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Data, model ensemble and code for "Hydraulic heads reveal the flow-controlled organization of nitrate persistence in a fractured aquifer of southern India"
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| Created: | Oct 28, 2026 at 9:51 p.m. (UTC) | |
| Last updated: | Nov 12, 2026 at 3:45 p.m. (UTC) (Metadata update) | |
| Published date: | Nov 12, 2026 at 3:45 p.m. (UTC) | |
| DOI: | 10.4211/hs.c04bfe8ee040479b9b521065517eb427 | |
| Citation: | See how to cite this resource | |
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| Sharing Status: | Published |
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Abstract
Observations, groundwater model ensemble and code for Bhaduri et al. (Hydrogeology Journal). Hydraulic conductivity, recharge and pumping of the fractured granite-gneiss aquifer of the Berambadi catchment (Kabini Critical Zone Observatory, Karnataka, India) were estimated from 44 December 2018 heads with FEFLOW 10 and PESTPP-IES. The resource holds the calibration heads, monthly depth to water of the Berambadi network (2010–2021), regional South Gundal heads (2009–2023), nitrate and major-ion surveys (2012–2020), camera fracture logs of 84 boreholes (2025–2026), GIS layers, the FEFLOW models, prior and posterior parameter ensembles, flow solutions for three recharge-pumping structures, and Python and MATLAB scripts that reproduce all statistics and figures.
Subject Keywords
Coverage
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Content
README.md
Data, model ensemble and code for "Hydraulic heads reveal the flow-controlled organization of nitrate persistence in a fractured aquifer of southern India"
Resource authors: Baibaswata Bhaduri, Laurent Ruiz, Jean Riotte and Sekhar Muddu. Paper: Bhaduri, Kuppel, Ruiz, Hrachowitz, Riotte and Muddu, Hydrogeology Journal (manuscript HYJO-D-26-00493). Contact: Baibaswata Bhaduri (bbhaduri@ucdavis.edu).
Summary
This resource contains the observations, the groundwater model ensemble and the code behind the paper. Hydraulic conductivity in three directions, recharge and pumping were estimated from 44 December 2018 heads in the Berambadi aquifer (South Gundal basin, Karnataka, India) with FEFLOW 10.0 and PESTPP-IES (an iterative ensemble smoother). The posterior Darcy-flux fields were then tested against nitrate surveys and borehole-fracture imagery that were not used in calibration. The persistent nitrate hotspot lies in a low-flow core in 94% of the 189 posterior realizations, and in 77–100% under two alternative recharge–pumping structures. The scripts here reproduce these numbers and all figures from the files provided.
Coordinates, units and coverage
- Coordinates: WGS 84 / UTM zone 43N (EPSG:32643), in meters. The borehole imagery log also gives latitude and longitude (WGS 84).
- Heads in m above mean sea level (m asl); depth to water in m below ground; Darcy flux in m d⁻¹.
- Model domain: 8.9 km × 7.1 km (62 km²), 76.614–76.696° E, 11.761–11.825° N. Reference area for all flow statistics: the Berambadi watershed inside the domain (20.8 km²).
- Time: monthly heads May 2010 to July 2021; calibration snapshot December 2018; boundary heads from the November 2018 regional equipotentials; nitrate surveys August 2012 to January 2020.
