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diff --git a/data/input/mixed/df_1/Waterbase_v2021_1_S_WISE6_SpatialObject_DerivedData.csv b/data/input/mixed/df_1/Waterbase_v2021_1_S_WISE6_SpatialObject_DerivedData.csv
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diff --git a/data/input/schelde/depth/df_1/Schelde depth.csv b/data/input/schelde/depth/df_1/Schelde depth.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3cfb8afa6014d7bab97df21962a838c61f854815
--- /dev/null
+++ b/data/input/schelde/depth/df_1/Schelde depth.csv	
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+version https://git-lfs.github.com/spec/v1
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diff --git a/ipynb/Schelde_Turbidity.ipynb b/ipynb/Schelde_Turbidity.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..3d7c1cad852de9331c3e02008457541dbcc8e2b1
--- /dev/null
+++ b/ipynb/Schelde_Turbidity.ipynb
@@ -0,0 +1,750 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "ca1a2222",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import os\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c53b7ab1",
+   "metadata": {},
+   "source": [
+    "## pre-processing Schelde turbidity data\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f1a9115b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>aphiaid</th>\n",
+       "      <th>latitude</th>\n",
+       "      <th>longitude</th>\n",
+       "      <th>depth</th>\n",
+       "      <th>datetime</th>\n",
+       "      <th>value</th>\n",
+       "      <th>lod</th>\n",
+       "      <th>loq</th>\n",
+       "      <th>standardparameterid</th>\n",
+       "      <th>...</th>\n",
+       "      <th>parametername</th>\n",
+       "      <th>parameterunit</th>\n",
+       "      <th>dataprovider</th>\n",
+       "      <th>datasettitle</th>\n",
+       "      <th>datafichetitle</th>\n",
+       "      <th>stationname</th>\n",
+       "      <th>category</th>\n",
+       "      <th>valuesign</th>\n",
+       "      <th>dateprecision</th>\n",
+       "      <th>scientificname</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8975471</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>51.320855</td>\n",
+       "      <td>4.276312</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2005-09-21T10:00:00</td>\n",
+       "      <td>111</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5384</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Nefelometrisch troebelheid (NTU)</td>\n",
+       "      <td>NTU</td>\n",
+       "      <td>MOW WL - Waterbouwkundig Laboratorium</td>\n",
+       "      <td>Flanders Hydraulics Research: Continuous monit...</td>\n",
+       "      <td>S-FC-V-005 - Turbiditeit - Continu</td>\n",
+       "      <td>Boei84-Boven SF/Zeeschelde</td>\n",
+       "      <td>lichtklimaat</td>\n",
+       "      <td>=</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>8975472</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>51.320855</td>\n",
+       "      <td>4.276312</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2005-09-21T10:10:00</td>\n",
+       "      <td>102</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5384</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Nefelometrisch troebelheid (NTU)</td>\n",
+       "      <td>NTU</td>\n",
+       "      <td>MOW WL - Waterbouwkundig Laboratorium</td>\n",
+       "      <td>Flanders Hydraulics Research: Continuous monit...</td>\n",
+       "      <td>S-FC-V-005 - Turbiditeit - Continu</td>\n",
+       "      <td>Boei84-Boven SF/Zeeschelde</td>\n",
+       "      <td>lichtklimaat</td>\n",
+       "      <td>=</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>8975473</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>51.320855</td>\n",
+       "      <td>4.276312</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2005-09-21T10:20:00</td>\n",
+       "      <td>94</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5384</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Nefelometrisch troebelheid (NTU)</td>\n",
+       "      <td>NTU</td>\n",
+       "      <td>MOW WL - Waterbouwkundig Laboratorium</td>\n",
+       "      <td>Flanders Hydraulics Research: Continuous monit...</td>\n",
+       "      <td>S-FC-V-005 - Turbiditeit - Continu</td>\n",
+       "      <td>Boei84-Boven SF/Zeeschelde</td>\n",
+       "      <td>lichtklimaat</td>\n",
+       "      <td>=</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8975474</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>51.320855</td>\n",
+       "      <td>4.276312</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2005-09-21T10:30:00</td>\n",
+       "      <td>97</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5384</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Nefelometrisch troebelheid (NTU)</td>\n",
