;, &quot;USE_LIVE&quot;: null, &quot;USE_NAVI&quot;: null, &quot;USE_OTHR&quot;: null, &quot;USE_PCON&quot;: null, &quot;USE_RECR&quot;: null, &quot;USE_SUPP&quot;: &quot;Sec&quot;, &quot;YEAR&quot;: 1975}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_45597d525ff0369e069ac0cbc5a15b85.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;RES_NAME&quot;];\n",
       "    let aliases = [&quot;Reservoir Name&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i].toLocaleString()}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v]).toLocaleString()}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
       "                     \n",
       "    \n",
       "        function geo_json_41b830e47db295b8e515fa752db6d0dc_highlighter(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;fillOpacity&quot;: 0.7};\n",
       "            }\n",
       "        }\n",
       "        function geo_json_41b830e47db295b8e515fa752db6d0dc_pointToLayer(feature, latlng) {\n",
       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;brown&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;brown&quot;, &quot;fillOpacity&quot;: 0.4, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 1};\n",
       "            \n",
       "            return new L.CircleMarker(latlng, opts)\n",
       "        }\n",
       "\n",
       "        function geo_json_41b830e47db295b8e515fa752db6d0dc_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "                mouseout: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        geo_json_41b830e47db295b8e515fa752db6d0dc.resetStyle(e.target);\n",
       "                    }\n",
       "                },\n",
       "                mouseover: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        const highlightStyle = geo_json_41b830e47db295b8e515fa752db6d0dc_highlighter(e.target.feature)\n",
       "                        e.target.setStyle(highlightStyle);\n",
       "                    }\n",
       "                },\n",
       "                click: function(e) {\n",
       "                    if (typeof e.target.getBounds === &#x27;function&#x27;) {\n",
       "                        map_eb4977ee5d2ea01a122d4197f30e63e6.fitBounds(e.target.getBounds());\n",
       "                    }\n",
       "                    else if (typeof e.target.getLatLng === &#x27;function&#x27;){\n",
       "                        let zoom = map_eb4977ee5d2ea01a122d4197f30e63e6.getZoom()\n",
       "                        zoom = zoom &gt; 12 ? zoom : zoom + 1\n",
       "                        map_eb4977ee5d2ea01a122d4197f30e63e6.flyTo(e.target.getLatLng(), zoom)\n",
       "                    }\n",
       "                }\n",
       "            });\n",
       "        };\n",
       "        var geo_json_41b830e47db295b8e515fa752db6d0dc = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_41b830e47db295b8e515fa752db6d0dc_onEachFeature,\n",
       "            \n",
       "                pointToLayer: geo_json_41b830e47db295b8e515fa752db6d0dc_pointToLayer\n",
       "        });\n",
       "\n",
       "        function geo_json_41b830e47db295b8e515fa752db6d0dc_add (data) {\n",
       "            geo_json_41b830e47db295b8e515fa752db6d0dc\n",
       "                .addData(data)\n",
       "                .addTo(map_eb4977ee5d2ea01a122d4197f30e63e6);\n",
       "        }\n",
       "            geo_json_41b830e47db295b8e515fa752db6d0dc_add({&quot;bbox&quot;: [13.787499864850005, -8.965386, 15.152801, -8.746884], &quot;features&quot;: [{&quot;bbox&quot;: [13.787499864850005, -8.962499804150006, 13.787499864850005, -8.962499804150006], &quot;geometry&quot;: {&quot;coordinates&quot;: [13.787499864850005, -8.962499804150006, 0.0], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;Count_ID&quot;: 1.0, &quot;DAM_ID&quot;: &quot;1002228&quot;, &quot;Latitud&quot;: -8.9625, &quot;Longitud&quot;: 13.7875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.152801, -8.746884, 15.152801, -8.746884], &quot;geometry&quot;: {&quot;coordinates&quot;: [15.152801, -8.746884, 0.0], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;Count_ID&quot;: 1.0, &quot;DAM_ID&quot;: &quot;1004076&quot;, &quot;Latitud&quot;: -8.746884, &quot;Longitud&quot;: 15.152801}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.790189, -8.965386, 13.790189, -8.965386], &quot;geometry&quot;: {&quot;coordinates&quot;: [13.790189, -8.965386, 0.0], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;2&quot;, &quot;properties&quot;: {&quot;Count_ID&quot;: 1.0, &quot;DAM_ID&quot;: &quot;1034935&quot;, &quot;Latitud&quot;: -8.965386, &quot;Longitud&quot;: 13.790189}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_41b830e47db295b8e515fa752db6d0dc.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;DAM_ID&quot;];\n",
       "    let aliases = [&quot;Dam ID&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i].toLocaleString()}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v]).toLocaleString()}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
       "                     \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2213e837b80>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a folium map centered on the AOI\n",
    "mymap = folium.Map(tiles=\"Cartodb Positron\", control_scale = True)\n",
    "bounds = cat.total_bounds.tolist()\n",
    "mymap.fit_bounds([bounds[:2][::-1], bounds[2:][::-1]])\n",
    "\n",
    "folium.GeoJson(\n",
    "    cat,\n",
    "    style_function=lambda feature: {\n",
    "        'fillColor': 'transparent',\n",
    "        'color': 'gray',\n",
    "        'weight': 3\n",
    "    },).add_to(mymap)\n",
    "\n",
    "res_tooltip = folium.GeoJsonTooltip(fields=['RES_NAME'], aliases=['Reservoir Name'], localize=True, style=('background-color: white; color: #333333;'))\n",
    "dam_tooltip = folium.GeoJsonTooltip(fields=['DAM_ID'], aliases=['Dam ID'], localize=True, style=('background-color: white; color: #333333;'))\n",
    "\n",
    "# Add blue polygons for reservoirs\n",
    "folium.GeoJson(\n",
    "    reservoirs,\n",
    "    style_function=lambda feature: {\n",
    "        'fillColor': 'blue',\n",
    "        'color': 'blue',\n",
    "        'weight': 1,\n",
    "    },\n",
    "    highlight_function=lambda x: {\"fillOpacity\": 0.7},\n",
    "    tooltip=res_tooltip,\n",
    "    zoom_on_click=True\n",
    ").add_to(mymap)\n",
    "\n",
    "# Add CircleMarkers for dams\n",
    "folium.GeoJson(\n",
    "    dams,\n",
    "    name=\"Dams\",\n",
    "    marker=folium.CircleMarker(radius=8, fill_color=\"brown\", fill_opacity=0.4, color=\"brown\", weight=1),\n",
    "    tooltip = dam_tooltip,\n",
    "    highlight_function=lambda x: {\"fillOpacity\": 0.7},\n",
    "    zoom_on_click=True,\n",
    ").add_to(mymap)\n",
    "\n",
    "# Add legend manually\n",
    "legend_html = '''\n",
    "     <div style=\"position: fixed; \n",
    "                 bottom: 50px; left: 50px; width: 150px; height: 70px; \n",
    "                 background-color: white; border:2px solid grey; z-index:9999; font-size:14px;\n",
    "                 \">&nbsp; <b>Legend</b> <br>\n",
    "                   &nbsp; Reservoirs &nbsp; \n",
    "                     <svg height=\"15\" width=\"15\">\n",
    "                       <rect width=\"15\" height=\"15\" style=\"fill:blue;stroke:blue;stroke-width:2;fill-opacity:0.5\" />\n",
    "                     </svg><br>\n",
    "                   &nbsp; Dams &nbsp; \n",
    "                     <svg height=\"10\" width=\"10\">\n",
    "                       <circle cx=\"5\" cy=\"5\" r=\"5\" style=\"fill:brown;stroke:brown;stroke-width:2;fill-opacity:0.5\" />\n",
    "                     </svg>\n",
    "     </div>\n",
    "     '''\n",
    "\n",
    "mymap.get_root().html.add_child(folium.Element(legend_html))\n",
    "\n",
    "mymap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c52d848-bab3-4e5d-900c-5f0f1814a133",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Precipitation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "31550515-a539-4f9d-813e-ea60d4c0c004",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(output_folder / 'precip.csv')\n",
    "df['time'] = pd.to_datetime(df['time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "f358cd3d-9df5-4964-ac3d-2d102976a00e",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "\n",
    "# Create the line chart using Seaborn with connected lines\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "sns.lineplot(data=df, x='time', y='precip', linewidth=1, color = '#2b8cbe')\n",
    "# sns.lineplot(data=df, x='time', y=df.precip.mean(), linewidth=1, color = 'grey')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('')\n",
    "plt.ylabel('')\n",
    "plt.title('Monthly precipitation 1993-2022 (mm)')\n",
    "\n",
    "# plt.xticks(rotation=45)\n",
    "plt.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0d0e0f6-41ec-4145-a616-bbfe50d2373b",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Runoff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "184db515-db17-4ceb-8035-180b3c878194",
   "metadata": {},
   "outputs": [],
   "source": [
    "var_list = {'ncrun': 'Net cell runoff', \n",
    "            'qs': 'Fast surface and fast subsurface runoff'}\n",
    "stat_list = {'mean': 'mean',\n",
    "             'std': 'standard deviation'}\n",
    "year_list = range(1987, 2017)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "9ea0973a-a65d-4dc0-b02b-77a84e0e67fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<folium.features.GeoJson at 0x2214805f640>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a folium map centered on the AOI\n",
    "mymap = folium.Map(tiles=\"Cartodb Positron\", control_scale = True)\n",
    "aoi_bounds = cat.total_bounds.tolist()\n",
    "mymap.fit_bounds([aoi_bounds[:2][::-1], aoi_bounds[2:][::-1]])\n",
    "\n",
    "folium.GeoJson(\n",
    "    cat,\n",
    "    style_function=lambda feature: {\n",
    "        'fillColor': 'transparent',\n",
    "        'color': 'gray',\n",
    "        'weight': 3\n",
    "    },\n",
    "    control = False).add_to(mymap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "7da59d87-2b93-44a2-8964-0ab5fa247443",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_ccf133a40e539bd6e38700a45d6d2351 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js&quot;&gt;&lt;/script&gt;\n",
       "    \n",
       "                    &lt;style&gt;\n",
       "                        .foliumtooltip {\n",
       "                            \n",
       "                        }\n",
       "                       .foliumtooltip table{\n",
       "                            margin: auto;\n",
       "                        }\n",
       "                        .foliumtooltip tr{\n",
       "                            text-align: left;\n",
       "                        }\n",
       "                        .foliumtooltip th{\n",
       "                            padding: 2px; padding-right: 8px;\n",
       "                        }\n",
       "                    &lt;/style&gt;\n",
       "            \n",
       "    \n",
       "                    &lt;style&gt;\n",
       "                        .foliumtooltip {\n",
       "                            \n",
       "                        }\n",
       "                       .foliumtooltip table{\n",
       "                            margin: auto;\n",
       "                        }\n",
       "                        .foliumtooltip tr{\n",
       "                            text-align: left;\n",
       "                        }\n",
       "                        .foliumtooltip th{\n",
       "                            padding: 2px; padding-right: 8px;\n",
       "                        }\n",
       "                    &lt;/style&gt;\n",
       "            \n",
       "    \n",
       "                    &lt;style&gt;\n",
       "                        .foliumtooltip {\n",
       "                            \n",
       "                        }\n",
       "                       .foliumtooltip table{\n",
       "                            margin: auto;\n",
       "                        }\n",
       "                        .foliumtooltip tr{\n",
       "                            text-align: left;\n",
       "                        }\n",
       "                        .foliumtooltip th{\n",
       "                            padding: 2px; padding-right: 8px;\n",
       "                        }\n",
       "                    &lt;/style&gt;\n",
       "            \n",
       "    \n",
       "                    &lt;style&gt;\n",
       "                        .foliumtooltip {\n",
       "                            \n",
       "                        }\n",
       "                       .foliumtooltip table{\n",
       "                            margin: auto;\n",
       "                        }\n",
       "                        .foliumtooltip tr{\n",
       "                            text-align: left;\n",
       "                        }\n",
       "                        .foliumtooltip th{\n",
       "                            padding: 2px; padding-right: 8px;\n",
       "                        }\n",
       "                    &lt;/style&gt;\n",
       "            \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_ccf133a40e539bd6e38700a45d6d2351&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_ccf133a40e539bd6e38700a45d6d2351 = L.map(\n",
