Brian Jackson and other consortium members visiting farms near Narrabri. The Namoi case study provided the researchers with the opportunity to validate satellite observations with limited field measurements.

Remote watersense improves water use efficiency

Data collection to inform irrigation scheduling programs has mainly relied on monitoring devices at a few locations around a farm and computer systems that estimate crop water use.

But what if you could collect frequent near real-time measurements of rainfall, soil moisture and crop growth across each field and the farm, during the season?

Brian Jackson, senior principal engineer with Water Technology Pty Ltd and local contact for the WaterSENSE consortium, says that remote sensing and Earth observation technology can help fill the current gaps in the data needed to make optimal water use decisions at the basin, catchment, farm and field levels.

Earth observation (EO) is the gathering of information about the physical, chemical, and biological systems of the planet. It can be performed via remote sensing technologies or through direct-contact in-situ sensors.

WaterSENSE uses both earth observation satellites and ground-based radar rainfall observations.

“The WaterSENSE project began in 2020 through to 2024, delivering a suite of operational tools for Australian water managers with funding from the European Commission’s Horizon 2020 Research and Innovation Program,” Brian says. “The WaterSENSE project brought together a unique multi-disciplinary consortium of experts in Earth observation, rainfall, water use, agronomy and decision support.”

Using the Namoi catchment in northern NSW as a case study area, the consortium team, led by Dr Willem Vervoort, Professor in Hydrology and Catchment Management at The University of Sydney, investigated how evapotranspiration, soil moisture, crop water use, farm water balance and farm dam volumes can be quantified based on Earth observation data and then developed new Earth observation services for water managers1.

Figure 1: Case study location

The consortium is represented by Water Technology in Australia (water experts), along with international research-focused enterprises:

eLEAF (Earth observation and agronomy experts);
HydroLogic (HydroNET platform provider) from the Netherlands;
Hydro & Meteo (radar rainfall specialists) from Germany; and,
Hidromod (agronomists and water modelling specialists) from Portugal.

Brian says that this research provides a step forward in the quest to use Earth observation to measure and monitor water cycle components at a field scale. This will allow growers to adjust their irrigation practices to optimise productive and efficient water use, crop growth, and yield potential. The Namoi case study provided the researchers with the opportunity to validate satellite observations with limited field measurements.

Because of the frequency of satellite data collection, Earth observation can effectively measure changes in key components of the water cycle, including a new method to calculate crop water use by monitoring changes in evapotranspiration.

The evapotranspiration data is calculated by combining Earth observation data with the latest energy balance modelling – the ETLook model. The United Nations (UN) Food and Agriculture Organisation (FAO) uses this model for their water productivity portal (WAPOR)2.

“Closure of the water balance is imminent with remote sensing of rainfall inputs, evapotranspiration outputs and changes in water storages, all observable at a fine scale,” says Brian. “One of the remaining challenges is to find ways to predict crop yield accurately.”

In addition to the potential value of remote sensing for better irrigation scheduling, the cotton industry can also use this technology to improve their sustainable and productive water use benchmarking. Brian says the current process is conducted annually with a small number of growers, and it takes up to two years to compile and analyse the data and communicate the results back to industry stakeholders.

“With Earth observation, sustainable water use data can be collected across a whole catchment in near real-time and analysed very quickly to inform the industry of their effective water use in a season,” he says.

The WaterSENSE project has moved into its second phase, called REINFORM (REmote Sensing INtegration For Optimized Resource Management), which aims to expand the scalability of the WaterSENSE services to national and global scales and further explore the potential of Earth observation-based productive and sustainable water use indicators.

Research papers:

Vervoort, R.W.; Fuentes, I.; Brombacher, J.; Degen, J.; Chambel-Leitão, P.; Santos, F. Progress in Developing Scale-Able Approaches to Field-Scale Water Accounting Based on Remote Sensing. Sustainability 2022, 14, 2732. doi.org/10.3390/su14052732

www.fao.org/in-action/remote-sensing-for-water-productivity

Brombacher, J., Silva, I., Degen, J., Pelgrum, H., 2022. A Novel Evapotranspiration Based Irrigation Quantification Method Using the Hydrological Similar Pixels Algorithm. Agricultural Water Management, Volume 267, 2022, 107602, ISSN 0378-3774, doi.org/10.1016/j.agwat.2022.107602.