+       "      <td>NTU</td>\n",
+       "      <td>MOW WL - Waterbouwkundig Laboratorium</td>\n",
+       "      <td>Flanders Hydraulics Research: Continuous monit...</td>\n",
+       "      <td>S-FC-V-005 - Turbiditeit - Continu</td>\n",
+       "      <td>Boei84-Boven SF/Zeeschelde</td>\n",
+       "      <td>lichtklimaat</td>\n",
+       "      <td>=</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>8975475</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>51.320855</td>\n",
+       "      <td>4.276312</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2005-09-21T10:40:00</td>\n",
+       "      <td>91</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5384</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Nefelometrisch troebelheid (NTU)</td>\n",
+       "      <td>NTU</td>\n",
+       "      <td>MOW WL - Waterbouwkundig Laboratorium</td>\n",
+       "      <td>Flanders Hydraulics Research: Continuous monit...</td>\n",
+       "      <td>S-FC-V-005 - Turbiditeit - Continu</td>\n",
+       "      <td>Boei84-Boven SF/Zeeschelde</td>\n",
+       "      <td>lichtklimaat</td>\n",
+       "      <td>=</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        id  aphiaid   latitude  longitude  depth             datetime  value  \\\n",
+       "0  8975471      NaN  51.320855   4.276312    NaN  2005-09-21T10:00:00    111   \n",
+       "1  8975472      NaN  51.320855   4.276312    NaN  2005-09-21T10:10:00    102   \n",
+       "2  8975473      NaN  51.320855   4.276312    NaN  2005-09-21T10:20:00     94   \n",
+       "3  8975474      NaN  51.320855   4.276312    NaN  2005-09-21T10:30:00     97   \n",
+       "4  8975475      NaN  51.320855   4.276312    NaN  2005-09-21T10:40:00     91   \n",
+       "\n",
+       "   lod  loq  standardparameterid  ...                     parametername  \\\n",
+       "0  NaN  NaN                 5384  ...  Nefelometrisch troebelheid (NTU)   \n",
+       "1  NaN  NaN                 5384  ...  Nefelometrisch troebelheid (NTU)   \n",
+       "2  NaN  NaN                 5384  ...  Nefelometrisch troebelheid (NTU)   \n",
+       "3  NaN  NaN                 5384  ...  Nefelometrisch troebelheid (NTU)   \n",
+       "4  NaN  NaN                 5384  ...  Nefelometrisch troebelheid (NTU)   \n",
+       "\n",
+       "   parameterunit                           dataprovider  \\\n",
+       "0            NTU  MOW WL - Waterbouwkundig Laboratorium   \n",
+       "1            NTU  MOW WL - Waterbouwkundig Laboratorium   \n",
+       "2            NTU  MOW WL - Waterbouwkundig Laboratorium   \n",
+       "3            NTU  MOW WL - Waterbouwkundig Laboratorium   \n",
+       "4            NTU  MOW WL - Waterbouwkundig Laboratorium   \n",
+       "\n",
+       "                                        datasettitle  \\\n",
+       "0  Flanders Hydraulics Research: Continuous monit...   \n",
+       "1  Flanders Hydraulics Research: Continuous monit...   \n",
+       "2  Flanders Hydraulics Research: Continuous monit...   \n",
+       "3  Flanders Hydraulics Research: Continuous monit...   \n",
+       "4  Flanders Hydraulics Research: Continuous monit...   \n",
+       "\n",
+       "                       datafichetitle                 stationname  \\\n",
+       "0  S-FC-V-005 - Turbiditeit - Continu  Boei84-Boven SF/Zeeschelde   \n",
+       "1  S-FC-V-005 - Turbiditeit - Continu  Boei84-Boven SF/Zeeschelde   \n",
+       "2  S-FC-V-005 - Turbiditeit - Continu  Boei84-Boven SF/Zeeschelde   \n",
+       "3  S-FC-V-005 - Turbiditeit - Continu  Boei84-Boven SF/Zeeschelde   \n",
+       "4  S-FC-V-005 - Turbiditeit - Continu  Boei84-Boven SF/Zeeschelde   \n",
+       "\n",
+       "       category valuesign dateprecision scientificname  \n",
+       "0  lichtklimaat         =           NaN            NaN  \n",
+       "1  lichtklimaat         =           NaN            NaN  \n",
+       "2  lichtklimaat         =           NaN            NaN  \n",
+       "3  lichtklimaat         =           NaN            NaN  \n",
+       "4  lichtklimaat         =           NaN            NaN  \n",
+       "\n",
+       "[5 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#os.getcwd()\n",
+    "os.chdir(\"C:\\\\Users\\\\Hannah Russell\\\\north_sea_estuaries_visualisations\")\n",
+    "\n",
+    "cwd = os.path.abspath(os.curdir)\n",
+    "Schelde_turbidity_df_1 = pd.read_csv(cwd + \"/data/input/schelde/turbidity/df_1/Turbidity Scheldt.csv\")\n",
+    "\n",
+    "Schelde_turbidity_df_1.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "c023efd3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "latitude = Schelde_turbidity_df_1['latitude']\n",
+    "longitude = Schelde_turbidity_df_1['longitude']\n",