       "                &quot;map_ccf133a40e539bd6e38700a45d6d2351&quot;,\n",
       "                {\n",
       "                    center: [0, 0],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 1,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "            L.control.scale().addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_56172963a9006926addb6b00ddf85085 = L.tileLayer(\n",
       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca target=\\&quot;_blank\\&quot; href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "        \n",
       "    \n",
       "            map_ccf133a40e539bd6e38700a45d6d2351.fitBounds(\n",
       "                [[-10.23750000012484, 12.991049194464779], [-8.462146674429448, 15.583333333466612]],\n",
       "                {}\n",
       "            );\n",
       "        \n",
       "    \n",
       "        function geo_json_bd1f5829eb75d149eb923ad5f2af1eab_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;color&quot;: &quot;gray&quot;, &quot;fillColor&quot;: &quot;transparent&quot;, &quot;weight&quot;: 3};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_bd1f5829eb75d149eb923ad5f2af1eab_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "            });\n",
       "        };\n",
       "        var geo_json_bd1f5829eb75d149eb923ad5f2af1eab = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_bd1f5829eb75d149eb923ad5f2af1eab_onEachFeature,\n",
       "            \n",
       "                style: geo_json_bd1f5829eb75d149eb923ad5f2af1eab_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_bd1f5829eb75d149eb923ad5f2af1eab_add (data) {\n",
       "            geo_json_bd1f5829eb75d149eb923ad5f2af1eab\n",
       "                .addData(data)\n",
       "                .addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "        }\n",
       "            geo_json_bd1f5829eb75d149eb923ad5f2af1eab_add({&quot;bbox&quot;: [12.991049194464779, -10.23750000012484, 15.583333333466612, -8.462146674429448], &quot;features&quot;: [{&quot;bbox&quot;: [12.991049194464779, -10.23750000012484, 15.583333333466612, -8.462146674429448], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[[13.19530368341833, -9.536416965070828], [13.203637017334529, -9.527248128598217], [13.204696316182094, -9.523916965095793], [13.196362983165216, -9.514748128623182], [13.19530368341833, -9.51025187182637], [13.19219631620706, -9.506414794706984], [13.191137017359495, -9.501918538809491], [13.18802964924896, -9.498081461690049], [13.186970350401396, -9.493585204893236], [13.179696316232082, -9.485581461715014], [13.179166666808271, -9.483333333766268], [13.179166666808271, -9.479166666808169], [13.175850762103039, -9.478315904555302], [13.174432712000112, -9.472789510327573], [13.171400621641453, -9.468877156355632], [13.170266045042013, 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[13.028583780517124, -9.003247070495888], [13.02500000014993, -9.004166666858168], [13.025617471968815, -8.99367302828756], [13.028549194389882, -8.989660305478651], [13.029784138926914, -8.985339694371362]], [[13.11751742918608, -8.905017429310874], [13.11581590468029, -8.911649237822019], [13.109156290930116, -8.913358222204124], [13.107766045166898, -8.919330511993508], [13.113350084139142, -8.921400620941881], [13.12021416595104, -8.915676201395513], [13.120833332991992, -8.904166667058007], [13.11751742918608, -8.905017429310874]], [[13.108744642451313, -8.927991739627032], [13.105381605177001, -8.92443271219986], [13.104166666958179, -8.929166667008019], [13.108744642451313, -8.927991739627032]]]], &quot;type&quot;: &quot;MultiPolygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;COAST&quot;: 1, &quot;DIST_MAIN&quot;: 0.0, &quot;DIST_SINK&quot;: 0.0, &quot;ENDO&quot;: 0, &quot;HYBAS_ID&quot;: 1060019280, &quot;MAIN_BAS&quot;: 1060019280, &quot;NEXT_DOWN&quot;: 0, &quot;NEXT_SINK&quot;: 1060019280, &quot;ORDER_&quot;: 0, &quot;PFAF_ID&quot;: 131700, &quot;SORT&quot;: 835, &quot;SUB_AREA&quot;: 3212.6, &quot;UP_AREA&quot;: 3212.6, &quot;aet_mm_s01&quot;: 50, &quot;aet_mm_s02&quot;: 48, &quot;aet_mm_s03&quot;: 71, &quot;aet_mm_s04&quot;: 90, &quot;aet_mm_s05&quot;: 80, &quot;aet_mm_s06&quot;: 56, &quot;aet_mm_s07&quot;: 42, &quot;aet_mm_s08&quot;: 35, &quot;aet_mm_s09&quot;: 30, &quot;aet_mm_s10&quot;: 27, &quot;aet_mm_s11&quot;: 37, &quot;aet_mm_s12&quot;: 48, &quot;aet_mm_syr&quot;: 615, &quot;aet_mm_uyr&quot;: 585, &quot;ari_ix_sav&quot;: 55, &quot;ari_ix_uav&quot;: 52, &quot;cls_cl_smj&quot;: 109, &quot;cly_pc_sav&quot;: 29, &quot;cly_pc_uav&quot;: 26, &quot;clz_cl_smj&quot;: 18, &quot;cmi_ix_s01&quot;: -61, &quot;cmi_ix_s02&quot;: -40, &quot;cmi_ix_s03&quot;: 27, &quot;cmi_ix_s04&quot;: 47, &quot;cmi_ix_s05&quot;: -81, &quot;cmi_ix_s06&quot;: -100, &quot;cmi_ix_s07&quot;: -100, &quot;cmi_ix_s08&quot;: -100, &quot;cmi_ix_s09&quot;: -98, &quot;cmi_ix_s10&quot;: -82, &quot;cmi_ix_s11&quot;: -12, &quot;cmi_ix_s12&quot;: -50, &quot;cmi_ix_syr&quot;: -45, &quot;cmi_ix_uyr&quot;: -48, &quot;crp_pc_sse&quot;: 2, &quot;crp_pc_use&quot;: 2, &quot;dis_m3_pmn&quot;: 0.033, &quot;dis_m3_pmx&quot;: 1.088, &quot;dis_m3_pyr&quot;: 0.268, &quot;dor_pc_pva&quot;: 0, &quot;ele_mt_sav&quot;: 146, &quot;ele_mt_smn&quot;: 0, &quot;ele_mt_smx&quot;: 285, &quot;ele_mt_uav&quot;: 57, &quot;ero_kh_sav&quot;: 4561, &quot;ero_kh_uav&quot;: 10810, &quot;fec_cl_smj&quot;: 551, &quot;fmh_cl_smj&quot;: 8, &quot;for_pc_sse&quot;: 16, &quot;for_pc_use&quot;: 0, &quot;gad_id_smj&quot;: 7, &quot;gdp_ud_sav&quot;: 6937, &quot;gdp_ud_ssu&quot;: 106154880, &quot;gdp_ud_usu&quot;: 3380229, &quot;gla_pc_sse&quot;: 0, &quot;gla_pc_use&quot;: 0, &quot;glc_cl_smj&quot;: 13, &quot;glc_pc_s01&quot;: 1, &quot;glc_pc_s02&quot;: 2, &quot;glc_pc_s03&quot;: 13, &quot;glc_pc_s04&quot;: 0, &quot;glc_pc_s05&quot;: 0, &quot;glc_pc_s06&quot;: 0, &quot;glc_pc_s07&quot;: 0, &quot;glc_pc_s08&quot;: 0, &quot;glc_pc_s09&quot;: 0, &quot;glc_pc_s10&quot;: 0, &quot;glc_pc_s11&quot;: 0, &quot;glc_pc_s12&quot;: 38, &quot;glc_pc_s13&quot;: 41, &quot;glc_pc_s14&quot;: 0, &quot;glc_pc_s15&quot;: 0, &quot;glc_pc_s16&quot;: 0, &quot;glc_pc_s17&quot;: 0, &quot;glc_pc_s18&quot;: 0, &quot;glc_pc_s19&quot;: 2, &quot;glc_pc_s20&quot;: 2, &quot;glc_pc_s21&quot;: 0, &quot;glc_pc_s22&quot;: 0, &quot;glc_pc_u01&quot;: 0, &quot;glc_pc_u02&quot;: 0, &quot;glc_pc_u03&quot;: 0, &quot;glc_pc_u04&quot;: 0, &quot;glc_pc_u05&quot;: 0, &quot;glc_pc_u06&quot;: 0, &quot;glc_pc_u07&quot;: 0, &quot;glc_pc_u08&quot;: 0, &quot;glc_pc_u09&quot;: 0, &quot;glc_pc_u10&quot;: 0, &quot;glc_pc_u11&quot;: 0, &quot;glc_pc_u12&quot;: 12, &quot;glc_pc_u13&quot;: 74, &quot;glc_pc_u14&quot;: 0, &quot;glc_pc_u15&quot;: 0, &quot;glc_pc_u16&quot;: 0, &quot;glc_pc_u17&quot;: 0, &quot;glc_pc_u18&quot;: 0, &quot;glc_pc_u19&quot;: 14, &quot;glc_pc_u20&quot;: 0, &quot;glc_pc_u21&quot;: 0, &quot;glc_pc_u22&quot;: 0, &quot;gwt_cm_sav&quot;: 317, &quot;hdi_ix_sav&quot;: 533, &quot;hft_ix_s09&quot;: 56, &quot;hft_ix_s93&quot;: 52, &quot;hft_ix_u09&quot;: 76, &quot;hft_ix_u93&quot;: 67, &quot;inu_pc_slt&quot;: 7, &quot;inu_pc_smn&quot;: 1, &quot;inu_pc_smx&quot;: 5, &quot;inu_pc_ult&quot;: 97, &quot;inu_pc_umn&quot;: 14, &quot;inu_pc_umx&quot;: 83, &quot;ire_pc_sse&quot;: 0, &quot;ire_pc_use&quot;: 0, &quot;kar_pc_sse&quot;: 0, &quot;kar_pc_use&quot;: 0, &quot;lit_cl_smj&quot;: 3, &quot;lka_pc_sse&quot;: 0, &quot;lka_pc_use&quot;: 0, &quot;lkv_mc_usu&quot;: 0, &quot;nli_ix_sav&quot;: 25, &quot;nli_ix_uav&quot;: 0, &quot;pac_pc_sse&quot;: 98, &quot;pac_pc_use&quot;: 64, &quot;pet_mm_s01&quot;: 130, &quot;pet_mm_s02&quot;: 121, &quot;pet_mm_s03&quot;: 129, &quot;pet_mm_s04&quot;: 113, &quot;pet_mm_s05&quot;: 101, &quot;pet_mm_s06&quot;: 90, &quot;pet_mm_s07&quot;: 86, &quot;pet_mm_s08&quot;: 94, &quot;pet_mm_s09&quot;: 104, &quot;pet_mm_s10&quot;: 117, &quot;pet_mm_s11&quot;: 119, &quot;pet_mm_s12&quot;: 125, &quot;pet_mm_syr&quot;: 1330, &quot;pet_mm_uyr&quot;: 1334, &quot;pnv_cl_smj&quot;: 12, &quot;pnv_pc_s01&quot;: 0, &quot;pnv_pc_s02&quot;: 0, &quot;pnv_pc_s03&quot;: 0, &quot;pnv_pc_s04&quot;: 0, &quot;pnv_pc_s05&quot;: 0, &quot;pnv_pc_s06&quot;: 0, &quot;pnv_pc_s07&quot;: 0, &quot;pnv_pc_s08&quot;: 0, &quot;pnv_pc_s09&quot;: 37, &quot;pnv_pc_s10&quot;: 12, &quot;pnv_pc_s11&quot;: 0, &quot;pnv_pc_s12&quot;: 51, &quot;pnv_pc_s13&quot;: 0, &quot;pnv_pc_s14&quot;: 0, &quot;pnv_pc_s15&quot;: 0, &quot;pnv_pc_u01&quot;: 0, &quot;pnv_pc_u02&quot;: 0, &quot;pnv_pc_u03&quot;: 0, &quot;pnv_pc_u04&quot;: 0, &quot;pnv_pc_u05&quot;: 0, &quot;pnv_pc_u06&quot;: 0, &quot;pnv_pc_u07&quot;: 0, &quot;pnv_pc_u08&quot;: 0, &quot;pnv_pc_u09&quot;: 24, &quot;pnv_pc_u10&quot;: 0, &quot;pnv_pc_u11&quot;: 0, &quot;pnv_pc_u12&quot;: 76, &quot;pnv_pc_u13&quot;: 0, &quot;pnv_pc_u14&quot;: 0, &quot;pnv_pc_u15&quot;: 0, &quot;pop_ct_ssu&quot;: 3.08, &quot;pop_ct_usu&quot;: 0.035, &quot;ppd_pk_sav&quot;: 0.989, &quot;ppd_pk_uav&quot;: 0.995, &quot;pre_mm_s01&quot;: 51, &quot;pre_mm_s02&quot;: 73, &quot;pre_mm_s03&quot;: 177, &quot;pre_mm_s04&quot;: 215, &quot;pre_mm_s05&quot;: 19, &quot;pre_mm_s06&quot;: 0, &quot;pre_mm_s07&quot;: 0, &quot;pre_mm_s08&quot;: 0, &quot;pre_mm_s09&quot;: 2, &quot;pre_mm_s10&quot;: 22, &quot;pre_mm_s11&quot;: 106, &quot;pre_mm_s12&quot;: 63, &quot;pre_mm_syr&quot;: 727, &quot;pre_mm_uyr&quot;: 691, &quot;prm_pc_sse&quot;: 0, &quot;prm_pc_use&quot;: 0, &quot;pst_pc_sse&quot;: 38, &quot;pst_pc_use&quot;: 32, &quot;rdd_mk_sav&quot;: 95, &quot;rdd_mk_uav&quot;: 0, &quot;rev_mc_usu&quot;: 0, &quot;ria_ha_ssu&quot;: 489.438, &quot;ria_ha_usu&quot;: 1.884, &quot;riv_tc_ssu&quot;: 2095.88, &quot;riv_tc_usu&quot;: 1.831, &quot;run_mm_syr&quot;: 189, &quot;sgr_dk_sav&quot;: 47, &quot;slp_dg_sav&quot;: 15, &quot;slp_dg_uav&quot;: 49, &quot;slt_pc_sav&quot;: 22, &quot;slt_pc_uav&quot;: 24, &quot;snd_pc_sav&quot;: 49, &quot;snd_pc_uav&quot;: 49, &quot;snw_pc_s01&quot;: 0, &quot;snw_pc_s02&quot;: 0, &quot;snw_pc_s03&quot;: 0, &quot;snw_pc_s04&quot;: 0, &quot;snw_pc_s05&quot;: 0, &quot;snw_pc_s06&quot;: 0, &quot;snw_pc_s07&quot;: 0, &quot;snw_pc_s08&quot;: 0, &quot;snw_pc_s09&quot;: 0, &quot;snw_pc_s10&quot;: 0, &quot;snw_pc_s11&quot;: 0, &quot;snw_pc_s12&quot;: 0, &quot;snw_pc_smx&quot;: 0, &quot;snw_pc_syr&quot;: 0, &quot;snw_pc_uyr&quot;: 0, &quot;soc_th_sav&quot;: 23, &quot;soc_th_uav&quot;: 29, &quot;swc_pc_s01&quot;: 38, &quot;swc_pc_s02&quot;: 39, &quot;swc_pc_s03&quot;: 52, &quot;swc_pc_s04&quot;: 77, &quot;swc_pc_s05&quot;: 81, &quot;swc_pc_s06&quot;: 63, &quot;swc_pc_s07&quot;: 49, &quot;swc_pc_s08&quot;: 38, &quot;swc_pc_s09&quot;: 29, &quot;swc_pc_s10&quot;: 24, &quot;swc_pc_s11&quot;: 30, &quot;swc_pc_s12&quot;: 38, &quot;swc_pc_syr&quot;: 47, &quot;swc_pc_uyr&quot;: 44, &quot;tbi_cl_smj&quot;: 7, &quot;tec_cl_smj&quot;: 35, &quot;tmp_dc_s01&quot;: 258, &quot;tmp_dc_s02&quot;: 262, &quot;tmp_dc_s03&quot;: 265, &quot;tmp_dc_s04&quot;: 263, &quot;tmp_dc_s05&quot;: 249, &quot;tmp_dc_s06&quot;: 220, &quot;tmp_dc_s07&quot;: 204, &quot;tmp_dc_s08&quot;: 204, &quot;tmp_dc_s09&quot;: 220, &quot;tmp_dc_s10&quot;: 241, &quot;tmp_dc_s11&quot;: 253, &quot;tmp_dc_s12&quot;: 255, &quot;tmp_dc_smn&quot;: 204, &quot;tmp_dc_smx&quot;: 265, &quot;tmp_dc_syr&quot;: 241, &quot;tmp_dc_uyr&quot;: 241, &quot;urb_pc_sse&quot;: 0, &quot;urb_pc_use&quot;: 0, &quot;wet_cl_smj&quot;: 4, &quot;wet_pc_s01&quot;: 0, &quot;wet_pc_s02&quot;: 0, &quot;wet_pc_s03&quot;: 0, &quot;wet_pc_s04&quot;: 1, &quot;wet_pc_s05&quot;: 0, &quot;wet_pc_s06&quot;: 0, &quot;wet_pc_s07&quot;: 0, &quot;wet_pc_s08&quot;: 0, &quot;wet_pc_s09&quot;: 0, &quot;wet_pc_sg1&quot;: 1, &quot;wet_pc_sg2&quot;: 1, &quot;wet_pc_u01&quot;: 0, &quot;wet_pc_u02&quot;: 0, &quot;wet_pc_u03&quot;: 0, &quot;wet_pc_u04&quot;: 2, &quot;wet_pc_u05&quot;: 0, &quot;wet_pc_u06&quot;: 0, &quot;wet_pc_u07&quot;: 0, &quot;wet_pc_u08&quot;: 0, &quot;wet_pc_u09&quot;: 0, &quot;wet_pc_ug1&quot;: 2, &quot;wet_pc_ug2&quot;: 2}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    var color_map_4dedba92cb442866ab7408d337b17515 = {};\n",
       "\n",
       "    \n",
       "    color_map_4dedba92cb442866ab7408d337b17515.color = d3.scale.threshold()\n",
       "              .domain([1.2756456726492615e-06, 1.2974377831212363e-06, 1.3192298935932112e-06, 1.341022004065186e-06, 1.3628141145371608e-06, 1.3846062250091355e-06, 1.4063983354811103e-06, 1.4281904459530852e-06, 1.44998255642506e-06, 1.4717746668970348e-06, 1.4935667773690095e-06, 1.5153588878409843e-06, 1.5371509983129592e-06, 1.558943108784934e-06, 1.5807352192569088e-06, 1.6025273297288835e-06, 1.6243194402008583e-06, 1.6461115506728332e-06, 1.6679036611448081e-06, 1.6896957716167828e-06, 1.7114878820887575e-06, 1.7332799925607325e-06, 1.7550721030327072e-06, 1.7768642135046821e-06, 1.7986563239766568e-06, 1.8204484344486315e-06, 1.8422405449206063e-06, 1.8640326553925812e-06, 1.8858247658645561e-06, 1.907616876336531e-06, 1.9294089868085055e-06, 1.9512010972804807e-06, 1.972993207752455e-06, 1.99478531822443e-06, 2.016577428696405e-06, 2.0383695391683795e-06, 2.0601616496403547e-06, 2.0819537601123294e-06, 2.103745870584304e-06, 2.125537981056279e-06, 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       "    \n",
       "\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.x = d3.scale.linear()\n",
       "              .domain([1.2756456726492615e-06, 1.2149908798164688e-05])\n",
       "              .range([0, 450 - 50]);\n",
