Rotational Grazing Optimizer

Challenge

A North Texas cattle operation managed multiple paddocks across varied terrain — hilltops, creek bottoms, and newly seeded pastures — each responding differently to weather and grazing pressure. Rotation decisions were made by feel, risking overgrazing during dry spells and underutilizing forage during growth windows.

Solution

Built a system dynamics simulation engine that models forage growth, soil moisture, and carrying capacity across every paddock simultaneously. The engine integrates real-time weather data — daily precipitation, evapotranspiration, and temperature — to forecast paddock conditions and recommend optimal rotation timing.

• Weather-driven forage growth model using Euler integration with daily time steps
• Per-paddock calibration accounting for terrain, shade, and drainage characteristics
• Two-move-ahead optimizer that evaluates rotation candidates against projected conditions
• Historical simulation mode to reconstruct current paddock state from planting and weather records

Impact

• Rotation decisions shifted from intuition to data-driven recommendations
• Optimizer evaluates all viable moves in under 120ms, enabling real-time decision support
• Forage utilization improved by avoiding premature moves during active growth periods
• System adapts automatically to weather variability without manual recalibration