Agricultural early warning system for crop risk in Uzbekistan

What is an agricultural early warning system?

Early warning in agriculture means learning about drought, frost, hot dry wind or flooding from data rather than from the sight of a damaged crop. The system continuously compares the current state of a field and the weather forecast with what is normal and reports when a deviation becomes dangerous.

What sets it apart from ordinary monitoring is the output. Monitoring gives an image or an index that someone has to open and interpret. An early warning system sends a ready message: which field, which risk, why it thinks so and what to check.

Risks differ in how far ahead they can be seen. Frost and hot dry wind can be anticipated from the forecast before they happen. Water stress can be caught at an early stage, while irrigation can still limit the loss. Hail is visible from space only after the event, and the system's job then is to show quickly where and when the damage occurred.

What are its components, and why does crop stage matter?

A working system is a chain of four links. If any one of them is missing, the warning either never appears or arrives and changes nothing in the field.

The same signal costs different amounts at different stages. According to FAO Irrigation and Drainage Paper 33, the yield response of winter wheat to water shortage during flowering is three times stronger than during the vegetative period: a coefficient of 0.60 against 0.20. Losses during flowering cannot be recovered by later irrigation.

A system that does not know the crop stage therefore either raises the alarm too often or misses the most dangerous window. Hot dry wind hurts wheat most during flowering and grain filling, and cotton during squaring and flowering. Harvest delay only makes sense once the crop has matured.

• Monitoring data: satellite imagery, weather history and forecasts, crop type, sowing date and irrigation records
• Risk assessment: comparison with the field's own normal and rules that account for the crop and its growth stage
• Alert delivery: a message in a channel the team uses every day, with the cause and a confidence level
• Response plan: an action agreed in advance – a field visit, irrigation, crop protection, recording the damage

What data does an early warning system use?

The core is open satellite data. The optical Sentinel-2 shows greenness and leaf water through the NDVI and NDMI indices. The Sentinel-1 radar emits its own signal, so it sees the field through clouds and at night and detects standing water. The Landsat thermal band gives surface temperature, but coarsely – at 100 m – and infrequently.

Weather – the ERA5 archive and forecasts – provides the earliest signal: heat, wind, low air humidity, frost, heavy rain. Satellites usually confirm damage after the event, so forecast and observation complement each other rather than replace one another.

The third layer comes from the farm: field boundaries, crop, sowing date, irrigation and the agronomist's notes. Without them the system does not know the growth stage and cannot tell, for example, water stress from salinity, or a sudden loss of greenness after hail from a normal harvest.

Why does drought early warning matter in Uzbekistan?

Agriculture, forestry and fisheries account for 19.2% of Uzbekistan's GDP (stat.uz, 2024). Irrigated land covers 4.3 million ha, agriculture uses about 90% of the country's water, and about 14 billion m³ of water a year is lost in unlined earth canals (Kazinform, 2023).

The water deficit could reach 15 billion m³ a year by 2030, and about 175,000 ha of fields at the tail ends of canals already receive too little water (Kazinform, 2023). IWMI (2025) estimates that droughts cost the country hundreds of millions of dollars a year, and that without adaptation losses could reach 5 billion dollars a year by 2050 – about 3% of GDP.

The state is also moving towards field-level data. A decree of 13 March 2026 provides for an Agricultural Monitoring Center that will analyse satellite data, weather and crop vegetation (Gazeta.uz, 16.03.2026). Agricultural insurance has a 2027 target of covering 45,000 agricultural enterprises and 60% of farm output, with fair loss assessment and less human discretion named as priorities (Spot.uz, 25.09.2026).

For a farm, this means that catching water stress early is a direct way to protect yield when water is limited, and a dated record of a field event is also useful when dealing with an insurer.

What can't the system see, and what should be checked in the field?

Optical satellites cannot see through clouds: in spring a clear image of a field may come only once every 10–20 days. An honest system says so when there is no observation instead of passing a guess off as data.

A Sentinel-2 pixel is 10 m, so small patches and individual rows are not distinguishable. An image shows the consequence, not the cause: a sudden loss of greenness after hail looks the same as after strong wind, a fire or an early cut.

Some damage shows up with a delay. After frost, dying tissue becomes visible on images only after 4–10 days. The earliest stage of water stress – leaf warming – is visible only in the thermal range, so optical imagery usually reveals stress once leaf water has already dropped. A warning is a reason to inspect, not a diagnosis: the agronomist makes the decision.

• Water stress signal – soil moisture and whether irrigation actually took place
• A few days after frost – flowers, young bolls or ears and growing points
• Sudden loss of greenness – the cause: hail, wind or harvest
• Plants wilting in moist soil – a soil test for salinity

What does it look like in practice? The ClusterOS example

ClusterOS is one example of such a system, built for cotton, winter wheat and rice in Uzbekistan. It assesses 24 crop risks on every field in five groups: water, weather, crop development, soil and nutrition, and field management. Each field's satellite history is available from 2019.

Warnings arrive in the web dashboard and in Telegram in Uzbek or Russian: which field, which risk, why the system thinks so, with what confidence and what to do. The agronomist marks false alarms, and the system takes them into account.

The system can warn about frost from the minimum temperature forecast, and about hot dry wind roughly a day ahead. Sentinel-1 radar detects flooding through clouds. Hail and harvest delay are detected from a sudden loss of greenness after the event, and the cause is confirmed by a field visit.

How do you start with early warning?

The starting point is not choosing software but deciding which risks cost the farm most and who will act on a signal. A warning without a named recipient and a pre-agreed action changes nothing.

It helps to start with part of the area: the team gets used to warnings and sees where they actually save field trips and water.

• Digitise field boundaries and record the crop and sowing date for each
• Pick a few key risks, for example water stress, hot dry wind and frost
• Assign a recipient for warnings on each field or block
• Write down the action for each risk: who goes out, what they check, what decision they take
• Record irrigation, treatments and confirmed events – this makes the assessment more accurate
• After the season, compare the warnings with what actually happened in the field

Related risks

• Water stressThe crop is short of water. Imagery and the forecast show it before the leaves start to wilt.
• Hot dry wind (garmsel)A hot dry wind dries out crops within days. We warn from the weather forecast.
• Spring frostFrost at emergence or flowering. The warning comes in advance, with time to protect the crop.
• HailHail from the forecast – a warning before the event, and images of the field before and after it.
• FloodingThe field or part of it is under water. The area and date are recorded – for decisions and insurance.
• Harvest delayThe field is ripe but harvest has not started. Losses grow every week, and the next sowing slips.

Questions