The Climate Corporation

Robert P Ewing

John Gates

Steven De Gryze

Harish Sangireddy

Jennifer Holt

Asra Nizami

John Browning Burdick

Michael S Byrns

Maria Antonia Terres

Andrew Robert McGowan

Subfield moisture model improvement in generating overland flow modeling using shallow water calculations and kinematic wave calculations is disclosed. In an embodiment, a computer-implemented data processing method comprises: receiving precipitation data and infiltration data for an agricultural field; obtaining surface water depth data, surface water velocity data, and surface water discharge data for the same agricultural field; determining subfield geometry data for the agricultural field; executing a plurality of water calculations and wave calculations using the subfield geometry data to generate an overland flow model that includes moisture levels for the agricultural field; based on, at least in part, the overland flow model, generating and causing displaying a visual graphical image of the agricultural field comprising a plurality of color pixels having color values corresponding to the moisture levels determined for the agricultural field. Output of the overland flow model is provided to control computers of seeders, planters, fertilizer spreaders, harvesters, or combines to control seeding, planting, fertilizing or irrigation activities in the field.

Sub field moisture model improvement using overland flow modeling with shallow water computations

Subfield moisture model improvement using overland flow modeling with shallow water computations

In an embodiment, the techniques herein include receiving a request for a suggested distribution rate of a particular field-distributed commodity in a particular geographical area. Based on that request, two or more rate models for distribution of the particular field-distributed commodity are computed, where one rate model is a user-tolerance model. The suggested distribution rate of the particular field-distributed commodity is determined by performing Bayesian updating where the user-tolerance model is treated as a prior distribution and distributions for each of the other rate models of the two or more rate models for distribution of the particular field-distributed commodity in the particular geographical area are treated as input data in the Bayesian updating. The determined suggested distribution rate of the particular field-distributed commodity is then sent in response to the received request.

Agricultural management recommendations based on blended model

Growing community of inventors

Puyallup, WA, United States of America

Robert P Ewing