       "\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.legend = L.control({position: &#x27;topright&#x27;});\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.legend.onAdd = function (map) {var div = L.DomUtil.create(&#x27;div&#x27;, &#x27;legend&#x27;); return div};\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.legend.addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.xAxis = d3.svg.axis()\n",
       "        .scale(color_map_4dedba92cb442866ab7408d337b17515.x)\n",
       "        .orient(&quot;top&quot;)\n",
       "        .tickSize(1)\n",
       "        .tickValues([1.2756456726492615e-06, 2.63492856333869e-06, 3.994211454028118e-06, 5.3534943447175465e-06, 6.712777235406975e-06, 8.072060126096403e-06, 9.431343016785831e-06, 1.079062590747526e-05, 1.2149908798164688e-05]);\n",
       "\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.svg = d3.select(&quot;.legend.leaflet-control&quot;).append(&quot;svg&quot;)\n",
       "        .attr(&quot;id&quot;, &#x27;legend&#x27;)\n",
       "        .attr(&quot;width&quot;, 450)\n",
       "        .attr(&quot;height&quot;, 40);\n",
       "\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.g = color_map_4dedba92cb442866ab7408d337b17515.svg.append(&quot;g&quot;)\n",
       "        .attr(&quot;class&quot;, &quot;key&quot;)\n",
       "        .attr(&quot;transform&quot;, &quot;translate(25,16)&quot;);\n",
       "\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.g.selectAll(&quot;rect&quot;)\n",
       "        .data(color_map_4dedba92cb442866ab7408d337b17515.color.range().map(function(d, i) {\n",
       "          return {\n",
       "            x0: i ? color_map_4dedba92cb442866ab7408d337b17515.x(color_map_4dedba92cb442866ab7408d337b17515.color.domain()[i - 1]) : color_map_4dedba92cb442866ab7408d337b17515.x.range()[0],\n",
       "            x1: i &lt; color_map_4dedba92cb442866ab7408d337b17515.color.domain().length ? color_map_4dedba92cb442866ab7408d337b17515.x(color_map_4dedba92cb442866ab7408d337b17515.color.domain()[i]) : color_map_4dedba92cb442866ab7408d337b17515.x.range()[1],\n",
       "            z: d\n",
       "          };\n",
       "        }))\n",
       "      .enter().append(&quot;rect&quot;)\n",
       "        .attr(&quot;height&quot;, 40 - 30)\n",
       "        .attr(&quot;x&quot;, function(d) { return d.x0; })\n",
       "        .attr(&quot;width&quot;, function(d) { return d.x1 - d.x0; })\n",
       "        .style(&quot;fill&quot;, function(d) { return d.z; });\n",
       "\n",
       "    color_map_4dedba92cb442866ab7408d337b17515.g.call(color_map_4dedba92cb442866ab7408d337b17515.xAxis).append(&quot;text&quot;)\n",
       "        .attr(&quot;class&quot;, &quot;caption&quot;)\n",
       "        .attr(&quot;y&quot;, 21)\n",
       "        .text(&quot;Net cell runoff (mean / standard deviation)&quot;);\n",
       "    \n",
       "        function geo_json_c0a0837a8a4f28a3995b24f20f456c11_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                case &quot;1&quot;: case &quot;3&quot;: case &quot;18&quot;: case &quot;21&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;transparent&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;2&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#33a8c3ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;7&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#d8f0b3ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;8&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#b7e3b6ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;9&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#d0edb3ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;13&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#c6e9b4ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;14&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#d7f0b3ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;16&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#feffd7ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                default:\n",
       "                    return {&quot;fillColor&quot;: &quot;#ffffd9ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "            }\n",
       "        }\n",
       "        function geo_json_c0a0837a8a4f28a3995b24f20f456c11_highlighter(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;fillOpacity&quot;: 0.9};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_c0a0837a8a4f28a3995b24f20f456c11_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "                mouseout: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        geo_json_c0a0837a8a4f28a3995b24f20f456c11.resetStyle(e.target);\n",
       "                    }\n",
       "                },\n",
       "                mouseover: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        const highlightStyle = geo_json_c0a0837a8a4f28a3995b24f20f456c11_highlighter(e.target.feature)\n",
       "                        e.target.setStyle(highlightStyle);\n",
       "                    }\n",
       "                },\n",
       "            });\n",
       "        };\n",
       "        var geo_json_c0a0837a8a4f28a3995b24f20f456c11 = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_c0a0837a8a4f28a3995b24f20f456c11_onEachFeature,\n",
       "            \n",
       "                style: geo_json_c0a0837a8a4f28a3995b24f20f456c11_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_c0a0837a8a4f28a3995b24f20f456c11_add (data) {\n",
       "            geo_json_c0a0837a8a4f28a3995b24f20f456c11\n",
       "                .addData(data)\n",
       "                .addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "        }\n",
       "            geo_json_c0a0837a8a4f28a3995b24f20f456c11_add({&quot;bbox&quot;: [12.5, -10.5, 16.0, -8.0], &quot;features&quot;: [{&quot;bbox&quot;: [13.0, -8.5, 13.5, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -8.0], [13.0, -8.5], [13.5, -8.5], [13.5, -8.0], [13.0, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.707794237721828e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -8.5, 15.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.0], [13.5, -8.5], [15.0, -8.5], [15.0, -8.0], [13.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -8.5, 15.5, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -8.0], [15.0, -8.5], [15.5, -8.5], [15.5, -8.0], [15.0, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;2&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.662266004132107e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.5, -8.5, 16.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -8.0], [15.5, -8.5], [16.0, -8.5], [16.0, -8.0], [15.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;3&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -9.0, 13.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -8.5], [13.0, -9.0], [13.5, -9.0], [13.5, -8.5], [13.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;4&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: -3.2510351957171224e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -9.0, 14.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.5], [13.5, -9.0], [14.0, -9.0], [14.0, -8.5], [13.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;5&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: -3.1696838505013147e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -9.0, 14.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -8.5], [14.0, -9.0], [14.5, -9.0], [14.5, -8.5], [14.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;6&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: -3.501641856473725e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.5, -9.0, 15.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.5, -8.5], [14.5, -9.0], [15.0, -9.0], [15.0, -8.5], [14.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;7&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 7.207932412711671e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -9.0, 15.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -8.5], [15.0, -9.0], [15.5, -9.0], [15.5, -8.5], [15.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;8&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 9.471707016928121e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.5, -9.0, 16.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -8.5], [15.5, -9.0], [16.0, -9.0], [16.0, -8.5], [15.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;9&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 7.903663572506048e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -9.5, 13.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -9.0], [13.0, -9.5], [13.5, -9.5], [13.5, -9.0], [13.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;10&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: -4.555629857350141e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -9.5, 14.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -9.0], [13.5, -9.5], [14.0, -9.5], [14.0, -9.0], [13.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;11&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: -1.4866123819956556e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -9.5, 14.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -9.0], [14.0, -9.5], [14.5, -9.5], [14.5, -9.0], [14.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;12&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.9399190023250412e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.5, -9.5, 15.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.5, -9.0], [14.5, -9.5], [15.0, -9.5], [15.0, -9.0], [14.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;13&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 8.772197361395229e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -9.5, 15.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -9.0], [15.0, -9.5], [15.5, -9.5], [15.5, -9.0], [15.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;14&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 7.335547252296237e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -10.0, 13.5, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -9.5], [13.0, -10.0], [13.5, -10.0], [13.5, -9.5], [13.0, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;15&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.1358614503697027e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -10.0, 14.0, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -9.5], [13.5, -10.0], [14.0, -10.0], [14.0, -9.5], [13.5, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;16&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.3045427042234223e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -10.0, 14.5, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -9.5], [14.0, -10.0], [14.5, -10.0], [14.5, -9.5], [14.0, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;17&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: -1.2124305612815078e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [12.5, -10.5, 13.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[12.5, -8.0], [12.5, -10.5], [13.0, -10.5], [13.0, -8.0], [12.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;18&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -10.5, 13.5, -10.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -10.0], [13.0, -10.5], [13.5, -10.5], [13.5, -10.0], [13.0, -10.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;19&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.0672588359739166e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -10.5, 14.0, -10.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -10.0], [13.5, -10.5], [14.0, -10.5], [14.0, -10.0], [13.5, -10.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;20&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: -6.204988494573627e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -10.5, 16.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -9.0], [15.5, -9.5], [14.5, -9.5], [14.5, -10.0], [14.0, -10.0], [14.0, -10.5], [16.0, -10.5], [16.0, -9.0], [15.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;21&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_c0a0837a8a4f28a3995b24f20f456c11.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;raster_val&quot;];\n",
       "    let aliases = [&quot;Net cell runoff (mean)&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: false});\n",
       "                     \n",
       "    \n",
       "        function geo_json_14e46c5d49de9127bcb093767728ec4b_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                case &quot;0&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#edf8b1ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;2&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#50bcc2ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;4&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffffd9ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;5&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ebf7b1ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;6&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#3eb3c4ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;7&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#b3e1b6ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;8&quot;: case &quot;13&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#a0dab8ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;9&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#c9eab4ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;10&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#1f7db7ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;11&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#79cbbcff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;12&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f9fdcbff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;14&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#c0e7b5ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;15&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#e8f6b2ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;16&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fafdcdff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;17&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#081d58ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;19&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#e7f6b2ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;20&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#234b9fff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                default:\n",