Strehz, A.; Einfalt, T. Precipitation Data Retrieval and Quality Assurance from Different Data Sources for the Namoi Catchment in Australia. Geomatics 2021, 1, 417-428. doi.org/10.3390/geomatics1040024

Watersense Services

Several of the tools that WaterSENSE developed are useful to growers, either directly or through a third-party agronomy service provider. Data on rainfall, weather, evapotranspiration, crop water use, soil moisture, percolation and runoff can be accessed to provide a richer data source than what is available from a single-point data collection point, such as an on-farm weather station.

For example, the rainfall data from radars fills the gaps between rain gauges to provide accurate data across each field.

For water management corporations and government agencies, the tools assist in managing water flows and delivery through the catchment and storage facilities.

Irrigated area mapping service and irrigated water use estimation

Knowledge of the area under irrigation and the amount of irrigation applied within those areas is critical for efficiently managing an irrigation water supply. Currently, water managers often work off historical irrigation maps and have limited ability to respond to changes in water demand during the current season.

WaterSENSE offers an Earth observation service that identifies irrigated fields within the water supply area and calculates the irrigated water use based on indicators such as actual evapotranspiration, soil moisture, biomass and water use efficiency.

The irrigated water use is then calculated from this data by the new Hydrologically Similar Pixels (HSP) algorithm3.

Using Earth observation data, the service distinguishes between irrigated and rainfed fields. It detects changes during the season, such as expansion of irrigation, abandonment of irrigated fields, potential excess water withdrawals, crop water consumption and the impact of drought on irrigation practices.

Brian says that water managers can use this near real-time mapping of the area under irrigation to analyse water distribution during the irrigation season and plan measures to improve water supply and water use efficiency for the future.

Gauge-adjusted radar rainfall service

Rain gauges provide highly accurate rainfall measurements at a single point. Even if multiple rain gauges are located around the farm, they can only provide limited insights into the rainfall distribution of an event.

Raw radar data also has limitations, such as unknown droplet size distribution, anomalies in the radar signal across an area and echoes from various ‘obstacles’.

The gauge-adjusted radar rainfall service combines the rainfall gauge data with adjusted radar data to produce a high-quality, near-real-time precipitation map for an area immediately after a rainfall event.

Figure 1: Adjusted radar map. The gauge-adjusted radar rainfall service combines the rainfall gauge data with adjusted radar data to produce a high-quality, near-real-time precipitation map for an area immediately after a rainfall event.

This service is available for radars near Narrabri, Emerald and Mackay, but it can be configured for any radar in Australia. Data can be accessed immediately after a rainfall event, and historical information is available from October 2020 to the present. Users can easily compare seasonal rainfall distribution and amount across years.

This data can be imported into the grower’s irrigation scheduling models, providing more accurate information about precipitation input at a paddock scale.

On-farm water management service

This service provides farm water managers with detailed information about their farm water balance and offers forecasts of the seasonal yield and irrigation needs of
each crop.

Earth observation can only reliably observe soil moisture changes in the top few centimetres of soil. The researchers used surface soil moisture and the new HydroAquaFarm model to estimate changes in soil moisture down the profile as the crop grew. They also used ground-breaking daily gauge-adjusted radar4 rainfall data and remote sensing to monitor the volume of water in on-farm reservoirs.

This is invaluable information for scheduling irrigation in the current season and makes it possible to assess changes in irrigation practices implemented to improve water
use efficiency.

Storm risk service

Remote-sensing of high rainfall events in near real-time provides water managers with the data they need to reduce the impact of flooding events. This service brings together data from the Bureau of Meteorology’s Australian Digital Forecast Database (ADFD), rain gauges and radar data to provide a visual representation of the rainfall intensity, duration, frequency and timing across a nominated catchment, right down to a specific address.

Find out more: https://www.watersense.eu

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