+    "turbidity = Schelde_turbidity_df_1['value']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f59e83a4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'turbidity')"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(latitude, turbidity)\n",
+    "#plt.xlim(586,700) \n",
+    "plt.title('Schelde Turbidity')\n",
+    "plt.xlabel('latitude')\n",
+    "plt.ylabel('turbidity')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "02398e90",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>latitude</th>\n",
+       "      <th>longitude</th>\n",
+       "      <th>value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>51.004325</td>\n",
+       "      <td>3.805347</td>\n",
+       "      <td>46.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>51.092564</td>\n",
+       "      <td>4.171004</td>\n",
+       "      <td>106.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>51.236968</td>\n",
+       "      <td>4.370562</td>\n",
+       "      <td>118.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>51.319507</td>\n",
+       "      <td>4.275884</td>\n",
+       "      <td>85.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>51.320855</td>\n",
+       "      <td>4.276312</td>\n",
+       "      <td>107.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    latitude  longitude  value\n",
+       "0  51.004325   3.805347   46.0\n",
+       "1  51.092564   4.171004  106.0\n",
+       "2  51.236968   4.370562  118.0\n",
+       "3  51.319507   4.275884   85.0\n",
+       "4  51.320855   4.276312  107.0"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Schelde_turbidity_df_1_med = Schelde_turbidity_df_1[['latitude', 'longitude', 'value']]\n",
+    "Schelde_turbidity_df_1_med.dropna()\n",
+    "\n",
+    "Schelde_turbidity_df_1_med = Schelde_turbidity_df_1_med.groupby('latitude', as_index=False).median() \n",
+    "\n",
+    "latitude_med = Schelde_turbidity_df_1_med['latitude']\n",
+    "turbidity_med = Schelde_turbidity_df_1_med['value']\n",
+    "\n",
+    "Schelde_turbidity_df_1_med"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "24f2c8c1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>latitude</th>\n",
+       "      <th>longitude</th>\n",
+       "      <th>value</th>\n",
+       "      <th>km from North Sea</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>51.004325</td>\n",
+       "      <td>3.805347</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>150</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>51.092564</td>\n",
+       "      <td>4.171004</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>104</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>51.236968</td>\n",
+       "      <td>4.370562</td>\n",
+       "      <td>118.0</td>\n",
+       "      <td>28.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>51.319507</td>\n",
+       "      <td>4.275884</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>42.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>51.320855</td>\n",
+       "      <td>4.276312</td>\n",
+       "      <td>107.0</td>\n",
+       "      <td>42.7</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    latitude  longitude  value km from North Sea\n",
+       "0  51.004325   3.805347   46.0               150\n",
+       "1  51.092564   4.171004  106.0               104\n",
+       "2  51.236968   4.370562  118.0              28.5\n",
+       "3  51.319507   4.275884   85.0              42.5\n",
+       "4  51.320855   4.276312  107.0              42.7"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "km_from_North_Sea = ['150', '104', '28.5', '42.5', '42.7'] #values measured on google maps\n",
+    "Schelde_turbidity_df_1_med['km from North Sea'] = km_from_North_Sea\n",
+    "km = Schelde_turbidity_df_1_med['km from North Sea']\n",
+    "value = Schelde_turbidity_df_1_med['value']\n",
+    "\n",
+    "Schelde_turbidity_df_1_med"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "3aab2ffc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Turbidity')"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# turbidity values from all years\n",
+    "plt.plot(km, value)\n",
+    "plt.gca().invert_xaxis()\n",
+    "plt.title('Schelde-- Median at km')\n",
+    "plt.xlabel('Kilometer from North Sea')\n",
+    "plt.ylabel('Turbidity')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8417f561",
+   "metadata": {},
+   "source": [
+    "## Schelde depth"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "85caf2c4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>km</th>\n",
+       "      <th>depth</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>11.400824</td>\n",
+       "      <td>8.621514</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13.912927</td>\n",
+       "      <td>9.181122</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>16.427276</td>\n",
