From 595390422f94ddc0e0297c4e3236993bd3fea981 Mon Sep 17 00:00:00 2001 From: valentijn7 Date: Tue, 17 Dec 2024 00:00:25 +0100 Subject: [PATCH] Matched DNH stations to gauges --- .../data/mappings/DNH_to_gauge.json | 16 + GoogleFloodHub/src/GRRR.ipynb | 288 ++++++++++++------ 2 files changed, 210 insertions(+), 94 deletions(-) create mode 100644 GoogleFloodHub/data/mappings/DNH_to_gauge.json diff --git a/GoogleFloodHub/data/mappings/DNH_to_gauge.json b/GoogleFloodHub/data/mappings/DNH_to_gauge.json new file mode 100644 index 0000000..b1b7d6d --- /dev/null +++ b/GoogleFloodHub/data/mappings/DNH_to_gauge.json @@ -0,0 +1,16 @@ +{ + "Guelelinkoro": "ds_reforecast_1121939410", + "Banankoro": "ds_reforecast_1120748680", + "Bamako": "ds_reforecast_1120714900", + "Koulikoro": "ds_reforecast_1120705070", + "Mopti": "ds_reforecast_1120641660", + "Dire": "ds_reforecast_1121862050", + "Ansongo ": "ds_reforecast_1120599600", + "Gao": "ds_reforecast_1120577750", + "Sofara": "ds_reforecast_1120659990", + "Douna": "ds_reforecast_1120690000", + "Bougouni": "ds_reforecast_1120761040", + "Pankourou": "ds_reforecast_1120758950", + "Kayes": "ds_reforecast_1120644270", + "Bafing Makana": "ds_reforecast_1120718150" +} \ No newline at end of file diff --git a/GoogleFloodHub/src/GRRR.ipynb b/GoogleFloodHub/src/GRRR.ipynb index 0cdcd7b..3905789 100644 --- a/GoogleFloodHub/src/GRRR.ipynb +++ b/GoogleFloodHub/src/GRRR.ipynb @@ -35,7 +35,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -59,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -69,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -97,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -128,7 +128,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -137,7 +137,7 @@ "\" comment-block (4)\\nimport os\\n\\nlocal_directory = '/content/gauge_data'\\nif not os.path.exists(local_directory):\\n os.makedirs(local_directory)\\n # for every hybas: get data and store locally\\ncount = 0 # in the directory /gauge_data/\\nexpected_count = len(Mali_hybases * 3)\\nfor hybas_id in Mali_hybases:\\n try:\\n gauge_reforecast_ds = reforecast_ds.sel(gauge_id = hybas_id).compute()\\n gauge_reanalysis_ds = reanalysis_ds.sel(gauge_id = hybas_id).compute()\\n gauge_return_periods_ds = return_periods_ds.sel(gauge_id = hybas_id).compute()\\n\\n reforecast_file = f'{local_directory}/{hybas_id}_reforecast_ds.nc'\\n reanalysis_file = f'{local_directory}/{hybas_id}_reanalysis_ds.nc'\\n return_periods_file = f'{local_directory}/{hybas_id}_return_periods_ds.nc'\\n\\n gauge_reforecast_ds.to_netcdf(reforecast_file)\\n gauge_reanalysis_ds.to_netcdf(reanalysis_file)\\n gauge_return_periods_ds.to_netcdf(return_periods_file)\\n\\n # check whether export OK\\n for file_path in [reforecast_file, reanalysis_file, return_periods_file]:\\n if os.path.exists(file_path):\\n file_size = os.path.getsize(file_path)\\n if file_size > 0:\\n count += 1\\n else:\\n print(f'Warning: {file_path} is empty')\\n else:\\n print(f'Error: file {file_path} not found after saving')\\n print(f'progress: {count}/{expected_count}, {count/expected_count * 100:.2f}%, countMOD3 = {count % 3}')\\n except Exception as exc:\\n print(f'An error occurred while processing {hybas_id}: {exc}')\\n\\nprint(f'\\n[actual/expected] downloaded files: {count}/{expected_count}')\\n\\nfrom google.colab import files\\nzip_file = 'gauge_data.zip'\\n\\nif os.path.exists(local_directory):\\n print(f'Compressing files in {local_directory} into {zip_file}...')\\n !zip -r {zip_file} {local_directory}\\n print(f'Compression complete: {zip_file}')\\nelse:\\n print(f'Error: the directory {local_directory} does not exist')\\n\\nif os.path.exists(zip_file): # download .zip file\\n files.download(zip_file)\\n\"" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -445,7 +445,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -492,7 +492,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -503,7 +503,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -517,7 +517,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -534,7 +534,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -565,7 +565,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -622,19 +622,9 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Caching the list of root modules, please wait!\n", - "(This will only be done once - type '%rehashx' to reset cache!)\n", - "\n" - ] - }, { "data": { "image/png": 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", @@ -656,7 +646,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -680,7 +670,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -698,7 +688,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -716,7 +706,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -1099,7 +1089,7 @@ " return_period_25 float64 ...\n", " return_period_5 float64 4.392e+03\n", " return_period_50 float64 ...\n", - " return_period_7 float64 ..." + " return_period_7 float64 ..." ], "text/plain": [ "\n", @@ -1119,7 +1109,7 @@ " return_period_7 float64 ..." ] }, - "execution_count": 16, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1130,7 +1120,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -1505,17 +1495,17 @@ " * time (time) datetime64[ns] 1980-01-01 1980-01-02 ... 2023-12-23\n", " gauge_id object ...\n", "Data variables:\n", - " streamflow (time) float32 ...
