Future Crop Production Planning Through Safe Climatic Space Optimization
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Solution Overview
Problem
Current methods for predicting the impact of future climate change on crop production do not address how to mitigate its adverse effects, particularly for crops like maize, wheat, and soybean, which are crucial for food security.
Innovation Solution
A method is provided to incorporate future crop production into a Safe Climatic Space (SCS) by calculating indicator data, adjusting climatic data, and optimizing planting area distribution using a genetic algorithm (GA) to enhance adaptability and maximize crop production within the SCS.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current prediction methods are used to forecast future climate impact on crop production, then future production levels can be predicted, but the adverse effects of climate change cannot be mitigated
Solution Approach 1:
The patent applies preliminary action by calculating the safe climatic space (SCS) in advance based on historical climate data and crop production patterns. This pre-calculated SCS serves as a reference framework that enables subsequent adaptation strategies to mitigate climate change impacts before they fully manifest, allowing policymakers and farmers to prepare adaptive measures proactively rather than reactively
Solution Approach 2:
The patent employs parameter changes by adjusting climatic parameters (temperature, precipitation, humidity) within the defined SCS boundaries to identify optimal planting conditions. By modifying these environmental parameters within safe limits, the method enables adaptation strategies that maintain crop production while mitigating climate change effects, transforming static prediction into dynamic adaptation
2Measurement precision
If the safe climatic space is defined using historical climate data, then the current crop production system can be characterized, but the method cannot address future climate adaptation strategies
Solution Approach 1:
The patent uses preliminary action by first defining the SCS based on historical climate data and current crop production patterns. This foundational SCS framework is then used as a reference for evaluating future climate scenarios and developing adaptation strategies, enabling the system to both accurately characterize current conditions and plan for future adaptation
Solution Approach 2:
The patent applies dynamics by transitioning from a static SCS definition to a dynamic framework that can accommodate future climate changes. The method allows the SCS boundaries and optimal planting parameters to be adjusted based on projected climate scenarios, enabling the system to adapt to changing conditions while maintaining accurate characterization of safe climatic conditions
3Productivity
If crop production is optimized without considering climate change impacts, then maximum yield can be achieved under current conditions, but vulnerability to future climate change increases
Solution Approach 1:
The patent employs parameter changes by adjusting climatic parameters within the SCS boundaries to identify optimal planting conditions that maximize crop yield while maintaining vulnerability to future climate change. By modifying temperature, precipitation, and humidity parameters within safe limits, the method enables optimization of crop production under current conditions while preparing for future climate adaptation
Solution Approach 2:
The patent applies feedback by using the defined SCS as a reference framework to evaluate and adjust crop production strategies. The SCS provides feedback on whether proposed optimization strategies remain within safe climatic boundaries, enabling continuous adjustment of planting decisions to balance maximum yield with climate change vulnerability reduction
Data Source
AI summary
Provided is a method for incorporating a future crop production into a safe climatic space (SCS), including: calculating indicator data according to climatic data of a preset region in a baseline period, and constructing a first SCS by combining the indicator data with production data of a crop in the baseline period; adjusting the climatic data, such that the first SCS moves, and a moving range of the first SCS is combined with the first SCS to form a second SCS, and according to climatic data in a future period, screening optimal indicator data when a production of the crop within SCS is maximum; and constructing a third SCS of the crop with the optimal indicator data of the crop, and optimizing a planting area distribution of the crop to improve a production of the crop in the third SCS.