+       "      <td>10.118064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>18.937997</td>\n",
+       "      <td>10.445467</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>21.450963</td>\n",
+       "      <td>11.150203</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          km      depth\n",
+       "0  11.400824   8.621514\n",
+       "1  13.912927   9.181122\n",
+       "2  16.427276  10.118064\n",
+       "3  18.937997  10.445467\n",
+       "4  21.450963  11.150203"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "schelde_depth_df_1 = pd.read_csv(cwd + \"/data/input/schelde/depth/df_1/Schelde depth.csv\")\n",
+    "\n",
+    "schelde_depth_df_1['km'] = schelde_depth_df_1['km'].astype(float)\n",
+    "schelde_depth_df_1.sort_values(by = 'km', inplace = True)\n",
+    "\n",
+    "schelde_depth_df_1.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "4a493afb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Depth')"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Stromkilometer_d = schelde_depth_df_1['km']\n",
+    "Depth = schelde_depth_df_1['depth']\n",
+    "schelde_depth_df_1\n",
+    "\n",
+    "# Depth plot\n",
+    "plt.plot(Stromkilometer_d, Depth)\n",
+    "#plt.gca().invert_xaxis()\n",
+    "plt.gca().invert_yaxis()\n",
+    "plt.title('Schelde Depth')\n",
+    "plt.xlabel('Kilometer')\n",
+    "plt.ylabel('Depth')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "ad29fb63",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# create figure and axis objects with subplots()\n",
+    "fig,ax1 = plt.subplots()\n",
+    "ax2 = ax1.twinx()\n",
+    "\n",
+    "# make a plot\n",
+    "ax1.plot(km, value, color=\"red\") # I can't figure out why the axes won't line up\n",
+    "ax2.plot(Stromkilometer_d, Depth, color=\"blue\")\n",
+    "\n",
+    "# x-axis\n",
+    "ax1.set_xlabel(\"Stromkilometer\", fontsize = 14)\n",
+    "#ax2.set_xlim(586,830) \n",
+    "#plt.xticks(np.arange(550, 850, step=50))\n",
+    "plt.gca().invert_xaxis()\n",
+    "\n",
+    "# y-axis labels\n",
+    "ax1.set_ylabel(\"Messwert\", color=\"red\", fontsize=14)\n",
+    "ax2.set_ylabel(\"Depth\",color=\"blue\",fontsize=14)\n",
+    "ax2.invert_yaxis()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "16991969",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dacced9d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/ipynb/Waterbase.ipynb b/ipynb/Waterbase.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..a767bb5efb0d866a35476195657abaa8fdf9f845
--- /dev/null
+++ b/ipynb/Waterbase.ipynb
@@ -0,0 +1,942 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "acec8070",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import glob\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "29ab3c2f",
+   "metadata": {},
+   "source": [
+    "## pre-processing waterbase dataset\n",
+    "includes data about many rivers throughout Europe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "982023de",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Hannah Russell\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3444: DtypeWarning: Columns (21,23,24,29) have mixed types.Specify dtype option on import or set low_memory=False.\n",
+      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>countryCode</th>\n",
+       "      <th>thematicIdIdentifier</th>\n",
+       "      <th>thematicIdIdentifierScheme</th>\n",
+       "      <th>monitoringSiteIdentifier</th>\n",
+       "      <th>monitoringSiteIdentifierScheme</th>\n",
+       "      <th>monitoringSiteName</th>\n",
+       "      <th>waterBodyIdentifier</th>\n",
+       "      <th>waterBodyIdentifierScheme</th>\n",
+       "      <th>waterBodyName</th>\n",
+       "      <th>specialisedZoneType</th>\n",
+       "      <th>...</th>\n",
+       "      <th>surfaceWaterBodyTypeCode</th>\n",
+       "      <th>subUnitIdentifier</th>\n",
+       "      <th>subUnitIdentifierScheme</th>\n",
+       "      <th>subUnitName</th>\n",
+       "      <th>rbdIdentifier</th>\n",
+       "      <th>rbdIdentifierScheme</th>\n",
+       "      <th>rbdName</th>\n",
+       "      <th>confidentialityStatus</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>lon</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>ALGW_011</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ALGW_011</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>1 -DOBRAC</td>\n",
+       "      <td>groundWaterBody</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>inapplicable</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>ALGW_021</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ALGW_021</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>50 BARBULLONJE</td>\n",