  • " ], "text/plain": [ "\n", @@ -1527,7 +1517,7 @@ " streamflow (time) float32 ..." ] }, - "execution_count": 17, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -1538,7 +1528,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -1687,7 +1677,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -1856,7 +1846,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -1909,7 +1899,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -2295,21 +2285,21 @@ " RP_20: 376.69343279034223\n", " pc_95th: 39.41727371215819\n", " pc_98th: 78.35467834472658\n", - " pc_99th: 116.63700698852435
  • RP_1.5 :
    89.75050452923384
    RP_2 :
    132.8784961487048
    RP_5 :
    239.01527224744933
    RP_7 :
    273.65214805644086
    RP_10 :
    309.28705329043413
    RP_20 :
    376.69343279034223
    pc_95th :
    39.41727371215819
    pc_98th :
    78.35467834472658
    pc_99th :
    116.63700698852435
  • " ], "text/plain": [ "\n", @@ -2332,7 +2322,7 @@ " pc_99th: 116.63700698852435" ] }, - "execution_count": 21, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -2343,7 +2333,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "metadata": {}, "outputs": [ { @@ -2377,7 +2367,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -2401,7 +2391,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ @@ -2431,7 +2421,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -2459,7 +2449,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -2493,7 +2483,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ @@ -2502,7 +2492,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -2590,7 +2580,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -2748,7 +2738,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -2760,7 +2750,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 32, "metadata": {}, "outputs": [], "source": [ @@ -2786,7 +2776,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -2824,7 +2814,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ @@ -2849,42 +2839,7 @@ }, { "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "# now, we match each DNH station to the closest gauge, and create a\n", - "# dictionary with the DNH station names as keys and the gauge IDs as values\n", - "from typing import Dict\n", - "import numpy as np\n", - "import pandas as pd\n", - "import xarray as xr\n", - "from scipy.spatial import cKDTree\n", - "\n", - "#! Test of ie werkt\n", - "def match_DNH_stations_to_gauges_optimized(\n", - " df_DNH: pd.DataFrame,\n", - " dict_gauges: Dict[str, xr.Dataset]\n", - ") -> Dict[str, str]:\n", - " \"\"\"\n", - " Match DNH stations to the closest gauges using a KDTree O(NlogN)\n", - "\n", - " :param df_DNH: DataFrame with the DNH station coordinates\n", - " :param dict_gauges: the dictionary with gauge datasets\n", - " :return: mapping of DNH to closest gauge\n", - " \"\"\"\n", - " tree = cKDTree(np.array([\n", - " [dict_gauges[gauge_id].attrs['latitude'], dict_gauges[gauge_id].attrs['longitude']]\n", - " for gauge_id in list(dict_gauges.keys())\n", - " ]))\n", - " _, indices = tree.query(df_DNH[['latitude', 'longitude']].to_numpy(), k = 1)\n", - " closest_gauges = [list(dict_gauges.keys())[idx] for idx in indices]\n", - " return dict(zip(df_DNH['name'], closest_gauges))" - ] - }, - { - "cell_type": "code", - "execution_count": 37, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -2896,7 +2851,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -3027,7 +2982,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 37, "metadata": {}, "outputs": [ { @@ -3053,6 +3008,151 @@ "plot_admin_units_with_gauges(dict_datasets, True, True, True, df_DNH_station_coords)" ] }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.10742169499207668 8\n", + "0.4753392057232792 5\n", + "0.2457807101039993 14\n", + "0.03449738315173928 4\n", + "Found verified gauge within radius\n", + "0.01784665487316949 0\n", + "Found verified gauge within radius\n", + "1.95459135805788 0\n", + "4.841400396485587 0\n", + "4.5137006369948285 0\n", + "0.3504258445207779 9\n", + "0.4097068968517104 2\n", + "0.8689297362499578 7\n", + "0.022284609866926815 7\n", + "Found verified gauge within radius\n", + "3.9100056252152067 14\n", + "2.031123340079459 5\n" + ] + }, + { + "data": { + "text/plain": [ + "{'Guelelinkoro': 'ds_reforecast_1121939410',\n", + " 'Banankoro': 