{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8c62ee6f",
   "metadata": {},
   "source": [
    "# Groundwater monitoring network (GMN)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb7fa509",
   "metadata": {},
   "source": [
    "In this example we download the metadata for the wells in the Groundwater Monitoring Network of Oudewater (BRO ID: GMN000000003996)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "25789435",
   "metadata": {},
   "outputs": [],
   "source": [
    "import brodata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ce89266",
   "metadata": {},
   "source": [
    "First, request the GroundwaterMonitoringNetwork object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b8b7d87",
   "metadata": {},
   "outputs": [],
   "source": [
    "gmn = brodata.gmn.GroundwaterMonitoringNetwork.from_bro_id(\"GMN000000003996\")\n",
    "gmn"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "563e50e8",
   "metadata": {},
   "source": [
    "The `measuringPoint` attribute contains the BRO IDs of all Groundwater Monitoring Wells in this network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "862eab6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "gmn.measuringPoint"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9275fd78",
   "metadata": {},
   "source": [
    "The gmn-object also contains some metadata, for example the name of the network and the monitoring-purpose."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b248a139",
   "metadata": {},
   "outputs": [],
   "source": [
    "gmn_data = gmn.to_dict()\n",
    "gmn_data.pop(\"measuringPoint\")\n",
    "gmn_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d5cb7ef",
   "metadata": {},
   "source": [
    "To retrieve detailed information for the wells, download them with `brodata.gmw.get_data_for_bro_ids` (this may take time). The method returns a dictionary keyed by BRO ID with GroundwaterMonitoringWell objects as values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbe85810",
   "metadata": {},
   "outputs": [],
   "source": [
    "gmw_ids = gmn.measuringPoint.index.levels[0].unique()\n",
    "gmws = brodata.gmw.get_data_for_bro_ids(gmw_ids)\n",
    "gmws"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f5137cd",
   "metadata": {},
   "source": [
    "We want to plot them on a map, so we transform this dictionary to a GeoDataFrame using the method `brodata.bro.objects_to_gdf`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01b378b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf = brodata.bro.objects_to_gdf(gmws)\n",
    "gdf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fd8c27b",
   "metadata": {},
   "source": [
    "Finally, plot these wells on an interactive map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "289778d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import folium\n",
    "tooltip = [\"broId\",\"wellCode\", \"groundLevelPosition\", \"wellConstructionDate\", \"numberOfMonitoringTubes\"]\n",
    "m = gdf.explore(tooltip=tooltip)\n",
    "m"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}