Contents
README.md
data/
observations/ field data used in calibration and in the independent tests
gis.zip shapefiles: watersheds, model domain, mesh nodes, pilot points, regional equipotentials
model/
feflow/ FEFLOW 10.0 model file
pestpp_ies_main/ control files, ensembles and run record of the reported inversion
realizations/ per-realization flow solutions (three zip archives)
code/
python/ analysis: fracture statistics, flow diagnostics, figure data
matlab/ all figures of the paper
output/
fig_data.mat figure data written by code/python/make_fig_data.py
data/observations
| File | Content |
|---|---|
heads_calibration_dec2018_44wells.csv |
The 44 calibration heads. well (well ID), obs_name (PEST observation name), X, Y, head_dec2018_m (m asl; ground elevation minus depth to water), sigma_m (standard deviation of the head error, m). |
monitoring_wells_depth_to_water_monthly.csv |
208 monitoring wells of the Berambadi network. well, X, Y, ground_elev_m (GPS ground elevation, m asl), then one column per survey date (YYYY-MM-DD, 123 dates from May 2010 to July 2021) with the depth to water (m below ground). Owner and village descriptions were removed. |
nitrate_surveys_2012_2020.csv |
1,546 nitrate analyses from ten surveys. id (sample label), bid (well ID, as in the head files), survey, date, no3 (mg L⁻¹ as NO₃⁻), X, Y. |
major_ions_surveys.csv |
549 major-ion analyses. id, survey, X, Y; NO3, Cl, Si, F, SO4 in µmol L⁻¹; Alk (alkalinity, µeq L⁻¹); EC (electrical conductivity, µS cm⁻¹); pH. |
borehole_imagery_fracture_log.csv |
Borehole camera log of 84 boreholes as recorded in the field. camera_id (C001 to C084), diam_in (diameter, inch), lat, lon, X, Y, swl_ft (static water level at imaging, ft below ground), casing_ft, fractures_ft (depths of horizontal fractures, ft; a-b marks an interval), dry_ft (dry fractures, ft), total_depth_ft. |
south_gundal_wells_depth_to_water_2009_2023.csv |
238 wells of the regional South Gundal network, surveyed about twice a year. sg_id, gps_time, X, Y, ground_elev_m (GPS ground elevation, m asl), then one column per survey (YYYY-MM, November 2009 to November 2023) with the depth to water (m below ground), and drilled_length_as_recorded. Non-numeric entries are field status notes as recorded (for example Dryed, Closed, Sealed, Removed, Struggled). The November 2018 survey underlies the regional equipotentials. Owner names were removed. |
monitoring_well_id_crosswalk.csv |
Well IDs of this resource (well, B numbers) and of the companion phase-portrait resource (well_id_jgr, D numbers) for the 120 wells common to both, with X, Y. |
data/gis.zip
Seven shapefiles (each with .shp, .shx, .dbf and .prj), in WGS 84 / UTM zone 43N. Unzip in place to create
data/gis/, which the code reads.
| File | Content |
|---|---|
berambadi_watershed.shp |
Berambadi watershed boundary. |
south_gundal_watershed.shp |
South Gundal watershed boundary. |
model_domain.shp |
The FEFLOW model domain (8.9 km × 7.1 km). |
regional_equipotentials_nov2018.shp |
Regional equipotentials of the South Gundal basin, November 2018 (polyline Z; Z is head in m asl). They set the fixed (Dirichlet) heads along the model perimeter. |
feflow_mesh_nodes.shp |
FEFLOW mesh nodes (NODE, SLICE, X, Y, Z; 2,093 nodes on each of two slices). |
pilot_points_K.shp |
The 182 pilot points of K_x, K_y and K_z. |
pilot_points_recharge_pumping.shp |
The 26 pilot points of recharge and of the pumping multiplier. |
model/feflow
| File | Content |
|---|---|
HYJO.fem |
FEFLOW 10.0 steady-state model used by the inversions: one layer of 4,016 triangular prismatic elements (2,093 nodes on each of two slices) with fixed heads along the perimeter. FePEST writes the parameter fields of each realization into it. |
The two alternative structures used the same mesh and boundary heads with a different source–sink term
(Section 2.3.4 of the paper); their posterior flow solutions are in model/realizations.
model/pestpp_ies_main
Ensembles and records of the reported inversion (PESTPP-IES 5.1.16; 200 prior realizations, 11 failed in the first forward run, 189 retained; 598 parameters; 44 observations; nine iterations).
| File | Content |
|---|---|
hyjo.0.par.csv |
Prior parameter ensemble (200 realizations). |
hyjo.9.par.csv |
Posterior parameter ensemble (189 realizations). |
hyjo.0.obs.csv, hyjo.9.obs.csv |
Simulated heads at the 44 wells (m asl) for the prior and the posterior. |
hyjo.obsnoise.csv |
Realizations of the observation noise added to the heads. |
hyjo.phi.actual.csv |
Objective function per iteration and realization. |
hyjo.rec |
PESTPP-IES run record, including all settings. |
hyjo.pst, hyjo.tpl, hyjo.ins |
Control, template and instruction files of the reported run, regenerated from the parameter, observation and option records in hyjo.rec, because the FePEST project was later reused for other runs. The original run also read a parameter covariance file (param.unc) that was not kept; the prior ensemble hyjo.0.par.csv takes its place. |
Parameter names: xco_*, yco_*, zco_* are K_x, K_y and K_z (m d⁻¹) at the 182 K pilot points;
rch_* is recharge (m d⁻¹) and pmp_* the pumping multiplier (dimensionless) at the 26 recharge–pumping
pilot points. Observation names hea_* match obs_name in heads_calibration_dec2018_44wells.csv.
