Boreholes
This notebook shows how to plot borehole data along with a groundwater measurement well.
Two different packages are used:
brodata, to obtain and visualise borehole data from the BRO databasegeostto get Bodemkundig booronderzoek from the BRO database
[1]:
import brodata
import contextily as ctx
import geopandas as gpd
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from shapely.geometry import LineString, Point
import hydropandas as hpd
[2]:
# reading data from a groundwatermonitoring well (see notebook 01)
gw_bro = hpd.GroundwaterObs.from_bro("GMW000000041261", 1)
Borehole (Brodata)
[3]:
# select extent with a buffer around gw_bro
p = Point(gw_bro.x, gw_bro.y)
extent = np.array(p.buffer(1000).bounds).astype(int)[[0, 2, 1, 3]]
# get bro ids of borehole data
gdf = brodata.bhr.get_characteristics(extent=extent)
[4]:
# plot borehole data
f, axes = plt.subplots(ncols=2, figsize=(16, 8))
gdf["broid"] = gdf.index.str[-7:]
gdf["x"] = gdf.geometry.x
gdf = gdf.sort_values("x")
gdf["geometry"] = gdf.geometry
line = LineString(gdf["deliveredLocation"].values)
distance_along_line = pd.Series(
[line.project(point) for point in gdf["geometry"]], gdf.index
)
# plot values
xticks = []
xticklabels = []
for bro_id in gdf.index:
bhrgt = brodata.bhr.GeotechnicalBoreholeResearch.from_bro_id(bro_id)
for x, bl in enumerate(bhrgt.descriptiveBoreholeLog):
brodata.plot.bro_lithology_advanced(
bl["layer"],
x=distance_along_line[bro_id],
z=bhrgt.offset,
width=80,
bro_id=bro_id,
ax=axes[0],
)
xticks.append(distance_along_line[bro_id])
xticklabels.append(bro_id[-7:])
axes[0].set_xlim(min(distance_along_line) - 80, max(distance_along_line) + 80)
axes[0].set_xticks(xticks)
axes[0].set_xticklabels(xticklabels, rotation=45, ha="right")
axes[0].set_ylim(3, gdf["offset"].astype(float).max() + 0.5)
axes[0].set_ylabel("z (m t.o.v. NAP)")
# plot map
# plot well
axes[1].scatter(gw_bro.x, gw_bro.y, color="black")
axes[1].annotate(gw_bro.name, (gw_bro.x + 25, gw_bro.y + 10))
# plot boreholes
legend_labels = gdf["broid"].tolist()
gdf.plot("broid", ax=axes[1], legend=True)
# plot line
gpd.GeoDataFrame(geometry=[line]).plot(ax=axes[1])
# settings
axes[1].set_xlim(extent[:2])
axes[1].set_ylim(extent[2:])
# basemap
ctx.add_basemap(axes[1], crs=28992)
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag determinationProcedure not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag determinationMethod not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag fractionDistribution not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag dispersionMethod not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag removedMaterial not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag equivalentMassDeterminationMethod not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag equivalentMass not supported in GeotechnicalBoreholeResearch BHR000000348833
Tag basicParticleSizeDistribution not supported in GeotechnicalBoreholeResearch BHR000000348833
SoilName sterkZandigSilt not supported (found at broId BHR000000348833). Please add sterkZandigSilt to lithology_properties.
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348807
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348807
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348866
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348866
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348629
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Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348867
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348867
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348683
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348683
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348675
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348675
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348869
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348869
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348801
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348801
Tag meanHighestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348684
Tag meanLowestGroundwaterLevel not supported in GeotechnicalBoreholeResearch BHR000000348684
Bodemkundig booronderzoek (geost)
The geost package can only be pip installed for python version 3.12 or higher. Install it using:
pip install geost
[5]:
!pip install geost
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[6]:
import geost
/home/docs/checkouts/readthedocs.org/user_builds/hydropandas/envs/stable/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
from .autonotebook import tqdm as notebook_tqdm
[7]:
# get Bodemkundig booronderzoek (BHR-GT)
boreholes = geost.bro_api_read("BHR-GT", bbox=[int(i) for i in p.buffer(1000).bounds])
[8]:
# add colors based on column 'standard_name'
# specify colors
colors = brodata.plot.lithology_colors.copy()
colors_rgb = {}
for soil, color in colors.items():
colors_rgb[soil] = tuple((np.array(color) * 255).astype(int))
colors_rgb["sterkZandigSilt"] = (243, 225, 100)
colors_rgb["siltigZandMetGrind"] = (220, 200, 80)
colors_rgb["siltigZand"] = (243, 225, 150)
colors_rgb["zwakGrindigZand"] = (231, 210, 70)
col = "geotechnicalSoilName" # "standardSoilName"
boreholes.data["color"] = boreholes.data[col].map(colors_rgb)
# plot borehole data
f, axes = plt.subplots(figsize=(16, 8), ncols=2)
labels = []
for i, (xy, df) in enumerate(boreholes.data.groupby("x")):
df["top"] = df["surface"] - df["top"]
df["bottom"] = df["surface"] - df["bottom"]
for _, row in df.iterrows():
color = [c / 255 for c in row["color"]] + [1.0]
if row[col] in labels:
axes[0].fill_between(
[i - 0.25, i + 0.25],
[row["top"], row["top"]],
[row["bottom"], row["bottom"]],
color=color,
)
else:
axes[0].fill_between(
[i - 0.25, i + 0.25],
[row["top"], row["top"]],
[row["bottom"], row["bottom"]],
color=color,
label=row[col],
)
labels.append(row[col])
axes[0].set_xticks(np.arange(0, i + 1), boreholes.data.sort_values("x")["nr"].unique())
# Rotate and align the xtick labels
for label in axes[0].get_xticklabels():
label.set_rotation(45)
label.set_ha("right")
axes[0].set_ylabel("m NAP") # assuming that the level is in m NAP
axes[0].set_xlim(-0.5, i + 1.5)
axes[0].legend()
axes[0].set_title(f"Bodemkundig booronderzoek close to {gw_bro.name}")
# plot map
# plot well
axes[1].scatter(gw_bro.x, gw_bro.y, label=gw_bro.name, color="black")
# plot boreholes
for i, dfnr in boreholes.data.groupby(["x", "y"]):
axes[1].scatter(*i, label=dfnr["nr"].unique()[0])
# settings
axes[1].set_xlim(extent[:2])
axes[1].set_ylim(extent[2:])
axes[1].legend()
# basemap
ctx.add_basemap(axes[1], crs=28992)
