CROSS Harmonization & HPC modelization of FOREST Datasets
ADVANCES CAMBRIC
Pilot CAMBRIC is aimed to show a map of quality and quantity of wood in current state and the evolution among next decades, for the Spanish territory. Two main tasks are required, calculate stocks and simulate its evolution. Herein below we will describe steps accomplished to yield a simulator able to perform this task as well as handle and transform required databases.
As a preliminary requirement, a simulator capable of running on HPC Calendula is required. There is already a web-based simulator, SIMANFOR, capable of running various types of models, based on .NET and C # technology. For this, it was decided to completely reprogram SIMANFOR to meet the Cross-Forest Project.
SIMANFOR is the core of simulation and is able to be deployed in three different environments, i) desktop PC, ii) cloud with the ability of run in different nodes, and iii) HPC, similar to cloud but compatible with MPI and OpenMP communication. Technology is typed Python 3.6 within Dask (Dask Development Team 2016) to support MPI programming (The Open MPI Project ©2004-2020 and Dask Development Team 2016).
SIMANFOR simulator is able to handle different input formats like CSV, EXCEL or JSON, what is defined in simulation input file. Output formats can be the same type as input, and are compatible, so an output can be used as input in a different simulation.
Simulator output can be tuned to represent the amount of wood available for each industry and year within a specific area. These outputs stored in the project database in LOD format, are easily browsable by the sector stakeholders. A very important issue concerning our simulations is the definition of the stand evolution and the different interventions are being performed. Each scenario is stored as JSON file, and stored in the project database. Growth and yield models codification are constitutive key of the simulations, which allow simulator perform changes that occur in each lapse of time. These changes are in size, diameter and height, or in health status. The model should be able to predict mortality or ingrowth of trees. A suitable model includes the following equations: Stand Quality Curves, Diameter and height growth, Mortality, Ingrowth and Taper equations. Ibero models have been developed for Pinus pinaster and for P. sylvestris and programmed for previous version of SIMANFOR, and now transcribed to new SIMANFOR in Python.
For evaluation purposes a non-real test is set up, based on a specific real-based randomly generated set of one hundred plots with one hundred trees per plot. This kind of data provides a balanced source of data, without null data or any other kind of data that can disturb results. The scenario for wood production is used to evaluate this plots, in which trees evolve from 20 to 150 years with 6 thinnings at 20, 30, 40, 50, 65 and 80 years age. Performance measured in computing time compares different versions of SIMANFOR: current online version, linux-PC, windows-PC and HPC (without parallelization). New SIMANFOR is able to provide more tailored outputs, but for comparing purposes only total commercial volume is being analysed.