Climate change significantly impacts agricultural yield estimates and poses challenges to using historical data for future predictions.
Let’s start with showing some real examples illustrating the real challenges of unpredictable weather: State of Kansas, by Counties, years 2021 vs. 2023, Crop Type: Wheat and planting areas over 52 million acres, ~49% differences in yields.
Traditional yield prediction models are facing an unprecedented level of unpredictability because of climate change. Factors such as temperature fluctuations, unpredictable weather patterns, and the increased frequency of extreme events have introduced a level of variability that traditional models, which rely on historical data and linear assumptions, struggle to accommodate.
So why is yield prediction proving to be particularly challenging in these times and why using historical data for future predictions isn't working?
Temperature changes and water availability: Research indicates that both temperature and water supply, specifically soil moisture, are critical for crops, Climate change alters these factors, affecting yield estimates. Although some crops are more resilient to extreme heat, but drought and flooding has a significant impact on crop yields as we previously showed in recent posts (flooding in Brazil, Crop losses dure to sever drought).
Regional Variability – which is another factor impacts yield estimates and related to more regional and seasonal changes, imposing precise planning and management strategies regionally.
Historical Data & Changing Climate Patterns: Historical data may not accurately represent future conditions as climate change leads to shifts in temperature, rainfall patterns, and carbon concentration and more, such historical data-based models can be susceptible to overfitting, making them less reliable for predicting future yields across different regions and crop types.
Climate change disrupts the consistency & stability of the environmental factors that historical yield estimates rely on. New methods that incorporate current and projected climate conditions with the advancements in satellite imagery and deep learning improvs significantly the accuracy of yield predictions in efficient way too, trustworthy yield estimations cannot be achieved by relying solely on historical data.
The good news is that breakthroughs are on the horizon!
SatYield can generate accurate predictions for major crop types, in any location and climate, up to three months before harvest. We fuse data from multiple satellites, weather and soil sources, into a crop model simulator to calculate vegetation metrics and identify yield gaps, variability and optimization opportunities, without using any historical data and model training. Click the link to learn about how Satyield Crop Yield Prediction works.
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