+       "      <td>groundWaterBody</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>inapplicable</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>ALGW_022</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ALGW_022</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>26 FUSHE KUQE</td>\n",
+       "      <td>groundWaterBody</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>inapplicable</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>ALGW_031</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ALGW_031</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>5 KRASTE -ELBASAN</td>\n",
+       "      <td>groundWaterBody</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>inapplicable</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>AL</td>\n",
+       "      <td>ALGW_034</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ALGW_034</td>\n",
+       "      <td>eionetGroundWaterBodyCode</td>\n",
+       "      <td>17 A VIDHAS</td>\n",
+       "      <td>groundWaterBody</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>inapplicable</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 22 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  countryCode thematicIdIdentifier thematicIdIdentifierScheme  \\\n",
+       "0          AL             ALGW_011  eionetGroundWaterBodyCode   \n",
+       "1          AL             ALGW_021  eionetGroundWaterBodyCode   \n",
+       "2          AL             ALGW_022  eionetGroundWaterBodyCode   \n",
+       "3          AL             ALGW_031  eionetGroundWaterBodyCode   \n",
+       "4          AL             ALGW_034  eionetGroundWaterBodyCode   \n",
+       "\n",
+       "  monitoringSiteIdentifier monitoringSiteIdentifierScheme monitoringSiteName  \\\n",
+       "0                      NaN                            NaN                NaN   \n",
+       "1                      NaN                            NaN                NaN   \n",
+       "2                      NaN                            NaN                NaN   \n",
+       "3                      NaN                            NaN                NaN   \n",
+       "4                      NaN                            NaN                NaN   \n",
+       "\n",
+       "  waterBodyIdentifier  waterBodyIdentifierScheme      waterBodyName  \\\n",
+       "0            ALGW_011  eionetGroundWaterBodyCode          1 -DOBRAC   \n",
+       "1            ALGW_021  eionetGroundWaterBodyCode     50 BARBULLONJE   \n",
+       "2            ALGW_022  eionetGroundWaterBodyCode      26 FUSHE KUQE   \n",
+       "3            ALGW_031  eionetGroundWaterBodyCode  5 KRASTE -ELBASAN   \n",
+       "4            ALGW_034  eionetGroundWaterBodyCode        17 A VIDHAS   \n",
+       "\n",
+       "  specialisedZoneType  ... surfaceWaterBodyTypeCode subUnitIdentifier  \\\n",
+       "0     groundWaterBody  ...                      NaN               NaN   \n",
+       "1     groundWaterBody  ...                      NaN               NaN   \n",
+       "2     groundWaterBody  ...                      NaN               NaN   \n",
+       "3     groundWaterBody  ...                      NaN               NaN   \n",
+       "4     groundWaterBody  ...                      NaN               NaN   \n",
+       "\n",
+       "  subUnitIdentifierScheme subUnitName rbdIdentifier rbdIdentifierScheme  \\\n",
+       "0                     NaN         NaN           NaN                 NaN   \n",
+       "1                     NaN         NaN           NaN                 NaN   \n",
+       "2                     NaN         NaN           NaN                 NaN   \n",
+       "3                     NaN         NaN           NaN                 NaN   \n",
+       "4                     NaN         NaN           NaN                 NaN   \n",
+       "\n",
+       "  rbdName confidentialityStatus lat lon  \n",
+       "0     NaN          inapplicable NaN NaN  \n",
+       "1     NaN          inapplicable NaN NaN  \n",
+       "2     NaN          inapplicable NaN NaN  \n",
+       "3     NaN          inapplicable NaN NaN  \n",
+       "4     NaN          inapplicable NaN NaN  \n",
+       "\n",
+       "[5 rows x 22 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "os.chdir(\"C:\\\\Users\\\\Hannah Russell\\\\north_sea_estuaries_visualisations\\\\\")\n",
+    "cwd = os.path.abspath(os.curdir)\n",
+    "\n",
+    "waterbase_sites = pd.read_csv(cwd + '/data/input/mixed/df_1/Waterbase_v2021_1_S_WISE6_SpatialObject_DerivedData.csv')\n",
+    "waterbase_agg = pd.read_csv(cwd + '/data/input/mixed/df_1/Waterbase_v2021_1_T_WISE6_AggregatedData.csv')\n",
+    "#waterbase_agg_by_wat = pd.read_csv('Waterbase_v2021_1_T_WISE6_AggregatedDataByWaterBody.csv')\n",
+    "\n",
+    "#waterbase_agg\n",