       "                    return {&quot;fillColor&quot;: &quot;transparent&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "            }\n",
       "        }\n",
       "        function geo_json_14e46c5d49de9127bcb093767728ec4b_highlighter(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;fillOpacity&quot;: 0.9};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_14e46c5d49de9127bcb093767728ec4b_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "                mouseout: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        geo_json_14e46c5d49de9127bcb093767728ec4b.resetStyle(e.target);\n",
       "                    }\n",
       "                },\n",
       "                mouseover: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        const highlightStyle = geo_json_14e46c5d49de9127bcb093767728ec4b_highlighter(e.target.feature)\n",
       "                        e.target.setStyle(highlightStyle);\n",
       "                    }\n",
       "                },\n",
       "            });\n",
       "        };\n",
       "        var geo_json_14e46c5d49de9127bcb093767728ec4b = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_14e46c5d49de9127bcb093767728ec4b_onEachFeature,\n",
       "            \n",
       "                style: geo_json_14e46c5d49de9127bcb093767728ec4b_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_14e46c5d49de9127bcb093767728ec4b_add (data) {\n",
       "            geo_json_14e46c5d49de9127bcb093767728ec4b\n",
       "                .addData(data)\n",
       "                .addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "        }\n",
       "            geo_json_14e46c5d49de9127bcb093767728ec4b_add({&quot;bbox&quot;: [12.5, -10.5, 16.0, -8.0], &quot;features&quot;: [{&quot;bbox&quot;: [13.0, -8.5, 13.5, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -8.0], [13.0, -8.5], [13.5, -8.5], [13.5, -8.0], [13.0, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 5.384423275245354e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -8.5, 15.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.0], [13.5, -8.5], [15.0, -8.5], [15.0, -8.0], [13.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -8.5, 15.5, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -8.0], [15.0, -8.5], [15.5, -8.5], [15.5, -8.0], [15.0, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;2&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.45390122270328e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.5, -8.5, 16.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -8.0], [15.5, -8.5], [16.0, -8.5], [16.0, -8.0], [15.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;3&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -9.0, 13.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -8.5], [13.0, -9.0], [13.5, -9.0], [13.5, -8.5], [13.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;4&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.069489937639446e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -9.0, 14.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.5], [13.5, -9.0], [14.0, -9.0], [14.0, -8.5], [13.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;5&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 5.621960553980898e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -9.0, 14.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -8.5], [14.0, -9.0], [14.5, -9.0], [14.5, -8.5], [14.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;6&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.5631097994628362e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.5, -9.0, 15.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.5, -8.5], [14.5, -9.0], [15.0, -9.0], [15.0, -8.5], [14.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;7&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 9.643708835938014e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -9.0, 15.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -8.5], [15.0, -9.0], [15.5, -9.0], [15.5, -8.5], [15.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;8&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.049412094289437e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.5, -9.0, 16.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -8.5], [15.5, -9.0], [16.0, -9.0], [16.0, -8.5], [15.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;9&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 8.577242624596693e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -9.5, 13.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -9.0], [13.0, -9.5], [13.5, -9.5], [13.5, -9.0], [13.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;10&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.9941047867177986e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -9.5, 14.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -9.0], [13.5, -9.5], [14.0, -9.5], [14.0, -9.0], [13.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;11&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.2334831808402669e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -9.5, 14.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -9.0], [14.0, -9.5], [14.5, -9.5], [14.5, -9.0], [14.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;12&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 3.2863822525541764e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.5, -9.5, 15.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.5, -9.0], [14.5, -9.5], [15.0, -9.5], [15.0, -9.0], [14.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;13&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.051554409059463e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -9.5, 15.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -9.0], [15.0, -9.5], [15.5, -9.5], [15.5, -9.0], [15.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;14&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 9.033362402988132e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -10.0, 13.5, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -9.5], [13.0, -10.0], [13.5, -10.0], [13.5, -9.5], [13.0, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;15&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 5.8449072639632504e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -10.0, 14.0, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -9.5], [13.5, -10.0], [14.0, -10.0], [14.0, -9.5], [13.5, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;16&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 3.06910715153208e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -10.0, 14.5, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -9.5], [14.0, -10.0], [14.5, -10.0], [14.5, -9.5], [14.0, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;17&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.8604605176951736e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [12.5, -10.5, 13.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[12.5, -8.0], [12.5, -10.5], [13.0, -10.5], [13.0, -8.0], [12.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;18&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -10.5, 13.5, -10.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -10.0], [13.0, -10.5], [13.5, -10.5], [13.5, -10.0], [13.0, -10.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;19&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 5.984771632938646e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -10.5, 14.0, -10.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -10.0], [13.5, -10.5], [14.0, -10.5], [14.0, -10.0], [13.5, -10.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;20&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.346966903132852e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -10.5, 16.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -9.0], [15.5, -9.5], [14.5, -9.5], [14.5, -10.0], [14.0, -10.0], [14.0, -10.5], [16.0, -10.5], [16.0, -9.0], [15.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;21&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_14e46c5d49de9127bcb093767728ec4b.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;raster_val&quot;];\n",
       "    let aliases = [&quot;Net cell runoff (standard deviation)&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: false});\n",
       "                     \n",
       "    \n",
       "    var color_map_38589045ce5e7dba5182803196eef109 = {};\n",
       "\n",
       "    \n",
       "    color_map_38589045ce5e7dba5182803196eef109.color = d3.scale.threshold()\n",
       "              .domain([2.069489937639446e-06, 2.1226665212853625e-06, 2.175843104931279e-06, 2.2290196885771954e-06, 2.282196272223112e-06, 2.335372855869028e-06, 2.3885494395149443e-06, 2.4417260231608608e-06, 2.4949026068067772e-06, 2.5480791904526937e-06, 2.60125577409861e-06, 2.6544323577445266e-06, 2.707608941390443e-06, 2.7607855250363595e-06, 2.8139621086822756e-06, 2.8671386923281924e-06, 2.9203152759741085e-06, 2.973491859620025e-06, 3.0266684432659414e-06, 3.079845026911858e-06, 3.1330216105577743e-06, 3.1861981942036908e-06, 3.2393747778496072e-06, 3.2925513614955233e-06, 3.34572794514144e-06, 3.398904528787356e-06, 3.4520811124332726e-06, 3.505257696079189e-06, 3.5584342797251056e-06, 3.611610863371022e-06, 3.6647874470169385e-06, 3.717964030662855e-06, 3.771140614308771e-06, 3.824317197954688e-06, 3.877493781600604e-06, 3.930670365246521e-06, 3.983846948892437e-06, 4.037023532538354e-06, 4.09020011618427e-06, 4.143376699830186e-06, 4.196553283476103e-06, 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8.82291606067083e-06, 8.876092644316746e-06, 8.929269227962663e-06, 8.98244581160858e-06, 9.035622395254497e-06, 9.088798978900413e-06, 9.141975562546329e-06, 9.195152146192245e-06, 9.24832872983816e-06, 9.301505313484078e-06, 9.354681897129994e-06, 9.407858480775911e-06, 9.461035064421828e-06, 9.514211648067745e-06, 9.56738823171366e-06, 9.620564815359575e-06, 9.673741399005492e-06, 9.72691798265141e-06, 9.780094566297326e-06, 9.833271149943243e-06, 9.886447733589158e-06, 9.939624317235075e-06, 9.992800900880992e-06, 1.0045977484526909e-05, 1.0099154068172824e-05, 1.0152330651818741e-05, 1.0205507235464658e-05, 1.0258683819110573e-05, 1.031186040275649e-05, 1.0365036986402407e-05, 1.0418213570048324e-05, 1.0471390153694239e-05, 1.0524566737340156e-05, 1.0577743320986073e-05, 1.0630919904631988e-05, 1.0684096488277905e-05, 1.0737273071923821e-05, 1.0790449655569738e-05, 1.0843626239215654e-05, 1.089680282286157e-05, 1.0949979406507487e-05, 1.1003155990153404e-05, 1.105633257379932e-05, 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       "    \n",
       "\n",
       "    color_map_38589045ce5e7dba5182803196eef109.x = d3.scale.linear()\n",
       "              .domain([2.069489937639446e-06, 2.8604605176951736e-05])\n",
       "              .range([0, 450 - 50]);\n",
       "\n",
       "    color_map_38589045ce5e7dba5182803196eef109.legend = L.control({position: &#x27;topright&#x27;});\n",
       "    color_map_38589045ce5e7dba5182803196eef109.legend.onAdd = function (map) {var div = L.DomUtil.create(&#x27;div&#x27;, &#x27;legend&#x27;); return div};\n",
       "    color_map_38589045ce5e7dba5182803196eef109.legend.addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "\n",
       "    color_map_38589045ce5e7dba5182803196eef109.xAxis = d3.svg.axis()\n",
       "        .scale(color_map_38589045ce5e7dba5182803196eef109.x)\n",
       "        .orient(&quot;top&quot;)\n",
       "        .tickSize(1)\n",
       "        .tickValues([2.069489937639446e-06, 5.386379342553482e-06, 8.703268747467519e-06, 1.2020158152381555e-05, 1.533704755729559e-05, 1.8653936962209627e-05, 2.1970826367123664e-05, 2.52877157720377e-05, 2.8604605176951736e-05]);\n",
       "\n",
       "    color_map_38589045ce5e7dba5182803196eef109.svg = d3.select(&quot;.legend.leaflet-control&quot;).append(&quot;svg&quot;)\n",
       "        .attr(&quot;id&quot;, &#x27;legend&#x27;)\n",
       "        .attr(&quot;width&quot;, 450)\n",
       "        .attr(&quot;height&quot;, 40);\n",
       "\n",
       "    color_map_38589045ce5e7dba5182803196eef109.g = color_map_38589045ce5e7dba5182803196eef109.svg.append(&quot;g&quot;)\n",
       "        .attr(&quot;class&quot;, &quot;key&quot;)\n",
       "        .attr(&quot;transform&quot;, &quot;translate(25,16)&quot;);\n",
       "\n",
       "    color_map_38589045ce5e7dba5182803196eef109.g.selectAll(&quot;rect&quot;)\n",
