Calperum Chowilla Flux Data Release 2025_v1 

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 (v3.4.18) as described by Isaac et al. (2017). PyFluxPro produces a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER).

The Calperum Chowilla site was established in July 2010 and is managed by the University of Adelaide, coordinated by Prof Wayne Meyer and Prof David Chittleborough of the Landscape Futures Program as part of the Environment Institute. This is a former sheep grazing property that has been destocked and is being managed as a conservation area in this type of ecosystem. The landscape is flat with a series of low east–west sand dunes. The dunes are remnants of a previous dry era and are mostly now stabilized by mallee (multi-stemmed Eucalypt trees) and various shrubs. It is a semi-arid environment fringing the River Murray floodplains of the Riverland. 

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.
Calperum Mallee site is managed by the University of Adelaide (UA) and is funded by TERN. Calperum is a reserve managed by the Australian Landscape Trust, for the Australian Government. 

The purpose of the Calperum Chowilla flux station is to:

• measure the energy, CO₂ and H₂O balance of mallee shrub land for short term (days) and long term (years)
• link vegetation and ecosystem response to soil, atmosphere and local management conditions to explain daily and seasonal variation in exchange processes
• use the site data to broaden environmental monitoring data for Ozflux and climate interpretation at the continental scale
• use the measured data to develop and test predictive models of vegetation and related ecosystems that can be used to improve restorative actions in conservation of this type of ecosystem.

 

All flux raw data is subject to the quality control process OzFlux QA/QC to generate data from L1 to L6. Levels 3 to 6 are available for re-use. Datasets contain Quality Controls flags which will indicate when data quality is poor and has been filled from alternative sources. For more details, refer to Isaac et al (2017).