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Field-Scale Impacts to Water, Carbon, and Productivity in an Agrivoltaics Array: Initial Results and Data
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| Created: | May 13, 2026 at 4:38 a.m. (UTC) | |
| Last updated: | May 13, 2026 at 7:54 p.m. (UTC) | |
| Citation: | See how to cite this resource | |
| Content types: | CSV Content |
| Sharing Status: | Public |
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Abstract
Agrivoltaic performance and ecosystem impacts are understudied in humid temperate climates, especially across photovoltaic (PV) configurations. To address this gap, we established an agrivoltaic observatory in Wisconsin, USA, comparing an open-sky control with fixed-tilt and single-axis tracking arrays. Continuous radiation, eddy-covariance, soil moisture/temperature, and phenocam observations were paired with vegetation surveys across below-panel, dripline, and alley microhabitats. Clear-sky radiation showed that fixed-tilt panels created persistent below-panel and shaded-side diffuse-dominated light conditions, whereas tracking arrays redistributed shade through the day and increased under-row light. Across May–December 2025, soils in the fixed-tilt were driest at intermediate-to-deep depths, while the tracking maintained the highest deep soil moisture. Within the fixed-tilt, below-panel soils were coolest, yet also among the driest, indicating that throughfall exclusion outweighed reduced evaporative demand as a control on moisture dynamics. Driplines accumulated water at intermediate depths, consistent with rainfall and infiltration concentration along panel edges. Tracking reduced within-array heterogeneity and maintained deeper water storage by uniformly suppressing evapotranspiration through shifting shade. The array showed lower net CO2 uptake and evapotranspiration than control during June--October by 36% and 28%, respectively, alongside higher sensible heat fluxes and lower relative humidity. Flux differences increased after early-August mowing and herbicide application, suggesting vegetation management can rival microclimate in shaping first-year outcomes. Overall, humid-climate agrivoltaic systems form repeatable microhabitat mosaics rather than uniformly cooler or wetter conditions, with array geometry governing light limitation, rainfall redistribution, and vegetative impacts. Our dataset provides a baseline for multi-year evaluation of carbon, water, and productivity tradeoffs.
Subject Keywords
Coverage
Spatial
Temporal
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Content
README.md
Lake Kegonsa Agrivoltaic Dataset
Ancillary micrometeorological, solar-radiation-component, within-array PPFD light-bar, and soil moisture / temperature observations supporting the paired Lake Kegonsa agrivoltaic flux towers (US-KSA and US-KSC), Wisconsin, USA, spanning the 2025 growing season.
Note on the eddy-covariance / flux tower data: the half-hourly EC + micromet records from the US-KSA (agrivoltaic) and US-KSC (open control) towers are not stored in this HydroShare resource. They are distributed via the AmeriFlux repository; see
fluxTower/README.mdfor the canonical URLs and download instructions. ThefluxTower/directory in this bundle is intentionally a documentation-only placeholder.
Sites and platforms
- US-KSA Agrivoltaic flux tower (hosted on AmeriFlux; see fluxTower/)
- Eddy-covariance tower under a single-axis tracker PV array.
- US-KSC Open-field control flux tower (hosted on AmeriFlux)
- Shadow-band radiometer (CR1000 logger): hourly direct / diffuse / total solar radiation partitioning. Co-location with US-KSA / US-KSC towers: TBD.
- Light-bar PPFD network: eight LI-COR quantum line sensors deployed across both panel systems (Single-axis tracking and Fixed-tilt) at Under-panel, Row-edge, and Alley positions; 5-min sampling.
- Soil moisture / temperature network: eight METER RXW-GP4A profile probes distributed across alley, below-panel, dripline, and control positions for both panel systems; volumetric water content at 4 depth bands (0-15, 16-30, 31-45, 46-60 cm) and point temperatures at 6 depths (3.5, 10, 20, 30, 45, 60 cm). 10-min sampling.