       "        .data(color_map_38589045ce5e7dba5182803196eef109.color.range().map(function(d, i) {\n",
       "          return {\n",
       "            x0: i ? color_map_38589045ce5e7dba5182803196eef109.x(color_map_38589045ce5e7dba5182803196eef109.color.domain()[i - 1]) : color_map_38589045ce5e7dba5182803196eef109.x.range()[0],\n",
       "            x1: i &lt; color_map_38589045ce5e7dba5182803196eef109.color.domain().length ? color_map_38589045ce5e7dba5182803196eef109.x(color_map_38589045ce5e7dba5182803196eef109.color.domain()[i]) : color_map_38589045ce5e7dba5182803196eef109.x.range()[1],\n",
       "            z: d\n",
       "          };\n",
       "        }))\n",
       "      .enter().append(&quot;rect&quot;)\n",
       "        .attr(&quot;height&quot;, 40 - 30)\n",
       "        .attr(&quot;x&quot;, function(d) { return d.x0; })\n",
       "        .attr(&quot;width&quot;, function(d) { return d.x1 - d.x0; })\n",
       "        .style(&quot;fill&quot;, function(d) { return d.z; });\n",
       "\n",
       "    color_map_38589045ce5e7dba5182803196eef109.g.call(color_map_38589045ce5e7dba5182803196eef109.xAxis).append(&quot;text&quot;)\n",
       "        .attr(&quot;class&quot;, &quot;caption&quot;)\n",
       "        .attr(&quot;y&quot;, 21)\n",
       "        .text(&quot;Fast surface and fast subsurface runoff (mean / standard deviation)&quot;);\n",
       "    \n",
       "        function geo_json_94dc18ab3f4009442aa3c0eed74fad0a_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                case &quot;1&quot;: case &quot;3&quot;: case &quot;18&quot;: case &quot;21&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;transparent&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;2&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ceecb4ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;7&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f7fcc7ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;8&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f4fbbfff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;9&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f8fdc9ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;13&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f1fabaff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;14&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f5fcc3ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                default:\n",
       "                    return {&quot;fillColor&quot;: &quot;#ffffd9ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "            }\n",
       "        }\n",
       "        function geo_json_94dc18ab3f4009442aa3c0eed74fad0a_highlighter(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;fillOpacity&quot;: 0.9};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_94dc18ab3f4009442aa3c0eed74fad0a_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "                mouseout: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        geo_json_94dc18ab3f4009442aa3c0eed74fad0a.resetStyle(e.target);\n",
       "                    }\n",
       "                },\n",
       "                mouseover: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        const highlightStyle = geo_json_94dc18ab3f4009442aa3c0eed74fad0a_highlighter(e.target.feature)\n",
       "                        e.target.setStyle(highlightStyle);\n",
       "                    }\n",
       "                },\n",
       "            });\n",
       "        };\n",
       "        var geo_json_94dc18ab3f4009442aa3c0eed74fad0a = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_94dc18ab3f4009442aa3c0eed74fad0a_onEachFeature,\n",
       "            \n",
       "                style: geo_json_94dc18ab3f4009442aa3c0eed74fad0a_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_94dc18ab3f4009442aa3c0eed74fad0a_add (data) {\n",
       "            geo_json_94dc18ab3f4009442aa3c0eed74fad0a\n",
       "                .addData(data)\n",
       "                .addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "        }\n",
       "            geo_json_94dc18ab3f4009442aa3c0eed74fad0a_add({&quot;bbox&quot;: [12.5, -10.5, 16.0, -8.0], &quot;features&quot;: [{&quot;bbox&quot;: [13.0, -8.5, 13.5, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -8.0], [13.0, -8.5], [13.5, -8.5], [13.5, -8.0], [13.0, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.6023504656459409e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -8.5, 15.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.0], [13.5, -8.5], [15.0, -8.5], [15.0, -8.0], [13.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -8.5, 15.5, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -8.0], [15.0, -8.5], [15.5, -8.5], [15.5, -8.0], [15.0, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;2&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 8.10509573057061e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.5, -8.5, 16.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -8.0], [15.5, -8.5], [16.0, -8.5], [16.0, -8.0], [15.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;3&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -9.0, 13.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -8.5], [13.0, -9.0], [13.5, -9.0], [13.5, -8.5], [13.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;4&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.9924529226500454e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -9.0, 14.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.5], [13.5, -9.0], [14.0, -9.0], [14.0, -8.5], [13.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;5&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.9575179521780228e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -9.0, 14.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -8.5], [14.0, -9.0], [14.5, -9.0], [14.5, -8.5], [14.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;6&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.0308316379669122e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.5, -9.0, 15.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.5, -8.5], [14.5, -9.0], [15.0, -9.0], [15.0, -8.5], [14.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;7&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 3.576352810341632e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -9.0, 15.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -8.5], [15.0, -9.0], [15.5, -9.0], [15.5, -8.5], [15.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;8&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 4.2591691453708336e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.5, -9.0, 16.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -8.5], [15.5, -9.0], [16.0, -9.0], [16.0, -8.5], [15.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;9&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 3.407666326893377e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -9.5, 13.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -9.0], [13.0, -9.5], [13.5, -9.5], [13.5, -9.0], [13.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;10&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.4656850428073085e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -9.5, 14.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -9.0], [13.5, -9.5], [14.0, -9.5], [14.0, -9.0], [13.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;11&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.8076661351406074e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -9.5, 14.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -9.0], [14.0, -9.5], [14.5, -9.5], [14.5, -9.0], [14.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;12&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 9.690802471595816e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.5, -9.5, 15.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.5, -9.0], [14.5, -9.5], [15.0, -9.5], [15.0, -9.0], [14.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;13&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 4.69897440780187e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -9.5, 15.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -9.0], [15.0, -9.5], [15.5, -9.5], [15.5, -9.0], [15.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;14&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 3.917869435099419e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -10.0, 13.5, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -9.5], [13.0, -10.0], [13.5, -10.0], [13.5, -9.5], [13.0, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;15&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.2702963658739463e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -10.0, 14.0, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -9.5], [13.5, -10.0], [14.0, -10.0], [14.0, -9.5], [13.5, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;16&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 5.572909458351205e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -10.0, 14.5, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -9.5], [14.0, -10.0], [14.5, -10.0], [14.5, -9.5], [14.0, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;17&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 4.949339427184896e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [12.5, -10.5, 13.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[12.5, -8.0], [12.5, -10.5], [13.0, -10.5], [13.0, -8.0], [12.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;18&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -10.5, 13.5, -10.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -10.0], [13.0, -10.5], [13.5, -10.5], [13.5, -10.0], [13.0, -10.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;19&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.0398069889561157e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -10.5, 14.0, -10.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -10.0], [13.5, -10.5], [14.0, -10.5], [14.0, -10.0], [13.5, -10.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;20&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 7.939585771055135e-07}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -10.5, 16.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -9.0], [15.5, -9.5], [14.5, -9.5], [14.5, -10.0], [14.0, -10.0], [14.0, -10.5], [16.0, -10.5], [16.0, -9.0], [15.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;21&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_94dc18ab3f4009442aa3c0eed74fad0a.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;raster_val&quot;];\n",
       "    let aliases = [&quot;Fast surface and fast subsurface runoff (mean)&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: false});\n",
       "                     \n",
       "    \n",
       "        function geo_json_bd29fb3d8f001cd52e72805fe010632f_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                case &quot;1&quot;: case &quot;3&quot;: case &quot;18&quot;: case &quot;21&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;transparent&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;2&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#7dccbcff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;6&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#e4f5b2ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;7&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ceecb4ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;8&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#caebb4ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;9&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#def2b2ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;12&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f3fbbeff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;13&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#bbe5b5ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;14&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#d2eeb3ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;15&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#edf8b1ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;16&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fbfecfff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;17&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fcfed2ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;19&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ecf8b1ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;20&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f1fab8ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                default:\n",
       "                    return {&quot;fillColor&quot;: &quot;#ffffd9ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "            }\n",
       "        }\n",
       "        function geo_json_bd29fb3d8f001cd52e72805fe010632f_highlighter(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;fillOpacity&quot;: 0.9};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_bd29fb3d8f001cd52e72805fe010632f_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "                mouseout: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        geo_json_bd29fb3d8f001cd52e72805fe010632f.resetStyle(e.target);\n",
       "                    }\n",
       "                },\n",
       "                mouseover: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        const highlightStyle = geo_json_bd29fb3d8f001cd52e72805fe010632f_highlighter(e.target.feature)\n",