+    "waterbase_sites.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "afbd57d5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Hannah Russell\\anaconda3\\lib\\site-packages\\pandas\\util\\_decorators.py:311: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  return func(*args, **kwargs)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>monitoringSiteIdentifier</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>lon</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>AL011</td>\n",
+       "      <td>41.6856</td>\n",
+       "      <td>20.3489</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>AL013</td>\n",
+       "      <td>42.0420</td>\n",
+       "      <td>19.4910</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>AL014</td>\n",
+       "      <td>42.0990</td>\n",
+       "      <td>19.5530</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>AL015</td>\n",
+       "      <td>42.0540</td>\n",
+       "      <td>19.5290</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>AL017</td>\n",
+       "      <td>41.3500</td>\n",
+       "      <td>19.4000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   monitoringSiteIdentifier      lat      lon\n",
+       "10                    AL011  41.6856  20.3489\n",
+       "11                    AL013  42.0420  19.4910\n",
+       "12                    AL014  42.0990  19.5530\n",
+       "13                    AL015  42.0540  19.5290\n",
+       "14                    AL017  41.3500  19.4000"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "waterbase_sites_coord = waterbase_sites[['monitoringSiteIdentifier', 'lat', 'lon']] #these are the relevant columns\n",
+    "waterbase_sites_coord.dropna(inplace = True)\n",
+    "waterbase_sites_coord.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "df424c99",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Merge coordinates with df\n",
+    "#waterbase_agg.observedPropertyDeterminandLabel.unique()\n",
+    "waterbase_coord = waterbase_agg.merge(waterbase_sites_coord, how = 'left', left_on = 'monitoringSiteIdentifier', right_on = 'monitoringSiteIdentifier')\n",
+    "\n",
+    "# separate df for \n",
+    "chlor = waterbase_coord[waterbase_coord['observedPropertyDeterminandLabel'].str.contains('Chlorophyll a') == True]\n",
+    "#chlor\n",
+    "\n",
+    "turbidity = waterbase_coord[waterbase_coord['observedPropertyDeterminandLabel'].str.contains('Turbidity') == True]\n",
+    "#turbidity"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "2d41c3c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# All Elbe sites 250+ km upstream\n",
+    "Elbe_sites = waterbase_sites[waterbase_sites['waterBodyName'].str.contains('elbe ', case = False) == True]\n",
+    "Elbe_sites = Elbe_sites[Elbe_sites['countryCode'].str.contains('DE') == True]\n",
+    "Elbe_sites = Elbe_sites[['monitoringSiteIdentifier', 'lat', 'lon']]\n",
+    "#Elbe_sites\n",
+    "\n",
+    "\n",
+    "\n",
+    "Maas_sites = waterbase_sites[waterbase_sites['waterBodyName'].str.contains('maas', case = False) == True]\n",
+    "Maas_sites = Maas_sites[Maas_sites['countryCode'].str.contains('NL') == True]\n",
+    "Maas_sites = Maas_sites[['monitoringSiteIdentifier', 'lat', 'lon']]\n",
+    "Maas_sites_list = Maas_sites['monitoringSiteIdentifier'].dropna().values.tolist()\n",
+    "#Maas_sites\n",
+    "\n",
+    "Ems_sites = waterbase_sites[waterbase_sites['waterBodyName'].str.contains('ems ', case = False) == True]\n",
+    "Ems_sites = Ems_sites[['monitoringSiteIdentifier', 'lat', 'lon']]\n",
+    "Ems_sites_list = Ems_sites['monitoringSiteIdentifier'].dropna().values.tolist()\n",
+    "#Ems_sites"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "d382e12f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "7795cd08",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>monitoringSiteIdentifier</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>lon</th>\n",
+       "      <th>km_from_sea</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3881</th>\n",
+       "      <td>BEVL_VMM_154100</td>\n",
+       "      <td>51.35300</td>\n",
+       "      <td>4.24068</td>\n",
+       "      <td>54.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3882</th>\n",
+       "      <td>BEVL_VMM_162000</td>\n",
+       "      <td>51.14311</td>\n",
+       "      <td>4.33057</td>\n",
+       "      <td>86.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3883</th>\n",
+       "      <td>BEVL_VMM_164000</td>\n",
+       "      <td>51.04082</td>\n",
+       "      <td>4.12334</td>\n",
+       "      <td>116.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3884</th>\n",
+       "      <td>BEVL_VMM_168900</td>\n",
+       "      <td>51.00578</td>\n",
+       "      <td>3.80358</td>\n",
+       "      <td>147.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3885</th>\n",
+       "      <td>BEVL_VMM_172100</td>\n",
