Agricultural weather station

When you hear aboutagricultural weather station, many people think - well, a thermometer with a rain gauge, what’s so complicated about that. And then they wonder why investments in 'advanced sensors' don't pay off. I myself saw how an expensive station was installed in the Krasnodar Territory, but they forgot about calibration for soil moisture - as a result, the irrigation system worked when it was too late. This is not about hardware, this is about how to fit them into a specific field.

What a field weather station should actually do

If we take our experience fromagricultural weather stationfor Shandong Lingyao LLC projects, the key is not just to collect data, but to connect it with the drip irrigation system. For example, a wind speed sensor seems like a small thing. But if it does not take into account local turbulence due to the topography, then the evaporation forecast is off by 15-20%. We have to supplement it with ground sensors.

Here on the website https://www.lyzhihuinongye.ru we show how the weather station integrates with irrigation controllers - but in real life this requires manual configuration for each crop. I remember in Stavropol we had to rewrite the algorithm for tomatoes because the standard air humidity threshold did not take into account night dew.

A common mistake is to set a station once and forget it. Soil sensors become clogged with clay after a season, and ultrasonic anemometers lose their calibration after a hailstorm. We at Shandong Lingyao always tell our clients: a weather station is like a tractor - you need regular maintenance, otherwise the data starts to lie.

How to avoid common installation failures

The biggest pain point is the power supply. Solar panels are good in theory, but in the conditions of, say, the Altai region with its cloudy periods, the batteries last for 3 days. You have to pull the cable, and this is an extra cost. Once in the Voronezh region they saved money on this - as a result, the station was “silent” just during the critical week of drought.

The installation height of the sensors is a different story. According to the standards, thermometers are 2 meters, but if there is a forest belt nearby, the data is distorted. We have to find a compromise between standards and the real landscape. In our projects, for example for smart parks, we sometimes install duplicate sensors at different heights - more expensive, but more accurate.

Another point is protection from rodents. Cables in the fields are chewed by mice throughout the season. We had to switch to armored wires, although initially they were not included in the estimates. It’s a small thing, but without it the whole system stops.

Integration with other systems - where are the pitfalls?

Whenagricultural weather stationworks in isolation from the fertilizer system, half the meaning is lost. At Shandong Lingyao LLC we are setting up a connection with fertilizer application units - but here it is important that the data exchange protocols are open. With some manufacturers you have to write crutches, because their software does not provide raw data, only averaged indicators.

It is especially difficult with forecasts. Taking ready-made ones from the Hydrometeorological Center is cheap, but it is not suitable for the microclimate of the field. We set up our models based on machine learning, but they require local calibration for at least a year. In the Rostov region they somehow started it without this - in the end they overfilled the water by 30% and washed out the nitrogen from the soil.

Integration with remote valves is seemingly simple. But if the weather station gives a command to water, and the pressure in the line has dropped, the valves may not work. We had to introduce pressure sensors into the control loop. Such nuances are not written in brochures, only through experience.

Cases: when a weather station really saved the harvest

Last year in Kazakhstan, on a project with an apple orchard, ouragricultural weather stationwith a frost forecast function, it gave a signal in advance to turn on sprinkling. The temperature dropped to -4, but the ice crust on the buds protected the flowers. Without this, it was possible to lose up to 70% of the ovary - they were then calculated from similar areas without automation.

Another example is with vineyards in Crimea. There, the station not only counted watering, but also tracked dew points to forecast mildew. The system warned about the risk 36 hours in advance - they managed to treat the entire field with fungicides, and not the entire field. Savings on medications are about 40% per season.

But here is a negative case: in the Volga region they installed a station without a solar radiation sensor. As a result, evapotranspiration was calculated using averaged formulas, without taking into account local cloudiness. The excess water consumption was about 25% until they added a pyranometer. Now we always include it in the basic configuration.

Prospects and what we are trying to implement now

Now we are experimenting with the additionagricultural weather stationdrones for point control. For example, weather sensors show the risk of drought, and a drone with a thermal imager already shows exactly which areas are affected first. This is still a pilot project in Shandong Lingyao LLC projects, but in greenhouse complexes it already gives an increase in accuracy of up to 15%.

Another direction is to simplify calibration. We want to make the system itself offer adjustments based on error statistics. For now, this requires an agronomist to visit us, but we are already testing the algorithms on historical data from our facilities.

And most importantly, we learn to predict not the weather, but the reaction of cultures. Sameagricultural weather stationmay show ideal conditions, but if the variety is sensitive to pressure changes, the harvest will still suffer. We are adding phenological models for 20+ crops to the database, but this is work that will take years.