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 Wellington Research Station flux tower is part of the network of Australian Critical Zone Observatories (OzCZO). The site vegetation is characterised by pastoral/woodland type. Climate of the site is represented by a humid subtropical climate type (Köppen), with hot summers and cool winters. Long term weather records from the Bureau of Meteorology (station no. 065035) states annual mean maximum temperatures of ca 22.8 °C, and mean minimum temperatures of ca 10.5 °C. The rainfall for the site is in the range from an annual lowest of 348.3 mm to annual highest of 1355.3 mm. The station was commissioned on 1 September 2023 and is managed by the CSIRO Environment.
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 Wellington Research Station flux tower is part of the network of Australian Critical Zone Observatories (OzCZO). Its primary purpose is to investigate the exchange of CO2 and water vapor between the atmosphere and land surface (vegetation, soil, vadose zone and groundwater), in a typical semi-arid pastoral farmland region of NSW. These water, energy and carbon dioxide fluxes form essential boundary conditions for environmental models and must be measured. A better understanding of hydrologic processes (such as groundwater recharge and evapotranspiration) in a pastoral landscape will inform policy makers on the challenges of water management and supporting food production for a growing population in a changing climate.
The Wellington Research Station’s groundwater investigation is particularly informative as it is located in a fractured rock domain, which is a poorly understood medium for groundwater. Less is known about the water resources available in fractured rocks than practically any other aquifer system, yet it has been estimated that approximately 1/3 of all bores drilled in Australia are into fractured rock systems. These systems are particularly important for understanding and monitoring dryland salinity and for supporting the increasing agricultural water demand from fractured rock environments. A better understanding of hydrologic processes (such as groundwater recharge and evapotranspiration) in a pastoral landscape will inform policy makers on the challenges of water management and supporting food production for a growing population in a changing climate.
The flux tower and associated infrastructure will also provide data for future projects, measurements for parameterising and validating remote sensing.
Lineage
Data collected using standard eddy covariance and meteorological instrumentation on a 2.5m tower at the Wellington 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.
Procedure Steps1.
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.