Crop2ML: An open-source multi-language modeling framework for the exchange and reuse of crop model components

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

doi:10.1016/j.envsoft.2021.105055

Abstract

Process-based crop models are popular tools to analyze and simulate the response of agricultural systems to weather, agronomic, or genetic factors. They are often developed in modeling platforms to ensure their future extension and to couple different crop models with a soil model and a crop management event scheduler. The intercomparison and improvement of crop simulation models is difficult due to the lack of efficient methods for exchanging biophysical processes between modeling platforms. We developed Crop2ML, a modeling framework that enables the description and the assembly of crop model components independently of the formalism of modeling platforms and the exchange of components between platforms. Crop2ML is based on a declarative architecture of modular model representation to describe the biophysical processes and their transformation to model components that conform to crop modeling platforms. Here, we present Crop2ML framework and describe the mechanisms of import and export between Crop2ML and modeling platforms.

Highlights

The wide range of crop process-based models (PBM) reflects the evolution of our knowledge of the soil-plant-atmosphere system and the rich historical development for more than five decades
At the interface between modeling and software engineering, this paper addresses plant and crop model component reuse by proposing the Crop2ML framework
Despite all the differences between PBM plat forms, some common features can be identified that enabled model representation regardless of the platforms’ specificities

Summary

Introduction

The wide range of crop process-based models (PBM) reflects the evolution of our knowledge of the soil-plant-atmosphere system and the rich historical development for more than five decades (reviewed in Jones et al, 2017; Muller and Martre 2019). Most of the PBM are continuous models, formalized using ordinary differential equations, but are implemented as discrete time simulation models using finite difference equations They are commonly decomposed into simpler biophysical functions (e.g. phenology, morphogenesis, resource acquisition, pests and diseases impact) often implemented by recurrent equations with control flows. Asseng et al, 2013; Wang et al, 2017) pointed out the large uncertainty of PBM simulations and have analyzed the sources of uncertainty or the processes involved These intercom parison results showed the potential and limits of PBM and highlighted the need to analyze models at the process level, and to exchange model components describing specific processes between simulation platforms A framework that would allow the exchange of model compo nents between different platforms would give crop modelers the ability to test alternative hypotheses in the same model, helping to reduce epistemic uncertainty

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