Helios: A Scalable 3D Plant and Environmental Biophysical Modeling Framework

Area of Science:

• Environmental modeling
• Plant physiology
• Computational science

Background:

• Existing environmental models often lack flexibility for integrating diverse systems.
• Accurate simulation of plant processes requires detailed 3D environmental data.
• High-performance computing is crucial for complex, large-scale environmental simulations.

Purpose of the Study:

• Introduce Helios, a novel 3D plant and environmental modeling framework.
• Demonstrate Helios's flexibility in coupling various environmental system models.
• Showcase efficient simulation capabilities using GPU acceleration.

Main Methods:

• Developed Helios as an open-source C++ API for model integration.
• Implemented plug-ins for radiation transport, energy balance, photosynthesis, and LiDAR data processing.
• Utilized graphics processing units (GPUs) for accelerated computations.
• Conducted an orchard study examining leaf-level water use and photosynthesis.

Main Results:

• Helios provides a flexible platform for integrating diverse 3D environmental models.
• GPU acceleration enables efficient simulation of large, detailed domains.
• Leaf-scale variability in water use and photosynthesis was analyzed.
• The study demonstrated the framework's utility in understanding canopy-scale fluxes.

Conclusions:

• Helios offers a powerful and flexible solution for 3D plant and environmental modeling.
• The framework facilitates detailed analysis of complex ecological processes.
• GPU-enhanced simulations allow for unprecedented scale and resolution in environmental studies.