       "                        e.target.setStyle(highlightStyle);\n",
       "                    }\n",
       "                },\n",
       "            });\n",
       "        };\n",
       "        var geo_json_bd29fb3d8f001cd52e72805fe010632f = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_bd29fb3d8f001cd52e72805fe010632f_onEachFeature,\n",
       "            \n",
       "                style: geo_json_bd29fb3d8f001cd52e72805fe010632f_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_bd29fb3d8f001cd52e72805fe010632f_add (data) {\n",
       "            geo_json_bd29fb3d8f001cd52e72805fe010632f\n",
       "                .addData(data)\n",
       "                .addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "        }\n",
       "            geo_json_bd29fb3d8f001cd52e72805fe010632f_add({&quot;bbox&quot;: [12.5, -10.5, 16.0, -8.0], &quot;features&quot;: [{&quot;bbox&quot;: [13.0, -8.5, 13.5, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -8.0], [13.0, -8.5], [13.5, -8.5], [13.5, -8.0], [13.0, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.2756456726492615e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -8.5, 15.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.0], [13.5, -8.5], [15.0, -8.5], [15.0, -8.0], [13.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -8.5, 15.5, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -8.0], [15.0, -8.5], [15.5, -8.5], [15.5, -8.0], [15.0, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;2&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.2149908798164688e-05}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.5, -8.5, 16.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -8.0], [15.5, -8.5], [16.0, -8.5], [16.0, -8.0], [15.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;3&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -9.0, 13.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -8.5], [13.0, -9.0], [13.5, -9.0], [13.5, -8.5], [13.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;4&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.8754657276076614e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -9.0, 14.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.5], [13.5, -9.0], [14.0, -9.0], [14.0, -8.5], [13.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;5&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.640233335820085e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -9.0, 14.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -8.5], [14.0, -9.0], [14.5, -9.0], [14.5, -8.5], [14.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;6&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 6.206330454006093e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.5, -9.0, 15.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.5, -8.5], [14.5, -9.0], [15.0, -9.0], [15.0, -8.5], [14.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;7&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 8.139495548675768e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -9.0, 15.5, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -8.5], [15.0, -9.0], [15.5, -9.0], [15.5, -8.5], [15.0, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;8&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 8.455304850940593e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.5, -9.0, 16.0, -8.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -8.5], [15.5, -9.0], [16.0, -9.0], [16.0, -8.5], [15.5, -8.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;9&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 6.733850113960216e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -9.5, 13.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -9.0], [13.0, -9.5], [13.5, -9.5], [13.5, -9.0], [13.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;10&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.7157605043394142e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -9.5, 14.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -9.0], [13.5, -9.5], [14.0, -9.5], [14.0, -9.0], [13.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;11&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1.4858258055028273e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -9.5, 14.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -9.0], [14.0, -9.5], [14.5, -9.5], [14.5, -9.0], [14.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;12&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 4.306406935938867e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.5, -9.5, 15.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.5, -9.0], [14.5, -9.5], [15.0, -9.5], [15.0, -9.0], [14.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;13&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 9.25729727896396e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [15.0, -9.5, 15.5, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.0, -9.0], [15.0, -9.5], [15.5, -9.5], [15.5, -9.0], [15.0, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;14&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 7.789049050188623e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -10.0, 13.5, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -9.5], [13.0, -10.0], [13.5, -10.0], [13.5, -9.5], [13.0, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;15&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 5.431196768768132e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -10.0, 14.0, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -9.5], [13.5, -10.0], [14.0, -10.0], [14.0, -9.5], [13.5, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;16&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.929707306975615e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -10.0, 14.5, -9.5], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[14.0, -9.5], [14.0, -10.0], [14.5, -10.0], [14.5, -9.5], [14.0, -9.5]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;17&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 2.6434779556439025e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [12.5, -10.5, 13.0, -8.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[12.5, -8.0], [12.5, -10.5], [13.0, -10.5], [13.0, -8.0], [12.5, -8.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;18&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.0, -10.5, 13.5, -10.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.0, -10.0], [13.0, -10.5], [13.5, -10.5], [13.5, -10.0], [13.0, -10.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;19&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 5.5005380090733524e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -10.5, 14.0, -10.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -10.0], [13.5, -10.5], [14.0, -10.5], [14.0, -10.0], [13.5, -10.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;20&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 4.817593435291201e-06}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [14.0, -10.5, 16.0, -9.0], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[15.5, -9.0], [15.5, -9.5], [14.5, -9.5], [14.5, -10.0], [14.0, -10.0], [14.0, -10.5], [16.0, -10.5], [16.0, -9.0], [15.5, -9.0]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;21&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: null}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_bd29fb3d8f001cd52e72805fe010632f.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;raster_val&quot;];\n",
       "    let aliases = [&quot;Fast surface and fast subsurface runoff (standard deviation)&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: false});\n",
       "                     \n",
       "    \n",
       "            var layer_control_bb4a4fe3869a039ed41eb283a4c197cb = {\n",
       "                base_layers : {\n",
       "                    &quot;cartodbpositron&quot; : tile_layer_56172963a9006926addb6b00ddf85085,\n",
       "                },\n",
       "                overlays :  {\n",
       "                    &quot;Net cell runoff (mean)&quot; : geo_json_c0a0837a8a4f28a3995b24f20f456c11,\n",
       "                    &quot;Net cell runoff (standard deviation)&quot; : geo_json_14e46c5d49de9127bcb093767728ec4b,\n",
       "                    &quot;Fast surface and fast subsurface runoff (mean)&quot; : geo_json_94dc18ab3f4009442aa3c0eed74fad0a,\n",
       "                    &quot;Fast surface and fast subsurface runoff (standard deviation)&quot; : geo_json_bd29fb3d8f001cd52e72805fe010632f,\n",
       "                },\n",
       "            };\n",
       "            L.control.layers(\n",
       "                layer_control_bb4a4fe3869a039ed41eb283a4c197cb.base_layers,\n",
       "                layer_control_bb4a4fe3869a039ed41eb283a4c197cb.overlays,\n",
       "                {&quot;autoZIndex&quot;: true, &quot;collapsed&quot;: true, &quot;position&quot;: &quot;topright&quot;}\n",
       "            ).addTo(map_ccf133a40e539bd6e38700a45d6d2351);\n",
       "            geo_json_14e46c5d49de9127bcb093767728ec4b.remove();\n",
       "            geo_json_94dc18ab3f4009442aa3c0eed74fad0a.remove();\n",
       "            geo_json_bd29fb3d8f001cd52e72805fe010632f.remove();\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2214805f280>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for var in var_list:\n",
    "    # set colormap\n",
    "    if var == 'ncrun':\n",
    "        colormap = linear.GnBu_09.scale(json['raster_val'].min(), json['raster_val'].max())\n",
    "        colormap.caption = f\"{var_list[var]} (mean / standard deviation)\"\n",
    "        colormap.add_to(mymap)\n",
    "    elif var == 'qs':\n",
    "        colormap = linear.YlGnBu_09.scale(json['raster_val'].min(), json['raster_val'].max())\n",
    "        colormap.caption = f\"{var_list[var]} (mean / standard deviation)\"\n",
    "        colormap.add_to(mymap)\n",
    "        \n",
    "    for stat in stat_list:\n",
    "        # read json\n",
    "        json = gpd.read_file(output_folder / f'{city.lower()}_{var}_{stat}.geojson').to_crs('epsg:4326')\n",
    "        \n",
    "        # determine whether to show layer by default\n",
    "        show = False\n",
    "        if var == 'ncrun' and stat == 'mean':\n",
    "            show = True\n",
    "        \n",
    "        # Add GeoJson layer with choropleth style\n",
    "        folium.GeoJson(\n",
    "            json,\n",
    "            name = f'{var_list[var]} ({stat_list[stat]})',\n",
    "            # overlay = False,\n",
    "            style_function=lambda feature: {\n",
    "                'fillColor': 'transparent' if pd.isna(feature['properties']['raster_val']) else colormap(feature['properties']['raster_val']),\n",
    "                # 'fillColor': colormap(feature['properties']['raster_val']),\n",
    "                'fillOpacity': 0.7,\n",
    "                'weight': 0,\n",
    "            },\n",
    "            highlight_function=lambda x: {'fillOpacity': 0.9},\n",
    "            tooltip=folium.GeoJsonTooltip(fields=['raster_val'], aliases = [f'{var_list[var]} ({stat_list[stat]})'], \n",
    "                                          labels=True, sticky=False),\n",
    "            show = show\n",
    "        ).add_to(mymap)\n",
    "\n",
    "# Add Layer Control to toggle the choropleth layer\n",
    "folium.LayerControl().add_to(mymap)\n",
    "\n",
    "mymap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f975f2e5-b4b5-4217-b76b-58b8afc55cab",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Potential evapotranspiration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "20749587-7466-4411-82ff-2882a083150b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(output_folder / 'potential_evaporation.csv')\n",
    "df['time'] = pd.to_datetime(df['time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "fddb2dfb-7f5b-4905-8ee0-ebc1aa417e77",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "\n",
    "# Create the line chart using Seaborn with connected lines\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "sns.lineplot(data=df, x='time', y='Ep', linewidth=1, color = '#c51b8a')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('')\n",
    "plt.ylabel('')\n",
    "plt.title('Monthly potential evaporation 1993-2022 (mm/day)')\n",
    "\n",
    "# plt.xticks(rotation=45)\n",
    "plt.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba8d3e84-313c-4b4c-a601-c0f648ee42ff",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Water pollution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "68d3eef0-345a-4616-b084-d72d700a3d7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ec = pd.read_csv(output_folder / f'{city.lower()}_electrical_conductivity.csv')\n",
    "noxn = pd.read_csv(output_folder / f'{city.lower()}_nitrate_nitrite.csv')\n",
    "bod = pd.read_csv(output_folder / f'{city.lower()}_biological_oxygen_demand.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "edc0cb69-5219-4582-ad4f-542e14cf57b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "ec['day'] = 1\n",
    "ec['time'] = pd.to_datetime(ec[['year', 'month', 'day']])\n",
    "noxn['day'] = 1\n",
    "noxn['time'] = pd.to_datetime(noxn[['year', 'month', 'day']])\n",
    "bod['day'] = 1\n",
    "bod['time'] = pd.to_datetime(bod[['year', 'month', 'day']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "7d8a1922-f3c9-404f-a79c-6ceef48417c7",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "\n",
