Reuse of process-based models: automatic transformation into many programming languages and simulation platforms

Cyrille Ahmed Midingoyi,Frédérick Garcia,Gerrit Hoogenboom,Davide Fumagalli,Dean Holzworth,Christophe Pradal,Peter Thorburn,Ioannis N Athanasiadis,Pierre Martre,Marcello Donatelli,Andreas Enders,Cheryl Porter,Hélène Raynal

doi:10.1093/insilicoplants/diaa007

Abstract

Abstract The diversity of plant and crop process-based modelling platforms in terms of implementation language, software design and architectural constraints limits the reusability of the model components outside the platform in which they were originally developed, making model reuse a persistent issue. To facilitate the intercomparison and improvement of process-based models and the exchange of model components, several groups in the field joined to create the Agricultural Model Exchange Initiative (AMEI). Agricultural Model Exchange Initiative proposes a centralized framework for exchanging and reusing model components. It provides a modular and declarative approach to describe the specification of unit models and their composition. A model algorithm is associated with each model specification, which implements its mathematical behaviour. This paper focuses on the expression of the model algorithm independently of the platform specificities, and how the model algorithm can be seamlessly integrated into different platforms. We define CyML, a Cython-derived language with minimum specifications to implement model component algorithms. We also propose CyMLT, an extensible source-to-source transformation system that transforms CyML source code into different target languages such as Fortran, C#, C++, Java and Python, and into different programming paradigms. CyMLT is also able to generate model components to target modelling platforms such as DSSAT, BioMA, Record, SIMPLACE and OpenAlea. We demonstrate our reuse approach with a simple unit model and the capacity to extend CyMLT with other languages and platforms. The approach we present here will help to improve the reproducibility, exchange and reuse of process-based models.

Highlights

Process-based crop models (PBM) are increasingly developed for a wide range of applications and research purposes
Even though there are key biophysical processes in PBM such as phenology, soil water balance, or biomass production, their modeling differs from one model to another according to the biological details, influenced by the availability of input data and final use of the model
The WOFOST model is implemented in Fortran in the WOFOST Control Centre (WCC) package, in Python in the Python Crop Simulation Environment framework, in Java in the Wageningen Integrated Systems Simulator framework (WISS), in C# in the Biophysical Models Application (BioMA) framework, and in C++ in the Crop Growth Monitoring System (CGMS)

Summary

Introduction

Process-based crop models (PBM) are increasingly developed for a wide range of applications and research purposes. The choice of modeling approaches to represent processes and combine them is one of the main reasons which led to the development of multiple PBM to simulate the same crops (Jones et al 2017). They have often been written repeatedly in several different languages with different software architectures. PBM intercomparison studies (Palosuo et al 2011; Rötter et al 2011; Asseng et al 2013; Aslam et al 2017) have pointed out the variability in model outputs but often without quantifying the sources of uncertainty or analyzing the processes involved. The main limitation comes from compatibility issues between PBM platforms (frameworks) resulting from differences in programming languages that are used and their specificities

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Conclusion