+       "      <td>51.00160</td>\n",
+       "      <td>3.72403</td>\n",
+       "      <td>162.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3886</th>\n",
+       "      <td>BEVL_VMM_173000</td>\n",
+       "      <td>50.89344</td>\n",
+       "      <td>3.68000</td>\n",
+       "      <td>178.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3887</th>\n",
+       "      <td>BEVL_VMM_174000</td>\n",
+       "      <td>50.87044</td>\n",
+       "      <td>3.62801</td>\n",
+       "      <td>183.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3888</th>\n",
+       "      <td>BEVL_VMM_179000</td>\n",
+       "      <td>50.70959</td>\n",
+       "      <td>3.36074</td>\n",
+       "      <td>212</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3908</th>\n",
+       "      <td>BEVL_VMM_351000</td>\n",
+       "      <td>51.06586</td>\n",
+       "      <td>4.36510</td>\n",
+       "      <td>Bosbeek</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3961</th>\n",
+       "      <td>BEVL_VMM_C05-181</td>\n",
+       "      <td>51.02646</td>\n",
+       "      <td>4.35861</td>\n",
+       "      <td>Zeekanal</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3965</th>\n",
+       "      <td>BEVL_VMM_C05-42</td>\n",
+       "      <td>51.14007</td>\n",
+       "      <td>4.32743</td>\n",
+       "      <td>86.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3966</th>\n",
+       "      <td>BEVL_VMM_C05-58</td>\n",
+       "      <td>50.95630</td>\n",
+       "      <td>3.65863</td>\n",
+       "      <td>170.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3977</th>\n",
+       "      <td>BEVL_VMM_C08-43</td>\n",
+       "      <td>51.29667</td>\n",
+       "      <td>4.29795</td>\n",
+       "      <td>62.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3979</th>\n",
+       "      <td>BEVL_VMM_C08-55</td>\n",
+       "      <td>50.71769</td>\n",
+       "      <td>3.36461</td>\n",
+       "      <td>211</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49218</th>\n",
+       "      <td>NL25_830002</td>\n",
+       "      <td>51.48858</td>\n",
+       "      <td>4.26269</td>\n",
+       "      <td>binnenschelde</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49531</th>\n",
+       "      <td>NL89_SCHAARVODDL</td>\n",
+       "      <td>51.35029</td>\n",
+       "      <td>4.25066</td>\n",
+       "      <td>55.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49536</th>\n",
+       "      <td>NL89_VLISSGBISSVH</td>\n",
+       "      <td>51.41199</td>\n",
+       "      <td>3.56562</td>\n",
+       "      <td>0.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49537</th>\n",
+       "      <td>NL89_WISSKKE</td>\n",
+       "      <td>51.60158</td>\n",
+       "      <td>3.72057</td>\n",
+       "      <td>Eastern Schelde</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      monitoringSiteIdentifier       lat      lon      km_from_sea\n",
+       "3881           BEVL_VMM_154100  51.35300  4.24068             54.5\n",
+       "3882           BEVL_VMM_162000  51.14311  4.33057             86.5\n",
+       "3883           BEVL_VMM_164000  51.04082  4.12334            116.8\n",
+       "3884           BEVL_VMM_168900  51.00578  3.80358            147.6\n",
+       "3885           BEVL_VMM_172100  51.00160  3.72403            162.5\n",
+       "3886           BEVL_VMM_173000  50.89344  3.68000            178.9\n",
+       "3887           BEVL_VMM_174000  50.87044  3.62801            183.8\n",
+       "3888           BEVL_VMM_179000  50.70959  3.36074              212\n",
+       "3908           BEVL_VMM_351000  51.06586  4.36510          Bosbeek\n",
+       "3961          BEVL_VMM_C05-181  51.02646  4.35861         Zeekanal\n",
+       "3965           BEVL_VMM_C05-42  51.14007  4.32743             86.8\n",
+       "3966           BEVL_VMM_C05-58  50.95630  3.65863            170.3\n",
+       "3977           BEVL_VMM_C08-43  51.29667  4.29795             62.7\n",
+       "3979           BEVL_VMM_C08-55  50.71769  3.36461              211\n",
+       "49218              NL25_830002  51.48858  4.26269    binnenschelde\n",
+       "49531         NL89_SCHAARVODDL  51.35029  4.25066             55.2\n",
+       "49536        NL89_VLISSGBISSVH  51.41199  3.56562              0.5\n",
+       "49537             NL89_WISSKKE  51.60158  3.72057  Eastern Schelde"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Schelde_sites = waterbase_sites[waterbase_sites['waterBodyName'].str.contains('scheld', case = False) == True]\n",
+    "Schelde_sites = Schelde_sites[['monitoringSiteIdentifier', 'lat', 'lon']]\n",
+    "Schelde_sites = Schelde_sites.dropna()\n",
+    "Schelde_sites_list = Schelde_sites['monitoringSiteIdentifier'].values.tolist()\n",
+    "#Schelde_sites\n",
