Customized land surface modeling in a soil-crop system using satellite data to detect irrigation and precipitation events for decision support in precision agriculture

A method, comprising:

• within a computing environment comprised of a computer processor and at least one computer-readable storage medium operably coupled to the computer processor and having program instructions stored therein, the computer processor being operable to execute the program instructions to assess a state of moisture content of a soil-crop system in a particular field over time in an irrigation advisory model by:
• predicting expected weather conditions impacting moisture conditions at multiple depths of a crop root zone in the soil-crop system in the particular field, by applying weather and climatological information comprised of historical field-level weather data and extended-range weather forecast data to one or more predictive numerical weather models;
• simulating crop water usage over time, soil moisture depletion at multiple depths within the soil-crop system over time and soil-water characteristics at the multiple depths relative to one or more crop growth stages over a crop growing season in the particular field, by aggregating the expected weather conditions, crop-specific information, and soil profile data in a customized land surface model;
• analyzing remotely-sensed imagery data to resolve inconsistencies in spatial and thermal resolutions to diagnose soil-crop moisture data for the particular field, by applying one or more disaggregation functions to identify moisture content at a specific spatial element between the images, and one or more fusion functions to identify moisture content at a specific temporal element within the images, the specific spatial element and the specific temporal element enabling an estimate of historical irrigation and other precipitation events for the particular field from the soil-crop moisture data the one or more disaggregation functions operating to normalize soil-crop moisture data represented in different spatial resolutions of the images to identify an occurrence of the prior irrigation activity in the particular field, and not a neighboring field represented within a spatially-similar coarse pixel resolution of the images, and the one or more fusion functions operating to normalize soil-crop moisture data within images taken at different times to identify which specific day the prior irrigation activity occurred that is within a time span relative to data from overpasses for the particular field;
• adjusting one or more simulation parameters in the land surface model based on identified differences between the simulations, and the estimate of historical irrigation and other precipitation events for the particular field from the soil-crop moisture data, and estimating moisture content in the soil-crop system at any point in the crop growing season in one or more additional simulations,
• wherein the soil-water characteristics include a depth profile of water extraction by the crop at the one or more growth stages, and an impact of prior irrigation activity on the state of moisture content, to profile root zone moisture from the simulated from the simulated crop water usage over time, soil moisture depletion and the soil-water characteristics;
• and
• developing an irrigation schedule from the profile of root zone moisture for delivering an application of water for the particular field, wherein a user applies water to the particular field based on the irrigation schedule or an automated application of water is controlled based on the irrigation schedule.

A system comprising:

• a computing environment including at least one computer-readable storage medium having program instructions stored therein and a computer processor operable to execute the program instructions to assess a state of moisture content of a soil-crop system in the particular field over time in an irrigation advisory model within a plurality of data processing modules, the plurality of data processing modules including:
• a weather modeling module configured to predict expected weather conditions impacting moisture conditions at multiple depths of the soil-crop system in the particular field, by applying weather and climatological information comprised of historical field-level weather data and extended-range weather forecast data to one or more predictive numerical weather models;
• one or more modules configured to simulate crop water usage over time, soil moisture depletion at multiple depths within the soil-crop system over time and soil-water characteristics at the multiple depths relative to one or more crop growth stages over a crop growing season in the particular field, by aggregating the expected weather conditions, crop-specific information, soil profile data, and the estimate of historical irrigation and other precipitation events for the particular field in a customized land surface model, and
• one or more modules configured to analyze remotely-sensed imagery data to resolve inconsistencies in spatial and thermal resolutions to diagnose soil-crop moisture data for the particular field, by applying one or more disaggregation functions to identify moisture fluxes at a specific spatial element between the images, and one or more fusion functions to identify moisture fluxes at a specific temporal element within the images, the specific spatial element and the specific temporal element enabling an estimate of historical irrigation and other precipitation events for the particular field from the soil-crop moisture data, the one or more disaggregation functions operating to normalize soil-crop moisture data represented in different spatial resolutions of the images to identify an occurrence of the prior irrigation activity in the particular field, and not a neighboring field represented within a spatially-similar coarse pixel resolution of the images, and the one or more fusion functions operating to normalize soil-crop moisture data within images taken at different times to identify which specific day the prior irrigation activity occurred that is within a time span relative to data from overpasses for the particular field, and adjust one or more simulation parameters in the land surface model based on identified differences between the simulations, and the estimate of historical irrigation and other precipitation events for the particular field from the soil-crop moisture data, and estimating moisture content in the soil-crop system at any point in the crop growing season in one or more additional simulations,
• wherein the soil-water characteristics include a depth profile of water extraction by the crop at the one or more growth stages, and an impact of prior irrigation activity on the state of moisture content, to profile root zone moisture from the simulated crop water usage over time, soil moisture depletion and the soil-water characteristics;
• and
• an irrigation scheduling module configured to develop an irrigation schedule from the profile of root zone moisture for delivering an application of water for the particular field, wherein a user applies water to the particular field based on the irrigation schedule or an automated application of water is controlled based on the irrigation schedule.