'ds_reforecast_1120748680',\n", + " 'Bamako': 'ds_reforecast_1120714900',\n", + " 'Koulikoro': 'ds_reforecast_1120705070',\n", + " 'Mopti': 'ds_reforecast_1120641660',\n", + " 'Dire': 'ds_reforecast_1121862050',\n", + " 'Ansongo ': 'ds_reforecast_1120599600',\n", + " 'Gao': 'ds_reforecast_1120577750',\n", + " 'Sofara': 'ds_reforecast_1120659990',\n", + " 'Douna': 'ds_reforecast_1120690000',\n", + " 'Bougouni': 'ds_reforecast_1120761040',\n", + " 'Pankourou': 'ds_reforecast_1120758950',\n", + " 'Kayes': 'ds_reforecast_1120644270',\n", + " 'Bafing Makana': 'ds_reforecast_1120718150'}" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# we match DNH stations to either a verified unit within a radius of\n", + "# 10 km, or else, to the closest gauge available. We export a mapping.\n", + "from scipy.spatial import cKDTree\n", + "import json\n", + "\n", + "\n", + "def haversine(\n", + " lon1: float, lat1: float, lon2: float, lat2: float\n", + " ) -> float:\n", + " \"\"\"\n", + " Calculate the great circle distance between two points\n", + " on the earth (specified in decimal degrees);\n", + " https://stackoverflow.com/questions/4913349/haversine-formula\n", + " -in-python-bearing-and-distance-between-two-gps-points\n", + "\n", + " :param lon1: longitude of point 1\n", + " :param lat1: latitude of point 1\n", + " :param lon2: longitude of point 2\n", + " :param lat2: latitude of point 2\n", + " :return: distance in km\n", + " \"\"\"\n", + " lon1, lat1, lon2, lat2 = map(np.radians, [lon1, lat1, lon2, lat2])\n", + " dlon = lon2 - lon1\n", + " dlat = lat2 - lat1\n", + " a = np.sin(dlat / 2)**2 + np.cos(lat1) * \\\n", + " np.cos(lat2) * np.sin(dlon / 2)**2\n", + " c = 2 * np.arcsin(np.sqrt(a))\n", + " return 6367 * c\n", + "\n", + "\n", + "def match_DNH_stations_to_gauges(\n", + " df_DNH: pd.DataFrame,\n", + " dict_gauges: Dict[str, xr.Dataset],\n", + " radius: int = 10\n", + " ) -> Dict[str, str]:\n", + " \"\"\"\n", + " Match DNH stations to the closest gauges using a KDTree O(NlogN)\n", + " if no verified gauge is available within a radius of 10 km\n", + "\n", + " :param df_DNH: DataFrame with the DNH station coordinates\n", + " :param dict_gauges: the dictionary with gauge datasets\n", + " :param radius: the radius to search for verified gauges\n", + " :return: mapping of DNH to closest gauge\n", + " \"\"\"\n", + " verified_gauges = [gauge_id for gauge_id, ds in dict_gauges.items() \\\n", + " if ds.attrs['qualityVerified'] == True]\n", + " verified_tree = cKDTree(np.array([\n", + " [dict_gauges[g].attrs['latitude'], dict_gauges[g].attrs['longitude']] \\\n", + " for g in verified_gauges\n", + " ]))\n", + " # for every DNH station, see if a gauge is within 10 km radius by calculating th\n", + " # radius of a 10 km circle (without adjusting for the earth's curvature) and then\n", + " # seeing if there is a verified gauge within that Euclidian distance. If not, just\n", + " # pick the closest one from the normal Tree\n", + " all_gauges = list(dict_gauges.keys())\n", + " normal_tree = cKDTree(np.array([\n", + " [dict_gauges[g].attrs['latitude'], dict_gauges[g].attrs['longitude']] \\\n", + " for g in all_gauges\n", + " ]))\n", + " \n", + " mapping = {}\n", + " for _, row in df_DNH.iterrows():\n", + " coords = np.array([row['latitude'], row['longitude']])\n", + " distances, idx = verified_tree.query(coords, k = 1)\n", + " print(distances, idx)\n", + "\n", + " g_id = verified_gauges[idx]\n", + " lat = dict_gauges[verified_gauges[idx]].attrs['latitude']\n", + " lon = dict_gauges[verified_gauges[idx]].attrs['longitude']\n", + " dist_km = haversine(lon, lat, row['longitude'], row['latitude'])\n", + "\n", + " if dist_km <= radius:\n", + " closest_gauge_id = g_id\n", + " print('Found verified gauge within radius')\n", + " else:\n", + " _, idx = normal_tree.query(coords, k = 1)\n", + " closest_gauge_id = all_gauges[idx]\n", + "\n", + " mapping[row['name']] = closest_gauge_id\n", + "\n", + " with open('../data/mappings/DNH_to_gauge.json', 'w') as f:\n", + " json.dump(mapping, f, indent = 4)\n", + "\n", + " return mapping\n", + "\n", + "\n", + "mapping = match_DNH_stations_to_gauges(df_DNH_station_coords, dict_datasets)\n", + "mapping\n", + "\n", + "#! TODO plot which ones found a gauge within radius and which ones did not" + ] + }, { "cell_type": "code", "execution_count": 40,