Pendall, E. (2026). Yarramundi Irrigated FLUXNET Release 2026_r1. Version 2026_r1. Terrestrial Ecosystem Research Network. Dataset. https://dx.doi.org/10.25901/5wpr-vr80
Yarramundi Irrigated FLUXNET Release 2026_r1
Ver: 2026_r1
Status of Data: completed
Update Frequency: annually
Security Classification: unclassified
Record Last Modified: 2026-04-02
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Dataset Created: 2026-03-20
Dataset Published: 2026-04-02
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This release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer using eddy covariance techniques. Data were processed using PyFluxPro as described by Isaac et al. (2017) for the quality control and post-processing steps. The final, gap-filled product containing Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER) has been produced using the ONEFlux software as described in Pastorello et al. (2020). This data set has been produced as part of the FLUXNET Shuttle project. The Yarramundi Irrigated Paddock site is located near Richmond, NSW (GPS coordinates -33.620812, 150.763284). The site is about 3 km east of the Cumberland Plain Woodland flux tower. The climate is warm-temperate, with annual rainfall averaging 728 mm, mean maximum temperature in January of 30.4 °C, and mean minimum temperature in July of 3.6°C (BOM station 067105). The elevation of the site is about 20 m asl and the topography is flat. The soil is sandy loam in texture, organic carbon content is <1%, and nutrient availability is moderate in the top 10 cm; iron concretions below 50 cm indicate poor drainage at times. The vegetation canopy is up to 1 m tall, and the plant community is dominated by exotic herbaceous perennials, including Digitaria sanguinalis, Bromus catharticus, Echinochloa crus-galli, Setaria parviflora, Eleusine indica, Conyza sumatrensis, Chenopodium album and Trifolium repens.
Fluxes of water vapour, carbon dioxide and heat are quantified with the open-path eddy flux technique from a 2.5 m tall mast. Additional measurements above the canopy include temperature, humidity, rainfall and net radiation, and photographs are taken several times per day to track canopy greenness. Irrigation water quality has higher nutrient and sodium levels than natural precipitation because the source is recycled wastewater.
Fluxes of water vapour, carbon dioxide and heat are quantified with the open-path eddy flux technique from a 2.5 m tall mast. Additional measurements above the canopy include temperature, humidity, rainfall and net radiation, and photographs are taken several times per day to track canopy greenness. Irrigation water quality has higher nutrient and sodium levels than natural precipitation because the source is recycled wastewater.
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
Purpose
The Yarramundi Irrigated paddock flux tower was established to evaluate effects of pasture improvements such as seeding, mowing, irrigation, strip grazing, on ecosystem carbon, water and energy fluxes. Yarramundi Irrigated is paired with Yarramundi Control.
Lineage
Data collected using standard eddy covariance and meteorological instrumentation on a 2m tower at the Yarramundi Irrigated site. The data were quality controlled using the PyFluxPro software package, see Isaac et al. (2017), which is available at https://github.com/OzFlux/PyFluxPro. Gap filling and partitioning has been done using the ONEFlux software package, see Pastorello et al. 2020, which is available at https://github.com/fluxnet/ONEFlux.
Method DocumentationPastorello, G., Trotta, C., Canfora, E. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci Data 7, 225 (2020).Isaac P., Cleverly J., McHugh I., van Gorsel E., Ewenz C. and Beringer, J. (2017). OzFlux data: network integration from collection to curation,PyFluxProONEFlux
Procedure Steps
1.
Data is measured using standard micro-meteorological instrumentation on a flux tower.
2.
Data is recorded on a data logger and is collected by the site PI.
3.
Data quality control including removal of data outside plausible ranges, removal of spikes, exclusion of particular date ranges and removal of data based on the dependence of one variable on another is done using PyFluxPro.
4.
Filtering for low-ustar conditions, gap filling and partitioning of NEE into GPP and ER are done using ONEFlux.
Spatial Description
The Yarramundi Control flux tower is located on the Western Sydney University Hawkesbury campus.
Temporal Coverage
From 2023-01-01 to 2026-01-01
Spatial Resolution
Data not provided.
Vertical Extent
Data not provided.
Data Quality Assessment Scope
Isaac P., Cleverly J., McHugh I., van Gorsel E., Ewenz C. and Beringer, J. (2017). OzThe data have been quality controlled using the PyFluxPro software. Quality control checks applied to the data include:
Specific checks applied to the sonic and IRGA data including rejection of points based on the sonic and IRGA diagnostic values and on either automatic gain control (AGC) or CO2 and H2O signal strength, depending upon the configuration of the IRGA.
If the data quality is poor, the meteorological data is filled from ERA5 reanalysis data and fluxes are filled using the Marginal Distribution Sampling method. Filled data can be identified by the Quality Controls flags in the dataset.
The ONEFlux software used to gap fill and partition this data set also applies a Median Absolute Deviation (MAD) filter to the carbon dioxide, latent heat and sensible heat before the gap filling step.
- range checks for plausible limits
- spike detection and removal
- dependency on other variables
- manual rejection of date ranges
Specific checks applied to the sonic and IRGA data including rejection of points based on the sonic and IRGA diagnostic values and on either automatic gain control (AGC) or CO2 and H2O signal strength, depending upon the configuration of the IRGA.
If the data quality is poor, the meteorological data is filled from ERA5 reanalysis data and fluxes are filled using the Marginal Distribution Sampling method. Filled data can be identified by the Quality Controls flags in the dataset.
The ONEFlux software used to gap fill and partition this data set also applies a Median Absolute Deviation (MAD) filter to the carbon dioxide, latent heat and sensible heat before the gap filling step.
Data Quality Assessment Outcome
No anomalous data detected after quality control.
ANZSRC - FOR
GCMD Sciences
Horizontal Resolution
Parameters
Platforms
Temporal Resolution
User Defined
AU-Ya2
FLUXNET ID
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia.
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