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2020 Annual progress update

The first year has focused on getting the programme up and running, with Scion leading the development of the operational research plan together with the programme collaborators. We have successfully contracted four national and eight international collaborators. Working with stakeholders, we have identified all six main research sites for the programme sites in Northland, Auckland, Manawatu-Whanganui, Wairarapa, Canterbury, and West Coast regions. Despite the disruptions from COVID-19, the programme is targeting to set up the first research site in Canterbury in October 2020.

The Forest Flows programme has engaged with stakeholders for two case studies, we have identified two communities and the various stakeholders that may be end users of Forest Flows outcomes. The first case study is on the Aupouri Peninsula, Northland. This aquifer is under increasing pressure from the growing number of avocado farms, a potential future requirement to supply potable water to Kaitaia, and other activities that require aquifer water. The second case study is the Akitio river catchment in the Manawatu-Whanganui region, near Dannevirke. There is considerable support in both case study areas from regional government, local iwi and community groups to collect data locally and address concerns with planted forests and water.

A key technology for Forest Flows is the creation of low-cost dataloggers that can successfully operate as a wireless, internet of things (IOT) network in forests. This is a very difficult environment as the wireless signal is reduced by steep terrain and signal-deadening vegetation. Scion has collaborated with the New Zealand technology research and design company INFACT Ltd, based in Christchurch, who have successfully designed low-cost dataloggers able to meet the above challenges. The dataloggers are to be built in October 2020 by New Zealand company Quick Circuit Ltd. This is a great example of NZ Inc. successfully developing a world-leading technology.

Forest Flows developed a key collaboration with the MBIE Time-Evolving Data Science/Artificial Intelligence for Advanced Open Environmental Science (TAIAO) data science programme led by the University of Waikato’s Artificial Intelligence Institute. This collaboration provides valuable synergies to both programmes.

International collaborations were forged with NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission and Massachusetts Institute of Technology (MIT) / University of Southern California (USC) Soil moisture Sensing Controller and oPtimal Estimator (SoilSCAPE) programme. 


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