    "# Create the line chart using Seaborn with connected lines\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "sns.lineplot(data=ec, x='time', y='preds', linewidth=1, color = '#e34a33')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('')\n",
    "plt.ylabel('')\n",
    "plt.title('Monthly electrical conductivity in surface water 1993-2022 (uS/cm)')\n",
    "\n",
    "# plt.xticks(rotation=45)\n",
    "plt.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c4f0fd10-c3bd-414a-85fb-00553388420d",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "\n",
    "# Create the line chart using Seaborn with connected lines\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "sns.lineplot(data=noxn, x='time', y='preds', linewidth=1, color = '#016c59')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('')\n",
    "plt.ylabel('')\n",
    "plt.title('Monthly nitrate-nitrite in surface water 1993-2022 (mg/l)')\n",
    "\n",
    "# plt.xticks(rotation=45)\n",
    "plt.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "3a54fad7-cf29-446d-9521-b28bd690f8ad",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "\n",
    "# Create the line chart using Seaborn with connected lines\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "sns.lineplot(data=bod, x='time', y='preds', linewidth=1, color = '#1c9099')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('')\n",
    "plt.ylabel('')\n",
    "plt.title('Monthly biological oxygen demand in surface water 1993-2022 (mg/l)')\n",
    "\n",
    "# plt.xticks(rotation=45)\n",
    "plt.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f093d7a1-749b-403b-851f-5bde736d52f7",
   "metadata": {},
   "source": [
    "### Residential overlay with livestock"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "99c89ffa-ca15-4dac-87bf-3b391c201a2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "glw = gpd.read_file(output_folder / f'{city.lower()}_livestock.geojson').to_crs('epsg:4326')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "bb2a3deb-4bd1-4200-a621-4876e6ca8c9b",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<folium.features.GeoJson at 0x22144d6cb20>"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a folium map centered on the AOI\n",
    "mymap = folium.Map(tiles=\"Cartodb Positron\", control_scale = True)\n",
    "aoi_bounds = aoi.total_bounds.tolist()\n",
    "mymap.fit_bounds([aoi_bounds[:2][::-1], aoi_bounds[2:][::-1]])\n",
    "\n",
    "folium.GeoJson(\n",
    "    aoi,\n",
    "    style_function=lambda feature: {\n",
    "        'fillColor': 'transparent',\n",
    "        'color': 'gray',\n",
    "        'weight': 3\n",
    "    },\n",
    "    control = False).add_to(mymap)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "faf7fbdb-e97c-43bf-93d3-0f89c93d5912",
   "metadata": {},
   "source": [
    "**Could you please add the built-up area underlay to this map??**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "d68ac1a3-804b-445d-895f-4fc88dc1d336",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_e28c5f9f1681f070d131960d6f15f699 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js&quot;&gt;&lt;/script&gt;\n",
       "    \n",
       "                    &lt;style&gt;\n",
       "                        .foliumtooltip {\n",
       "                            \n",
       "                        }\n",
       "                       .foliumtooltip table{\n",
       "                            margin: auto;\n",
       "                        }\n",
       "                        .foliumtooltip tr{\n",
       "                            text-align: left;\n",
       "                        }\n",
       "                        .foliumtooltip th{\n",
       "                            padding: 2px; padding-right: 8px;\n",
       "                        }\n",
       "                    &lt;/style&gt;\n",
       "            \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_e28c5f9f1681f070d131960d6f15f699&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_e28c5f9f1681f070d131960d6f15f699 = L.map(\n",
       "                &quot;map_e28c5f9f1681f070d131960d6f15f699&quot;,\n",
       "                {\n",
       "                    center: [0, 0],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 1,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "            L.control.scale().addTo(map_e28c5f9f1681f070d131960d6f15f699);\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_f477aa5e5d4b307b15beecb2120f6694 = L.tileLayer(\n",
       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca target=\\&quot;_blank\\&quot; href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_e28c5f9f1681f070d131960d6f15f699);\n",
       "        \n",
       "    \n",
       "            map_e28c5f9f1681f070d131960d6f15f699.fitBounds(\n",
       "                [[-9.344259181999917, 12.992500001000167], [-8.636368108999932, 13.633978038000066]],\n",
       "                {}\n",
       "            );\n",
       "        \n",
       "    \n",
       "        function geo_json_7d48dd8132eca166d9b9395ed95462c8_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;color&quot;: &quot;gray&quot;, &quot;fillColor&quot;: &quot;transparent&quot;, &quot;weight&quot;: 3};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_7d48dd8132eca166d9b9395ed95462c8_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "            });\n",
       "        };\n",
       "        var geo_json_7d48dd8132eca166d9b9395ed95462c8 = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_7d48dd8132eca166d9b9395ed95462c8_onEachFeature,\n",
       "            \n",
       "                style: geo_json_7d48dd8132eca166d9b9395ed95462c8_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_7d48dd8132eca166d9b9395ed95462c8_add (data) {\n",
       "            geo_json_7d48dd8132eca166d9b9395ed95462c8\n",
       "                .addData(data)\n",
       "                .addTo(map_e28c5f9f1681f070d131960d6f15f699);\n",
       "        }\n",
       "            geo_json_7d48dd8132eca166d9b9395ed95462c8_add({&quot;bbox&quot;: [12.992500001000167, -9.344259181999917, 13.633978038000066, -8.636368108999932], &quot;features&quot;: [{&quot;bbox&quot;: [12.992500001000167, -9.344259181999917, 13.633978038000066, -8.636368108999932], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[[13.019185425000103, -9.021944499999904], [13.02048584400012, -9.01380766699998], [13.023560067000062, -9.00836106699984], [13.025290909000091, -9.014184181999894], [13.023628480000127, -9.020155319999958], [13.019185425000103, -9.021944499999904]]], [[[12.996944833000043, -9.099643943999979], [12.994567417000155, -9.093995874999962], [12.992986250000172, -9.086528], [12.992500001000167, -9.080417000999944], [12.992500001000167, -9.070138000999975], [12.992778000000158, -9.064027999999894], [12.993056, -9.058474], [12.993471500000169, -9.05416699899996], [12.99402700000013, -9.048332000999892], [12.9946528750001, -9.0427], [12.995650200000114, 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       "\n",
       "        \n",
       "    \n",
       "    var color_map_6884dc2ef07b6be130dc3e998d884ea0 = {};\n",
       "\n",
       "    \n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.color = d3.scale.threshold()\n",
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       "    \n",
       "\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.x = d3.scale.linear()\n",
       "              .domain([1091.411865234375, 651066.4375])\n",
       "              .range([0, 450 - 50]);\n",
       "\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.legend = L.control({position: &#x27;topright&#x27;});\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.legend.onAdd = function (map) {var div = L.DomUtil.create(&#x27;div&#x27;, &#x27;legend&#x27;); return div};\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.legend.addTo(map_e28c5f9f1681f070d131960d6f15f699);\n",
       "\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.xAxis = d3.svg.axis()\n",
       "        .scale(color_map_6884dc2ef07b6be130dc3e998d884ea0.x)\n",
       "        .orient(&quot;top&quot;)\n",
       "        .tickSize(1)\n",
       "        .tickValues([1091.411865234375, 82338.29006958008, 163585.16827392578, 244832.04647827148, 326078.9246826172, 407325.8028869629, 488572.6810913086, 569819.5592956543, 651066.4375]);\n",
       "\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.svg = d3.select(&quot;.legend.leaflet-control&quot;).append(&quot;svg&quot;)\n",
       "        .attr(&quot;id&quot;, &#x27;legend&#x27;)\n",
       "        .attr(&quot;width&quot;, 450)\n",
       "        .attr(&quot;height&quot;, 40);\n",
       "\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.g = color_map_6884dc2ef07b6be130dc3e998d884ea0.svg.append(&quot;g&quot;)\n",
       "        .attr(&quot;class&quot;, &quot;key&quot;)\n",
       "        .attr(&quot;transform&quot;, &quot;translate(25,16)&quot;);\n",
       "\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.g.selectAll(&quot;rect&quot;)\n",
       "        .data(color_map_6884dc2ef07b6be130dc3e998d884ea0.color.range().map(function(d, i) {\n",
       "          return {\n",
       "            x0: i ? color_map_6884dc2ef07b6be130dc3e998d884ea0.x(color_map_6884dc2ef07b6be130dc3e998d884ea0.color.domain()[i - 1]) : color_map_6884dc2ef07b6be130dc3e998d884ea0.x.range()[0],\n",
       "            x1: i &lt; color_map_6884dc2ef07b6be130dc3e998d884ea0.color.domain().length ? color_map_6884dc2ef07b6be130dc3e998d884ea0.x(color_map_6884dc2ef07b6be130dc3e998d884ea0.color.domain()[i]) : color_map_6884dc2ef07b6be130dc3e998d884ea0.x.range()[1],\n",
       "            z: d\n",
       "          };\n",
       "        }))\n",
       "      .enter().append(&quot;rect&quot;)\n",
       "        .attr(&quot;height&quot;, 40 - 30)\n",
       "        .attr(&quot;x&quot;, function(d) { return d.x0; })\n",
       "        .attr(&quot;width&quot;, function(d) { return d.x1 - d.x0; })\n",
       "        .style(&quot;fill&quot;, function(d) { return d.z; });\n",
       "\n",
       "    color_map_6884dc2ef07b6be130dc3e998d884ea0.g.call(color_map_6884dc2ef07b6be130dc3e998d884ea0.xAxis).append(&quot;text&quot;)\n",
       "        .attr(&quot;class&quot;, &quot;caption&quot;)\n",
       "        .attr(&quot;y&quot;, 21)\n",
       "        .text(&quot;Number of livestocks&quot;);\n",
       "    \n",
       "        function geo_json_e4155ee2ae868a911ca462602fe3f563_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                case &quot;0&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffea99ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;1&quot;: case &quot;20&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffffcaff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;2&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffda77ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;4&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f33924ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;5&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#800026ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;6&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fec15cff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;7&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fff2acff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;8&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fffcc4ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;9&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f64126ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;10&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f74226ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;11&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#9e0026ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;12&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffe084ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;13&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffdc7cff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;14&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffffcbff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;15&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#feaf4aff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;16&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#f94627ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;17&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fe9c42ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;18&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#d10d21ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;19&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fed06cff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;22&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffefa5ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;23&quot;: case &quot;31&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffec9eff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;24&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffe691ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;25&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffec9dff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;26&quot;: case &quot;27&quot;: case &quot;28&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fffec9ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;30&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fffdc7ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;32&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#fffdc6ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                case &quot;35&quot;: \n",
