Oruamatua


What was achieved

  • A wireless sensor network was established that enabled some of the first daily farm scale mapping of soil properties (temperature and moisture) in New Zealand hill country.
  • These maps can be used to drive forage yield models and help inform decision-making on pasture management.

About the study site

Oruamatua is a 10,000 ha farm near Taihape.

 

What was trialled

  • The trial investigated the potential for modelling the distribution of soil temperature and moisture in hill country landscapes at high spatial and temporal resolution. The spatial resolution of existing widely-available soil temperature and moisture data is too coarse to provide useful information at farm scale in hill country, and is unable to account for the influence of topography in these landscapes.
  • A wireless sensor network (WSN) was installed at Oruamatua in June 2020. The WSN consisted of twenty sensors installed in the soil at 30 cm depth. The sensors were distributed across the farm in a way that accounted for topographic variation in elevation, aspect (the direction a hillslope faces) and the potential for water to accumulate (strongly influenced by slope gradient).
  • The sensors were configured to measure soil temperature and soil moisture at hourly intervals and report measurements back to a cloud database via the cellular network. On the farm, LoRa (Long Range) technology was used to communicate between components of the WSN.
  • Statistical models were fit to the soil temperature and moisture data in order to relate those soil properties to other topographic variables including elevation, aspect and slope. The models were used to predict soil temperature and moisture across the farm at 30 m resolution at daily intervals across a generic model year.

Key findings

  • The WSN performed well.
  • As expected, sensor data revealed that north-facing slopes tended to be warmer and drier than south-facing slopes, which reflects the influence of topography. Interestingly, soils on north-facing slopes warmed from the winter minimum temperature through an arbitrary threshold of 10°C about 23 days faster than soils on south-facing slopes (about 88 days versus 111 days in 2021).
  • The soil temperature model performed very well, but the soil moisture model performed relatively poorly. The difference in performance is due in part to differences in predictability between soil temperature and soil moisture, the former varying more smoothly and more regularly over time than the latter.
  • Soil moisture predictions derived from the model should be interpreted with caution, but should be good enough to provide a broad indication of when soils are near field capacity versus when they are near wilting point.
  • It is expected that model performance should improve with a longer time-series of data, and better sensor calibration.

 

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