DEVELOPMENT OF ADVANCED CALIBRATION PROTOCOLS FOR SOIL-CROP MODELS IN THE AgMIP CALIBRATION INITIATIVE

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INRAE presentation

The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a major player in research and innovation. It is a community of 12,000 people with 272 research, experimental research, and support units located in 18 regional centres throughout France. Internationally, INRAE is among the top research organisations in the agricultural and food sciences, plant and animal sciences, as well as in ecology and environmental science. It is the world’s leading research organisation specialising in agriculture, food and the environment. INRAE’s goal is to be a key player in the transitions necessary to address major global challenges. Faced with a growing world population, climate change, resource scarcity, and declining biodiversity, the Institute has a major role to play in building solutions and supporting the necessary acceleration of agricultural, food and environmental transitions.

Work environment, missions and activities

Context

Process-based soil-crop models play a crucial role in agronomic research by enabling the characterization and prediction of crop performance under diverse environmental and management conditions. The accuracy and reliability of these models strongly depend on their calibration, which involves estimating parameter values to minimize discrepancies between model outputs and experimental observations.

Despite numerous advancements, a consensus on best practices for calibrating these models remains lacking. The Agricultural Model Intercomparison and Improvement Project (AgMIP) Calibration initiative has been addressing this challenge by developing standardized calibration protocols and by fostering international collaboration to evaluate them on various soil-crop models (see e.g. Wallach et al. 2023, 2024). These protocols leverage advanced statistical methods to improve model parameterization, ultimately enhancing predictive accuracy and robustness.

Their evaluation across a large number of models have been greatly facilitated by the use and development of the R package CroptimizR which provides a generic interface specifically designed to connect crop models with various parameter estimation algorithms. The protocols and methods developed within AgMIP Calibration are systematically implemented with CroptimizR, making it possible to apply them to any crop model for which an interface has been developed and to various dataset. This allows for a rigorous comparison of results obtained with different models and calibration methods.

This postdoctoral position is part of the ongoing AgMIP Calibration project and aims to refine existing calibration protocols by integrating novel algorithms for parameter selection and optimization. The work will contribute to the development and dissemination of improved methodologies within the international soil-crop modeling community.

Activities

The selected candidate will join the CAPTE team at the EMMAH laboratory (INRAE Avignon), where the CroptimizR package is developed, and will work in close collaboration with the AgMIP Calibration co-leaders and the wider community of international modelers involved in AgMIP.

The main responsibilities will include:

• Conducting a literature review to identify relevant global optimization algorithms suitable for high-dimensional parameter spaces.
• Implementing and integrating selected parameter selection and global optimization algorithms into the CroptimizR package.
• Applying these algorithms to multiple soil-crop models (e.g., STICS, DSSAT-CERES, APSIM NextGen, SiriusQuality2) using already available real-world experimental datasets and associated model configurations.
• Characterizing the response surfaces of the optimization problems to better understand their structure and associated challenges and optimizing the hyper-parameters of the selected methods to enhance their efficiency and robustness.
• Evaluating the performance of alternative AgMIP calibration protocols, incorporating these algorithms, on the selected models and datasets.
• Engaging with the international AgMIP modeling community to discuss results obtained with the different models.
• Contributing to the dissemination of results through scientific publications, presentations at AgMIP meetings, and updates to the CroptimizR software package.

 Depending on the availability of the candidate, the position can start between the  1st June 2025 and 1st October 2025

Training and skills

•    PhD in applied mathematics, statistics, computational sciences, or related disciplines. PhD in agronomy or related fields will also be considered.
•    Expertise in parameter estimation and optimization techniques.
•    Experience in statistical methods for variable selection, global optimization and/or Bayesian estimation.
•    Strong proficiency in R programming.
•    Knowledge of process-based soil-crop models and their calibration methodologies is a plus.
•    Demonstrated ability to publish scientific articles in peer-reviewed journals.
•    Fluency in English (written and spoken).
•    Teamwork and communication skills.

INRAE's life quality

By joining our teams, you benefit from (depending on the type of contract and its duration):

- up to 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);
- parenting support: CESU childcare, leisure services;
- skills development systems: training, career advise;
- social support: advice and listening, social assistance and loans;
- holiday and leisure services: holiday vouchers, accommodation at preferential rates;
- sports and cultural activities;
- collective catering.

How to apply

I send my CV and my motivation letter