Estimating Plant Available Soil Water (SWApp)

“New tools to measure and monitor soil water” (GRDC project USQ 00014)


Update: SoilWaterApp V3 was released to the App Stores on 10th November 2016.

SWApp provides farmers and advisers with a ready estimate of plant available water (PAW) in the soil during a fallow and early crop phase. SWApp estimates soil water (PAW) using a tested water balance model (Howleaky) and inputs from:

  • weather data from a nearby Bureau of Meteorology (BoM) sourced from the Silo (https://www.longpaddock.qld.gov.au/silo/);
  • rainfall data from a local rain gauge (manual entry);
  • rainfall data automatically uploaded from a Bluetooth enabled rain gauge (20m range);
  • a soil description best suited to your paddock; and
  • soil and crop cover conditions for each paddock.

SWApp considered all components of the water cycle on a daily basis and uses long term climate data to provide a forward-looking estimate of likely outcomes for the specified soil, location and fallow/crop conditions. 

Acknowledgements

SWApp was developed for the Grain Research and Development Corporation by the University of Southern Queensland.

The project team includes: 

    Prof. Steve Raine (project diector), 

    Dr David Freebairn and Dr Brett Robinson (project managers), 

    Dr David McClymont of DHM Environmental Software Engineering (software engineering), 

    Erik Schmidt (project administrator), Victor Skowronski (Electrical Engineer), Dr Jochen Eberhard (data analysis).

Project Objectives

Develop a low-cost, grower-friendly application for a smartphone that estimates soil-water storage. The system uses water-balance simulation, online climate data (BoM data from Silo), local rainfall data and soil descriptions (ApSoil and SoilMapp). The project tested an automatic rain gauge and soil water sensors.

Specific design objectives included:

  1. Designed for iOS devices (iPhone and iPad).
  2. Simple and intuitive to use. The target audience is farmers and consultants.
  3. A “site or paddock" is the focus of each analysis. A site links to data including:
    • Climate data including rainfall, max/min temperature, evaporation from the SILO climate database;
    • Soil data based on local knowledge and the ApSoil database
    • Vegetation/ground-cover descriptions including growing and residue cover.
  4. Ability to store information for multiple sites, summarising site information:
    • Show current soil water status;
    • Show icons representing linked sensors
    • Ability to add delete sites.
  5. Allow users to select climate data from the Silo database nearest to their location:
    • Allow users to override Silo data and upload their own data.
    • Download climate data from SILO website;
    • Detect nearest location to user’s location;
    • Save a list of favourite locations.
  6. Allow users to select the soil for their site:
    • Select soils based on Australian States;
    • Provision for creating new soil and vegetation types;
  7. Allow users to select vegetation and ground-cover (tillage) types:
    • Select a range of vegetation /crops.
  8. Develop a detailed analysis page showing:
    • Title and list of attached sensors.
    • A summary overview of soil moisture from water balance and sensors for the current day.
    • Develop a chart (period =1yr) showing current soil water time-series underlain by historical soil water time series;
    • Develop a Soil profile chart representing depth vs SoilWater (%) showing by layers:
      • Air dry limit
      • Wilting point limit
      • Field capacity limit
      • Saturation limit
      • Current soil water level
  9. Show projected soil moisture for the next 3 months, based on the current value. Will be shown as a “horse-tail” of soil moisture curves overlaid (transparently) on the soil moisture time-series.
  10. Develop a calendar view showing:
    • Days with measurements
    • Allow editing of user-data
  11. Interactive features – possibly ability to turn off sensor measurement data for any day.
  12. Develop a user-interactive feature to switch between different calibration “possibilities”.
  13. Apply the HowLeaky water balance model to estimate soil-moisture
  14. Allow soil-moisture sensor information to be integrated to initialise and potentially calibrate the water balance model.
  15. Develop a calibration module to calibrate the water balance model based on sensor-data.
  16. Add user-messaging functionality.
  17. App review functionality.