Groundwater Production Dossier (GPD)

A Groundwater Production Dossier contains the production figures of a groundwater use system.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import brodata

gpd = brodata.gpd.GroundwaterProductionDossier.from_bro_id("GPD000000012107")
gpd

GroundwaterProductionDossier(broId='GPD000000012107')

There are multiple reports in this Groundwater Production Dossier, where each report contains multiple volume-registrations. The metadata of the reports are contained in the attribute report, and the volumes are contained in the attribute volumeSeries. These two pandas DataFrames are linked to eachother by the column reportId.

gpd.report

	method	beginDate	endDate
reportId
598916	onbekend	2019-01-01	2019-12-31
599120	onbekend	2021-01-01	2021-12-31
599372	onbekend	2020-01-01	2020-12-31
599600	onbekend	2024-01-01	2024-12-31
599716	onbekend	2023-01-01	2023-12-31

Show the volume-series

gpd.volumeSeries

	beginDate	endDate	waterInOut	volume	reportId	temperatureIn
0	2019-01-01	2019-01-31	onttrokken	16867	598916	NaN
1	2019-02-01	2019-02-28	onttrokken	17230	598916	NaN
2	2019-03-01	2019-03-31	onttrokken	14377	598916	NaN
3	2019-04-01	2019-04-30	onttrokken	16253	598916	NaN
4	2019-05-01	2019-05-31	onttrokken	15115	598916	NaN
...	...	...	...	...	...	...
235	2023-08-01	2023-08-31	ingebracht	0	599716	warm
236	2023-09-01	2023-09-30	ingebracht	0	599716	warm
237	2023-10-01	2023-10-31	ingebracht	0	599716	warm
238	2023-11-01	2023-11-30	ingebracht	0	599716	warm
239	2023-12-01	2023-12-31	ingebracht	0	599716	warm

240 rows × 6 columns

Plot the volume series and separate volumes by the waterInOut attribute; for injections, further separate by temperatureIn.

f, ax = plt.subplots(figsize=(10, 6))
ax.axhline(0, color="black", lw=0.5)
for waterInOut in gpd.volumeSeries["waterInOut"].unique():
    maskInOut = gpd.volumeSeries["waterInOut"] == waterInOut
    for temperatureIn in gpd.volumeSeries.loc[maskInOut, "temperatureIn"].unique():
        if pd.isna(temperatureIn):
            maskTemperatureIn = gpd.volumeSeries["temperatureIn"].isna()
            label = f"{waterInOut}"
        else:
            maskTemperatureIn = gpd.volumeSeries["temperatureIn"] == temperatureIn
            label = f"{waterInOut} - {temperatureIn}"
        mask = maskInOut & maskTemperatureIn
        df = gpd.volumeSeries.loc[mask]

        # sort by the column `beginDate`
        df = df.sort_values("beginDate")

        # make a matplotlib plot of the volume series, with a constant value between beginDate and endDate
        x = df.loc[:, ["beginDate", "endDate"]].values.ravel()

        y = np.vstack((df["volume"].values, df["volume"].values)).transpose().ravel()
        if waterInOut == "onttrokken":
            y = -y

        # make sure to draw a line between the endDate of one row and the beginDate of the next row if they are not consecutive
        mask = (
            df["endDate"].values[:-1] + pd.Timedelta(1, "D")
            != df["beginDate"].values[1:]
        )
        ind = ((np.where(mask)[0] + 1) * 2).tolist()
        ind = [0] + ind + [len(x)]

        # get next color from the color cycle
        color = ax._get_lines.get_next_color()
        for i in range(len(ind) - 1):
            ax.plot(
                x[ind[i] : ind[i + 1]],
                y[ind[i] : ind[i + 1]],
                label=label if i == 0 else None,
                color=color,
            )

ax.set_xlim(gpd.volumeSeries["beginDate"].min(), gpd.volumeSeries["endDate"].max())
ax.legend();

Show the rest of the contents of the Groundwater Production Dossier.

gpd_data = gpd.to_dict()
gpd_data.pop("report")
gpd_data.pop("volumeSeries")
gpd_data

{'GroundwaterUsageFacility': 'GUF000000022602',
 'broId': 'GPD000000012107',
 'corrected': 'nee',
 'deliveryAccountableParty': '51468751',
 'deregistered': 'nee',
 'endTime': '2024-12-31',
 'id': 'BRO_0011',
 'latestAdditionTime': '2025-04-07T10:12:15+02:00',
 'objectRegistrationTime': '2025-04-03T14:12:11+02:00',
 'qualityRegime': 'IMBRO/A',
 'registrationStatus': 'aangevuld',
 'reregistered': 'nee',
 'startTime': '2019-01-01',
 'underReview': 'nee'}