+    "\n",
+    "Schelde_sites_km_from_North_Sea = ['54.5', '86.5', '116.8', '147.6', '162.5', '178.9', '183.8', '212', 'Bosbeek', 'Zeekanal', '86.8', '170.3', '62.7', '211', 'binnenschelde', '55.2', '0.5', 'Eastern Schelde']\n",
+    "\n",
+    "Schelde_sites['km_from_sea'] = Schelde_sites_km_from_North_Sea\n",
+    "Schelde_sites"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "e3f206da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Chlorophyll ug/L')"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot Schelde chlorophyll values\n",
+    "Schelde_chlor = chlor[chlor['monitoringSiteIdentifier'].str.contains(\"|\".join(Schelde_sites_list))]\n",
+    "#Schelde_chlor\n",
+    "\n",
+    "sch_lat = Schelde_chlor['lat']\n",
+    "sch_value = Schelde_chlor['resultMeanValue']\n",
+    "\n",
+    "# plot of all cholorphyll values from all years on one plot\n",
+    "plt.scatter(sch_lat, sch_value)\n",
+    "plt.title('Schelde-- All Years')\n",
+    "plt.xlabel('lat')\n",
+    "plt.ylabel('Chlorophyll ug/L')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "89c75c78",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Turbidity')"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot Schelde turbidity values (apparently there are none)\n",
+    "Schelde_turb = turbidity[turbidity['monitoringSiteIdentifier'].str.contains(\"|\".join(Schelde_sites_list))]\n",
+    "Schelde_turb\n",
+    "\n",
+    "sch_t_lat = Schelde_turb['lat']\n",
+    "sch_t_value = Schelde_turb['resultMeanValue']\n",
+    "\n",
+    "# plot of all turbidity values from all years on one plot\n",
+    "plt.scatter(sch_t_lat, sch_t_value)\n",
+    "plt.title('Schelde-- All Years')\n",
+    "plt.xlabel('lat')\n",
+    "plt.ylabel('Turbidity')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "01069ee5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Chlorophyll ug/L')"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Schelde_c_avg = Schelde_chlor.groupby('monitoringSiteIdentifier').median()\n",
+    "Schelde_c_avg\n",
+    "# NL89_SCHAARVODDL is 55.43 km from the Sea\n",
+    "\n",
+    "# Chlorophyll values from all years\n",
+    "lat_a = Schelde_c_avg['lat']\n",
+    "Schelde_chlor_a = Schelde_c_avg['resultMeanValue']\n",
+    "plt.plot(lat_a, Schelde_chlor_a)\n",
+    "plt.title('Schelde')\n",
+    "plt.xlabel('lat')\n",
+    "plt.ylabel('Chlorophyll ug/L')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8cf6b830",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# extract Maas sites from chlor\n",
+    "Maas_chlor = chlor_cd[chlor_cd['monitoringSiteIdentifier'].str.contains(\"|\".join(Maas_sites_list))]\n",
+    "Maas_chlor\n",
+    "\n",
+    "Maas_avg = Maas_chlor.groupby('monitoringSiteIdentifier').median()\n",
+    "Maas_avg\n",
+    "# NL89_SCHAARVODDL is 55.43 km from the Sea\n",
+    "\n",
+    "maas_lat = Maas_chlor['lat']\n",
+    "maas_value = Maas_chlor['resultMeanValue']\n",
+    "\n",
+    "# plot of all cholorphyll values from all years on one plot\n",
+    "plt.scatter(maas_lat, maas_value)\n",
+    "plt.title('Maas-- All Years')\n",
+    "plt.xlabel('lat')\n",
+    "plt.ylabel('Chlorophyll ug/L')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "189866c7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Maas_c_avg = Maas_chlor.groupby('monitoringSiteIdentifier').median()\n",
+    "Maas_c_avg\n",
+    "\n",
+    "# Chlorophyll values from all years\n",
+    "Maas_lat_a = Maas_c_avg['lat']\n",
+    "Maas_chlor_a = Maas_c_avg['resultMeanValue']\n",
+    "plt.plot(Maas_lat_a, Maas_chlor_a)\n",
+    "plt.title('Maas')\n",
+    "plt.xlabel('lat')\n",
+    "plt.ylabel('Chlorophyll ug/L')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2b5b014b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "01bd2618",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a1771f99",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "42404b8c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2fdbd01e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ba09097",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "74b79b27",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ef7140eb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2a83d37d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a038a72c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c9523149",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "61571384",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# extract Ems sites from chlor\n",
+    "Ems_chlor = chlor_cd[chlor_cd['monitoringSiteIdentifier'].str.contains(\"|\".join(Ems_sites_list))]\n",
+    "Ems_chlor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "78ad3173",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c3f59cbb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}