Land Surface Model for Precision Irrigation Scheduling
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Solution Overview
Problem
Current irrigation management techniques rely on simplified representations of the soil-plant-atmosphere system, neglecting complex interactions and variations in soil moisture distribution, leading to inefficiencies in water use and nutrient availability, particularly in precision agriculture.
Innovation Solution
A system and method combining weather and climatological data with land surface models and crop-specific information to simulate the soil-plant-atmosphere system, incorporating spatially-varying soil composition, crop growth stages, and real-time moisture conditions to optimize irrigation scheduling and nutrient application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simplified representations of the soil-plant-atmosphere system are used, then the model complexity is reduced and ease of operation is improved, but the manufacturing precision and measurement precision of soil moisture distribution are worsened
Solution Approach 1:
The patent divides the field into multiple management zones with distinct soil types and moisture characteristics. Each zone is modeled separately with its own soil parameters, crop coefficients, and moisture dynamics, allowing the system to capture spatial variability while maintaining manageable complexity through modular zone-based processing
Solution Approach 2:
The patent applies local quality by assigning different soil parameters, crop coefficients, and moisture dynamics to specific management zones based on their unique characteristics. Each zone receives customized irrigation recommendations tailored to its local soil type, slope, and crop stage, improving precision without requiring a complete overhaul of the modeling approach
2Device complexity
If simplified representations of the soil-plant-atmosphere system are used, then the device complexity is reduced, but the reliability of irrigation management decisions is worsened
Solution Approach 1:
The system segments the complex soil-plant-atmosphere system into manageable components: soil moisture dynamics, evapotranspiration calculations, crop growth stages, and irrigation scheduling. Each component is handled through dedicated algorithms and data structures, reducing overall system complexity while maintaining reliability through specialized processing for each function
Solution Approach 2:
The patent introduces an intermediary layer of management zones that act as mediators between the complex physical system and the irrigation decision-making process. These zones aggregate spatial variability and translate it into zone-level parameters that can be processed by standard irrigation models, bridging the gap between complexity and simplicity
3Manufacturing precision
If spatially-varying soil composition and real-time moisture conditions are incorporated, then the manufacturing precision of irrigation recommendations is improved, but the device complexity and loss of information are worsened
Solution Approach 1:
The patent segments the field into management zones based on soil composition and moisture characteristics, processing each zone separately with its own parameter set. This segmentation allows the system to handle spatial variability and complex soil-plant-atmosphere interactions while maintaining manageable computational complexity through zone-level aggregation
Solution Approach 2:
The patent adds the spatial dimension by incorporating x and y coordinates for each management zone, allowing the system to track and process soil moisture, evapotranspiration, and irrigation needs across the field landscape. This dimensional approach enables precise spatial mapping of irrigation requirements without requiring overly complex point-by-point analysis
4Measurement precision
If spatially-varying soil composition and real-time moisture conditions are incorporated, then the measurement precision of soil moisture distribution is improved, but the loss of time for data processing is worsened
Solution Approach 1:
The patent segments the field into a limited number of management zones (typically 3-10 zones per field) rather than processing every individual measurement point. This segmentation reduces the computational burden of processing spatially-varying data while maintaining measurement precision at the zone level, achieving a practical balance between detail and processing time
Solution Approach 2:
The patent processes data at the management zone level rather than at the finest possible resolution, applying partial action by aggregating measurements within each zone. This approach provides sufficiently precise irrigation recommendations for practical decision-making without requiring the excessive computational resources needed for point-by-point analysis of every soil moisture sensor reading
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances irrigation efficiency by providing precise, spatially-variable recommendations for irrigation, reducing water and nutrient losses, and promoting optimal crop growth by tailoring irrigation to the specific needs of different field zones and crop stages.
Implementation Method 1
Evaporation accounts for the conversion of liquid water resident near the soil surface or on the plant itself into a gaseous form
Implementation Method 2
Transpiration is the process by which moisture is carried through plants from roots to small pores on the leaves (called 'stomata'), where it changes to vapor and is released to the atmosphere
Implementation Method 3
The heat lost from the plant during evaporation from the plant stomata maintains an acceptable temperature within the plant system. The loss of water through transpiration is regulated by guard cells on the sides of the stomata
Data Source
AI summary
An irrigation modeling framework in precision agriculture utilizes a combination of weather data, crop data, and other agricultural inputs to create customized agronomic models for diagnosing and predicting a moisture state in a field, and a corresponding need for, and timing of, irrigation activities. Specific combinations of various agricultural inputs can be applied, together with weather information to identify or adjust water-related characteristics of crops and soils, to model optimal irrigation activities and provide advisories, recommendations, and scheduling guidance for targeted application of artificial precipitation to address specific moisture conditions in a soil system of a field.