Field Plot Irrigation Forecasting With Dynamic ETc Curves
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Solution Overview
Problem
Existing irrigation systems struggle to accurately manage crop water needs throughout a growing season, particularly in stress conditions, due to the dynamic nature of crop evapotranspiration and water stress coefficients, which are influenced by weather and local conditions.
Innovation Solution
A computerized method and system that utilizes remote sensing products (RSP) to forecast and adjust irrigation based on global and plot-specific variables, generating evapotranspiration (ETc) curves to determine optimal water amounts and dates for irrigation, incorporating ensemble learning and real-time data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static and global crop coefficient (Kc) definitions from FAO56 are used, then calculation simplicity is maintained, but accuracy in representing actual local crop growth conditions deteriorates
Solution Approach 1:
The patent applies local quality by transitioning from static global Kc values to dynamic plot-specific Kc values that are customized for each field plot based on local conditions including crop type, growth stage, and environmental factors. Each plot receives tailored irrigation management rather than uniform global treatment.
Solution Approach 2:
The patent implements dynamics by updating Kc values continuously throughout the growing season based on current crop growth stage, weather conditions, and plot-specific measurements. The system evolves from static FAO56 definitions to dynamic, adaptive values that reflect real-time crop needs.
2Force
If irrigation management is based on forecasted data only, then forward planning capability is improved, but responsiveness to actual current conditions deteriorates
Solution Approach 1:
The patent implements feedback by continuously comparing forecasted irrigation needs against actual measured conditions (soil moisture, crop stress indicators, weather deviations) and adjusting subsequent irrigation decisions accordingly. This closed-loop system ensures both forward planning and responsiveness to actual conditions.
Solution Approach 2:
The patent applies preliminary action by using forecasted weather data and crop growth models to predict future irrigation requirements in advance, allowing proactive water management planning while maintaining the ability to adjust based on actual conditions as they unfold.
3Ease of operation
If uniform irrigation management is applied across all field plots, then operational simplicity is maintained, but adaptability to local plot-specific conditions deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the farm into discrete field plots, each with its own irrigation management plan based on plot-specific characteristics such as crop type, soil properties, topography, and growth stage. This allows customized treatment for each plot while maintaining centralized system coordination.
Solution Approach 2:
The patent implements local quality by tailoring irrigation parameters (water amount, timing, frequency) to each individual plot's specific needs rather than applying uniform management across all plots. Each plot receives optimized irrigation based on its unique local conditions.
4Loss of energy
If irrigation timing is delayed until water stress becomes severe, then water use efficiency is improved, but crop yield and plant health deteriorate
Solution Approach 1:
The patent applies preliminary action by predicting future water stress conditions using weather forecasts and crop growth models, allowing irrigation to be applied before severe stress occurs. This proactive approach prevents yield loss while optimizing water timing to match actual crop demand.
Solution Approach 2:
The patent implements feedback by monitoring actual crop response to irrigation and environmental conditions, then adjusting subsequent irrigation timing and amounts to maintain optimal water status. This continuous adaptation maximizes both water use efficiency and crop productivity.
Data Source
AI summary
An irrigation management method constituted of: applying a global RSP model to received GIV values to forecast global RSP values; and applying a plot-specific RSP model to receive PS IV values to forecast plot-specific RSP values, wherein responsive to the forecast global and plot-specific RSP values, a forecast ETO and measured plot-specific RSP values, the method is further constituted of: generating an ETc curve; responsive to the generated ETc curve, determining a growing season water amount for the field plot and/or determining a next irrigation water amount for the field plot; and outputting to a device the determined growing season water amount and/or the determined next irrigation water amount such that irrigation of the field plot can be adjusted.