model/realizations
Steady-state flow solutions exported from FEFLOW, one CSV per realization and one row per mesh node:
node, head (m asl), qx, qy, qz (Darcy-flux components, m d⁻¹).
| Archive | Content |
|---|---|
main_recharge_pumping.zip |
Reported model, spatially variable recharge and pumping (189 realizations). |
recharge_only.zip |
Alternative structure with recharge only (82 realizations). |
net_vertical_flux.zip |
Alternative structure with a net vertical flux that can be negative (76 realizations). |
code
| File | Content |
|---|---|
python/common.py |
Paths (relative to this folder), loaders, regridding of the nodal solutions to a 50 m grid, low-flow probability P (Eq. 10) and core metric F_core (Eq. 11). |
python/fractures.py |
Fracture saturation at the 81 imaged boreholes (Section 3.2, Fig. 7); writes data/observations/borehole_fractures_81.csv (per borehole: fracture depths in m, interpolated December 2018 and long-term depth to water, imaged and submerged fractures, distance from the hotspot core). |
python/make_fig_data.py |
Flow diagnostics for the three structures and all figure data; writes output/fig_data.mat. |
python/requirements.txt |
Python dependencies. |
matlab/fig_all.m |
Figures 1 to 7 and A1 to A3 from output/fig_data.mat and data/gis (MATLAB R2019a or later, no toolboxes). |
Reproducing the results
- Install Python 3.10 or later and the dependencies:
pip install -r code/python/requirements.txt(tested with Python 3.13, NumPy 2.5, pandas 3.0, SciPy 1.18, Matplotlib 3.11 and pyshp 3.1). - Unzip
data/gis.zipand the three archives inmodel/realizationsin place; each creates a folder of the same name. python code/python/fractures.pyprints the fracture statistics of Section 3.2 (for example 29% of fractures submerged within 1 km of the core against 89% beyond) and writesdata/observations/borehole_fractures_81.csv.python code/python/make_fig_data.pywritesoutput/fig_data.matand prints F_core for the reported model and the two alternative structures (0.942, 0.768 and 1.000).- In MATLAB, run
code/matlab/fig_all.m; the figures are written tofigures/. - To repeat the inversion, run PESTPP-IES 5.1 with
model/pestpp_ies_main/hyjo.pst. The model call (run_model.bat) is the FePEST wrapper: it writes the pilot-point values (hyjo.fpi) intoHYJO.femby inverse-distance interpolation (Eq. 3 of the paper; pilot points indata/gis) and returns the simulated heads at the 44 wells (hyjo.fpo). Set up this wrapper again in FePEST, or replace it with a script.
Data sources
Heads, nitrate and major ions come from the monitoring network of the Berambadi catchment, part of the Kabini Critical Zone Observatory (M-TROPICS, https://mtropics.obs-mip.fr/; Indo-French Cell for Water Sciences, Indian Institute of Science, Bangalore). Longer records are available through M-TROPICS. The regional South Gundal heads come from the same observatory. The borehole imagery was collected between November 2025 and January 2026 with a downhole inspection camera and is reported here as logged.
Related resources
The monitoring heads, the borehole camera logs and the catchment boundary are also part of the companion
resource for Bhaduri, Chaudhuri, Ruiz and Muddu (submitted to JGR: Solid Earth), on phase portraits of the
same hydrographs. The values are identical; the monitoring wells carry different IDs there (see
monitoring_well_id_crosswalk.csv), and the camera IDs C001 to C084 are the same.
License and citation
Released under the Creative Commons Attribution 4.0 International license (CC BY 4.0). Please cite the paper and this resource.
Related Resources
| This resource is required by | Bhaduri B, Kuppel S, Ruiz L, Hrachowitz M, Riotte J, Sekhar M (in review) Hydraulic heads reveal the flow-controlled organization of nitrate persistence in a fractured aquifer of southern India. Hydrogeology Journal |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| Indian Institute of Science | None | SP/INRA-17-0002 |
| Agence Nationale de la Recherche | ATCHA | ANR-16-CE03-0006 |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
| Name | Organization | Address | Phone | Author Identifiers |
|---|---|---|---|---|
| Sylvain Kuppel | Géosciences Environnement Toulouse (Université Paul-Sabatier, IRD, CNRS) | |||
| Markus Hrachowitz | Department of Water Management, Delft University of Technology |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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