File organization (manifest)
Top-level directories group sources by platform; within each, data are subdivided by measurement family.
fluxTower/ empty placeholder - see README inside
README.md redirect to AmeriFlux US-KSA / US-KSC
shadowband/ shadow-band radiometer, hourly, 2025-06-02 to 2025-10-10
shadowband_radiation.csv Shadow_Avg, Clear_Avg, Bar_Avg,
Shadowfiveminavg_Avg, Stot, Sbeam, Sdiff
lightbar_ppfd/ LI-COR light bars, 5 min, 2025-05-30 to 2025-10-10
sensor_inventory.csv per-sensor metadata (8 rows)
lightbar_ppfd_tracking.csv L1-L4 (single-axis tracking system)
lightbar_ppfd_fixed.csv L5-L8 (fixed-tilt system)
soil/ METER RXW-GP4A probes, 10 min
soil_sensor_inventory.csv per-probe metadata (8 probes)
soil_moisture_10min.csv 32 SM channels, May 2025 to Jan 2026 (Dec gap)
soil_temperature_10min.csv 48 T channels, May to Nov 2025
soil_moisture_correction.md documentation of temperature correction
used for the manuscript-figure variant
Each data CSV begins with a commented metadata header (lines starting
with #) followed by a single column row and the data records. To read
in pandas:
python
import pandas as pd
df = pd.read_csv('soil/soil_moisture_10min.csv', comment='#',
parse_dates=['datetime_iso'])
Companion files
variables.csv- controlled vocabulary mapping each short variable code to a long name, CF/CUAHSI standard name, units, instrument, and the sites it applies to.methods.md- flux processing chain, QC scheme, gap-filling notes, and outstanding items (TBD fields).CHANGELOG.md- version history.LICENSE- CC-BY-4.0 license text.
Time convention
All timestamps are ISO-8601 with an explicit offset.
- shadowband:
-06:00(America/Chicago Local Standard Time, no DST applied). Each timestamp marks the start of the 1-h averaging interval. - lightbar_ppfd:
Z(UTC). Timestamps mark the sample instant. The source files use the UTC convention; preserved as-is here to avoid lossy round-trips. Convert downstream if needed:UTC - 6 h = LST. - soil: the source export embeds an explicit offset per timestamp
(
-05:00for CDT,-06:00for CST). The offsets are preserved verbatim - note that the November 2025 source file remained on-05:00past the 2025-11-02 DST transition while the January 2026 source file moved to-06:00. Normalise downstream if a single canonical offset is required.
Missing values
Missing values are coded as NA. No gap-filling has been applied in
this release; downstream users should apply their preferred
gap-filling / partitioning workflow (e.g., REddyProc, ONEFlux).
Record counts
fluxTower (US-KSA, US-KSC)
- External - hosted on AmeriFlux. See
fluxTower/README.mdfor retrieval. The directory in this bundle is an empty placeholder.
shadowband (hourly)
shadowband_radiation.csv: 3132 records
lightbar_ppfd (5 min)
sensor_inventory.csv: 8 sensorslightbar_ppfd_tracking.csv: 66857 records (L1-L4)lightbar_ppfd_fixed.csv: 90739 records (L5-L8)- Note: 128 of 157596 records are off the nominal 5-min grid (mostly off-by-one-second; plus a small instrument-startup cluster on 2025-05-30). Preserved as-is - filter downstream if a strictly regular grid is required.
soil (10 min)
soil_sensor_inventory.csv: 8 probessoil_moisture_10min.csv: 31691 records x 32 SM channels (8 probes x 4 depth bands), 2025-05-20 to 2026-01-31soil_temperature_10min.csv: 27798 records x 48 T channels (8 probes x 6 point depths), 2025-05-22 to 2025-12-01- Note: December 2025 is absent from the SM source export (gap between the November and January files); soil temperature was not exported for December 2025 or January 2026. Values of 0.0 in the early record (May-Jun 2025) typically indicate pre-deployment / pre-calibration. No filter applied.
Citation
Han, K., Mackin, H., Mather, E., Lawton, S., Thom, J., Desai, A. R., Kucharik, C. J., Loheide, S. P. (2026). Lake Kegonsa agrivoltaic ancillary dataset - shadow-band radiation, within-array PPFD, and soil moisture / temperature (2025 growing season). HydroShare. DOI: TBD
For the paired eddy-covariance flux records (US-KSA, US-KSC), cite the AmeriFlux site data products separately following the AmeriFlux Data Use Policy.
Contact
khan99@wisc.edu
License
Released under Creative Commons Attribution 4.0 (CC-BY-4.0).
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| United States Department of Energy | None | None |
| Wisconsin Alumni Research Foundation | None | None |
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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