       "                    return {&quot;fillColor&quot;: &quot;#ffffccff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "                default:\n",
       "                    return {&quot;fillColor&quot;: &quot;#fffec8ff&quot;, &quot;fillOpacity&quot;: 0.7, &quot;weight&quot;: 0};\n",
       "            }\n",
       "        }\n",
       "        function geo_json_e4155ee2ae868a911ca462602fe3f563_highlighter(feature) {\n",
       "            switch(feature.id) {\n",
       "                default:\n",
       "                    return {&quot;fillOpacity&quot;: 0.9};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_e4155ee2ae868a911ca462602fe3f563_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "                mouseout: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        geo_json_e4155ee2ae868a911ca462602fe3f563.resetStyle(e.target);\n",
       "                    }\n",
       "                },\n",
       "                mouseover: function(e) {\n",
       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
       "                        const highlightStyle = geo_json_e4155ee2ae868a911ca462602fe3f563_highlighter(e.target.feature)\n",
       "                        e.target.setStyle(highlightStyle);\n",
       "                    }\n",
       "                },\n",
       "            });\n",
       "        };\n",
       "        var geo_json_e4155ee2ae868a911ca462602fe3f563 = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_e4155ee2ae868a911ca462602fe3f563_onEachFeature,\n",
       "            \n",
       "                style: geo_json_e4155ee2ae868a911ca462602fe3f563_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_e4155ee2ae868a911ca462602fe3f563_add (data) {\n",
       "            geo_json_e4155ee2ae868a911ca462602fe3f563\n",
       "                .addData(data)\n",
       "                .addTo(map_e28c5f9f1681f070d131960d6f15f699);\n",
       "        }\n",
       "            geo_json_e4155ee2ae868a911ca462602fe3f563_add({&quot;bbox&quot;: [13.0, -9.333333333333329, 13.666666666666657, -8.583333333333329], &quot;features&quot;: [{&quot;bbox&quot;: [13.416666666666657, -8.666666666666663, 13.5, -8.583333333333329], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.416666666666657, -8.583333333333329], [13.416666666666657, -8.666666666666663], [13.5, -8.666666666666663], [13.5, -8.583333333333329], [13.416666666666657, -8.583333333333329]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 96308.3828125}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -8.666666666666663, 13.583333333333323, -8.583333333333329], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.583333333333329], [13.5, -8.666666666666663], [13.583333333333323, -8.666666666666663], [13.583333333333323, -8.583333333333329], [13.5, -8.583333333333329]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 5478.6435546875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.416666666666657, -8.75, 13.5, -8.666666666666663], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.416666666666657, -8.666666666666663], [13.416666666666657, -8.75], [13.5, -8.75], [13.5, -8.666666666666663], [13.416666666666657, -8.666666666666663]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;2&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 161075.28125}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -8.75, 13.583333333333323, -8.666666666666663], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.666666666666663], [13.5, -8.75], [13.583333333333323, -8.75], [13.583333333333323, -8.666666666666663], [13.5, -8.666666666666663]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;3&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 9689.333984375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.25, -8.833333333333329, 13.333333333333323, -8.75], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.25, -8.75], [13.25, -8.833333333333329], [13.333333333333323, -8.833333333333329], [13.333333333333323, -8.75], [13.25, -8.75]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;4&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 439527.25}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.333333333333323, -8.833333333333329, 13.416666666666657, -8.75], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.333333333333323, -8.75], [13.333333333333323, -8.833333333333329], [13.416666666666657, -8.833333333333329], [13.416666666666657, -8.75], [13.333333333333323, -8.75]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;5&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 651066.4375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.416666666666657, -8.833333333333329, 13.5, -8.75], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.416666666666657, -8.75], [13.416666666666657, -8.833333333333329], [13.5, -8.833333333333329], [13.5, -8.75], [13.416666666666657, -8.75]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;6&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 214122.765625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -8.833333333333329, 13.583333333333323, -8.75], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.75], [13.5, -8.833333333333329], [13.583333333333323, -8.833333333333329], [13.583333333333323, -8.75], [13.5, -8.75]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;7&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 60088.98828125}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.583333333333323, -8.833333333333329, 13.666666666666657, -8.75], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.583333333333323, -8.75], [13.583333333333323, -8.833333333333329], [13.666666666666657, -8.833333333333329], [13.666666666666657, -8.75], [13.583333333333323, -8.75]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;8&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 17236.322265625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.166666666666657, -8.916666666666663, 13.25, -8.833333333333329], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.166666666666657, -8.833333333333329], [13.166666666666657, -8.916666666666663], [13.25, -8.916666666666663], [13.25, -8.833333333333329], [13.166666666666657, -8.833333333333329]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;9&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 426946.0}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.25, -8.916666666666663, 13.333333333333323, -8.833333333333329], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.25, -8.833333333333329], [13.25, -8.916666666666663], [13.333333333333323, -8.916666666666663], [13.333333333333323, -8.833333333333329], [13.25, -8.833333333333329]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;10&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 425778.46875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.333333333333323, -8.916666666666663, 13.416666666666657, -8.833333333333329], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.333333333333323, -8.833333333333329], [13.333333333333323, -8.916666666666663], [13.416666666666657, -8.916666666666663], [13.416666666666657, -8.833333333333329], [13.333333333333323, -8.833333333333329]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;11&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 611178.5625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.416666666666657, -8.916666666666663, 13.5, -8.833333333333329], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.416666666666657, -8.833333333333329], [13.416666666666657, -8.916666666666663], [13.5, -8.916666666666663], [13.5, -8.833333333333329], [13.416666666666657, -8.833333333333329]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;12&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 135581.015625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.5, -8.916666666666663, 13.583333333333323, -8.833333333333329], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.5, -8.833333333333329], [13.5, -8.916666666666663], [13.583333333333323, -8.916666666666663], [13.583333333333323, -8.833333333333329], [13.5, -8.833333333333329]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;13&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 151911.6875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.583333333333323, -8.916666666666663, 13.666666666666657, -8.833333333333329], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.583333333333323, -8.833333333333329], [13.583333333333323, -8.916666666666663], [13.666666666666657, -8.916666666666663], [13.666666666666657, -8.833333333333329], [13.583333333333323, -8.833333333333329]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;14&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 4053.243896484375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.083333333333323, -9.0, 13.166666666666657, -8.916666666666663], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.083333333333323, -8.916666666666663], [13.083333333333323, -9.0], [13.166666666666657, -9.0], [13.166666666666657, -8.916666666666663], [13.083333333333323, -8.916666666666663]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;15&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 252081.65625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.166666666666657, -9.0, 13.25, -8.916666666666663], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.166666666666657, -8.916666666666663], [13.166666666666657, -9.0], [13.25, -9.0], [13.25, -8.916666666666663], [13.166666666666657, -8.916666666666663]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;16&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 420049.46875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.25, -9.0, 13.333333333333323, -8.916666666666663], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.25, -8.916666666666663], [13.25, -9.0], [13.333333333333323, -9.0], [13.333333333333323, -8.916666666666663], [13.25, -8.916666666666663]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;17&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 293153.6875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.333333333333323, -9.0, 13.416666666666657, -8.916666666666663], &quot;geometry&quot;: {&quot;coordinates&quot;: 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&quot;Polygon&quot;}, &quot;id&quot;: &quot;34&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 9694.2568359375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [13.166666666666657, -9.333333333333329, 13.25, -9.25], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[13.166666666666657, -9.25], [13.166666666666657, -9.333333333333329], [13.25, -9.333333333333329], [13.25, -9.25], [13.166666666666657, -9.25]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;35&quot;, &quot;properties&quot;: {&quot;raster_val&quot;: 1091.411865234375}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_e4155ee2ae868a911ca462602fe3f563.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;raster_val&quot;];\n",
       "    let aliases = [&quot;Number of livestocks&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: false});\n",
       "                     \n",
       "    \n",
       "            var layer_control_20700a64632c93250ba84ccda215aad3 = {\n",
       "                base_layers : {\n",
       "                    &quot;cartodbpositron&quot; : tile_layer_f477aa5e5d4b307b15beecb2120f6694,\n",
       "                },\n",
       "                overlays :  {\n",
       "                    &quot;Number of livestocks&quot; : geo_json_e4155ee2ae868a911ca462602fe3f563,\n",
       "                },\n",
       "            };\n",
       "            L.control.layers(\n",
       "                layer_control_20700a64632c93250ba84ccda215aad3.base_layers,\n",
       "                layer_control_20700a64632c93250ba84ccda215aad3.overlays,\n",
       "                {&quot;autoZIndex&quot;: true, &quot;collapsed&quot;: true, &quot;position&quot;: &quot;topright&quot;}\n",
       "            ).addTo(map_e28c5f9f1681f070d131960d6f15f699);\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x22144d6e6b0>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a colormap based on the 'YlOrRd' scale and the 'raster_val' column\n",
    "colormap = linear.YlOrRd_09.scale(glw['raster_val'].min(), glw['raster_val'].max())\n",
    "colormap.caption = \"Number of livestocks\"\n",
    "colormap.add_to(mymap)\n",
    "\n",
    "# Add GeoJson layer with choropleth style\n",
    "folium.GeoJson(\n",
    "    glw,\n",
    "    name='Number of livestocks',\n",
    "    style_function=lambda feature: {\n",
    "        'fillColor': colormap(feature['properties']['raster_val']),\n",
    "        'fillOpacity': 0.7,\n",
    "        'weight': 0,\n",
    "    },\n",
    "    highlight_function=lambda x: {'fillOpacity': 0.9},\n",
    "    tooltip=folium.GeoJsonTooltip(fields=['raster_val'], aliases = ['Number of livestocks'], labels=True, sticky=False),\n",
    ").add_to(mymap)\n",
    "\n",
    "# Add Layer Control to toggle the choropleth layer\n",
    "folium.LayerControl().add_to(mymap)\n",
    "\n",
    "mymap"
   ]
  }
 ],
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