Risk-Based Irrigation Using Satellite Data Reconciliation
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Solution Overview
Problem
Existing methods for monitoring soil moisture levels, such as probe-based techniques, provide estimates that are difficult to scale up to field level and are costly to maintain, while deterministic-based estimation models lack the ability to assimilate observations and propagate uncertainty, making them inadequate for risk-based irrigation management.
Innovation Solution
A system and method for risk-based irrigation management that uses a hydrology model to perform both observation-based and deterministic-based estimates, reconciling conflicts between the two using a reconciliation algorithm to generate accurate soil moisture content modeling values, thereby facilitating risk-based irrigation decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If probe-based methods are used to measure soil moisture levels, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses satellite remote sensing to create a copy or representation of soil moisture conditions over large areas, replacing the need for physical probes in every location. The satellite data provides a spatially distributed model that replicates what probes would measure, enabling field-scale monitoring without deploying numerous expensive probes.
Solution Approach 2:
The patent replaces mechanical probe-based measurement systems with a satellite-based remote sensing system. Instead of using physical sensors that require installation and maintenance in the soil, the system uses satellite imagery and hydrological models to estimate soil moisture, eliminating the mechanical complexity of probe deployment.
2Productivity
If deterministic-based estimation models are used, then productivity is improved, but reliability deteriorates due to inability to assimilate observations and propagate uncertainty
Solution Approach 1:
The patent implements a feedback mechanism where satellite observations are assimilated into the hydrological model to update and correct the model's state. This allows the deterministic model to incorporate real-world measurements, improving its reliability by reducing accumulated errors and maintaining accuracy over time through continuous observation integration.
Solution Approach 2:
The patent creates a composite modeling approach that combines deterministic hydrological models with satellite-based remote sensing observations. This hybrid system integrates the computational efficiency of deterministic models with the observational accuracy of satellite data, producing a more reliable estimation system that leverages the strengths of both approaches.
3Measurement precision
If distributed models are used, then measurement precision is improved with spatial details, but device complexity increases
Solution Approach 1:
The patent uses a universal satellite-based remote sensing system that can provide distributed soil moisture information across diverse landscapes and soil types. The satellite platform performs multiple functions including optical imaging, thermal sensing, and hydrological parameter estimation, enabling spatially detailed monitoring without requiring location-specific complex instrumentation for each field area.
Data Source
AI summary
A system for risk-based management of irrigation may perform an initial assimilation for a first layer of soil, wherein the initial assimilation for the first layer of the soil is based on water input data and an initial water withdrawal estimate. The system may perform a deterministic-based estimate to generate deterministic-based estimate values for one or more additional layers of the soil. The system may perform an observation-based estimate to generate observation-based estimate values for the one or more additional layers of the soil. The system may generate soil moisture content modelling values based on the observation-based estimate values and the deterministic-based estimate values, the soil moisture content modelling values generated by applying a reconciliation algorithm to reconcile conflict between the deterministic-based estimate values and the observation-based estimate values.