Original title: SoilWaterNow: Soil water nowcasting for mapping plant available water (PAW) across paddocks for improved on-farm decision-making
Yi Yu, Mikaela J. Tilse, Patrick Filippi, Thomas F. A. Bishop · August 2026
Farmers in dry areas need to know how much water their crops can reach in the soil, known as plant-available water. Without good estimates, making day-to-day farming choices is hard. To fix this, researchers built the Sydney Soil Water-Energy Balance model. This system blends satellite images, climate measurements, and soil traits to map root-zone soil moisture and water evaporating from crops. It calculates these conditions every day at a detailed 30 m resolution across entire paddocks. When tested against soil moisture sensor networks across Australia, the model performed reliably across varied grain-growing regions. Its correlation scores usually ranged from 0.70 to 0.85, showing it can track soil water well enough to guide farm management.
You are baking a tray of biscuits, but the oven heats unevenly. Checking the middle tells you nothing about the edges, and a single timer cannot capture the whole tray. In this paper, a paddock is that tray and the uneven heat is the soil water: some 30-metre patches stay moist while neighbours dry out. The model uses satellite and weather data to tell each patch how moist it is, so a farmer can act on the dry parts instead of an average.
Dryland grain farmers make nitrogen decisions when water is in short supply, and a poor guess wastes money or yield. This model delivers a daily map of root-zone water at 30-metre resolution, so decisions can be tailored to the driest and wettest parts of a paddock. It held up well against soil-moisture networks across Australia, with correlations usually between 0.70 and 0.85, which makes the output plausible enough to act on.
The abstract reports validation correlations generally from 0.70 to 0.85 for most regions, so some regions fit less well; it does not state error margins, validation dates, or performance under extreme events. It also presents yield-potential estimates and nitrogen recommendations as future applications, not as tested outcomes.
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SoilWaterNow: Soil water nowcasting for mapping plant available water (PAW) across paddocks for improved on-farm decision-making — Yi Yu, Mikaela J. Tilse, Patrick Filippi et al.
Abstract licence: CC0
Explanation generated by Synthesis from the abstract — it is not the original paper. This is a preprint, so it hasn't necessarily been peer reviewed.