SPOTPY

SPOTPY performs parameter calibration, analysis, and optimization for ecological and biogeochemical models.

Key Features:

• Algorithms and Objective Functions: Incorporates eight parameter-estimation algorithms and supports 11 objective functions for assessing model performance.
• Parameter Sampling: Supports sampling from eight parameter distributions to define parameter search spaces.
• Model-Independent Framework: Provides a model-independent interface for integration into ecological models.
• Parallel Computing: Supports parallel execution via the Message Passing Interface (MPI) for multi-node or cluster computing.

Scientific Applications:

• Benchmark Function Parameterization: Applied to parameterization of mathematical benchmark functions including Rosenbrock, Griewank, and Ackley.
• Soil Moisture Modeling: Applied to a one-dimensional soil moisture routine using the van Genuchten-Mualem function.
• Biogeochemistry Model Calibration: Applied to calibration of biogeochemistry models using multiple objective functions and validated across five case studies.

Methodology:

Implements eight parameter-estimation algorithms, 11 objective functions, sampling from eight parameter distributions, a model-independent interface for model integration, and parallel execution via MPI.