Irrigation and Agriculture

June 3, 2016


Pastoral agriculture comprises more than half of New Zealand’s primary exports, worth ∼$29.7 billion annually (Statistics New Zealand, 2015). Much of that agricultural activity takes place on land with insufficient rainfall, which requires supplementary irrigation. An estimated 2.4% of New Zealand’s GDP relies on irrigation (Doak, 2005). Due to current resource limits, the agricultural industry must increase its efficiency if it continues to grow. Precision agriculture is the practice of managing resource use on a farm at the sub-paddock scale to maximise output and minimise waste. Precision irrigation can save between 9% and 26% of water and reduce runoff and drainage by 55% (Hedley, 2010). When including electricity costs, variable-rate irrigation systems are estimated to save farmers $60–$150 per hectare per year. To implement precision agricultural systems, high resolution NRT maps of soil moisture deficit are needed. One of CSST’s key goals is to use space based measurements to create these maps.


The 2011 Onefarm report (Allen & Wolfert, 2011) identified several information challenges and bottlenecks impeding growth in agriculture, including data accuracy, quantification, and timeliness, as well as the maintenance of an historical dataset for long-term farm management. Space-based measurements and higher order data products that will be made available once CSST is operational could alleviate many of these bottlenecks as they would provide timely, accurate and quantifiable measures of a number of farm parameters. In addition, the large historical library of satellite imagery made available through the CSST archive would be available to reconstruct elements of farm history that have been lost.

Key operational goals for CSST include:

  • Assess the utility of high spatial resolution maps of soil moisture derived from visible and TIR imagery.
  • Develop a 4-dimensional variational data assimilation (4D-Var) system that would be built on a state-of-the-art hydrology model to permit exploitation of data from multiple sources (space-based measurements, measurements from drones, in-situ measurements from soil moisture probes etc.) to generate high quality soil moisture maps.
  • Develop research capabilities in GNSS-R measurements of soil moisture. The goal of this line of research would be to provide an additional data stream for the 4D-Var assimilation model.
  • Generate maps of water stress, nitrogen-related stress, and biomass from existing freely available, or low-cost, space-based imagery and integrate these products with existing geospatial agricultural tools to facilitate their uptake by the precision agriculture community in New Zealand. In collaboration with industry partners, CSST would also conduct the extensive validation required for the New Zealand environment.
  • Generate plant specific models relating space-based measurements to water stress, nitrogen- related stress, and biomass for key New Zealand crops.