Announcements

Special Issue in SOIL on Advances in dynamic soil modelling across scales now open for submission

This special issue (SI) invites papers that study soil dynamics using numerical and statistical models. The focus will be on the development of model-based representations, or digital twins, of soil systems to study soil processes, dynamics, and functions from the pore to the landscape scale and from diurnal dynamics to millennial evolution. By bringing together modellers and models that work on different spatiotemporal scales, we aim at synergies between soil hydrology, soil physics, soil geography, and soil ecology to develop holistic models that consider soils and their functions as dynamic systems. This SI is an initiative of the International Soil Modeling Consortium and the 3-4D Soil models working group, part of the German Soil Science Society. Further details on the SI and submission can be found here. Submission deadline is Summer 2025.

Special Issue "Critical Zone Observatories Promoting Short- and Long-Term Research at the Cross-Road of Disciplines and Scales" in Journal Hydrological Processes now open for submission

The proposed special issue will welcome studies on the following topics, but not limited to: 

•     CZOs fostering multi-disciplinary research
•     Benefits of long-term measurements for CZ understanding
•     Instrumental development for CZOs studies
•     Modeling long-term CZ behavior
•     Anthropogenic impacts on CZ ecological services and key resources
•     Cross CZOs intercomparison through monitoring and modeling

 Your paper will be well managed by a team of guest editors from different specialties within CZ sciences:

 Jean Marçais (Institut national de la recherche agronomique (INRAE),France), Nicole Fernandez (Cornell University, USA), Jannis Groh (University of Bonn, Germany), Pamela Sullivan (Oregon State University, USA), and Damien Jougnot (Sorbonne University, France)

Submission deadline: Sunday, 31 August 2025 and we look forward to your contributions!More details can be found here.

Featured Paper

Do you want your paper featured?

Please share your recent paper if you want to be featured in the ISMC newsletter. With your contributions, we will select one paper to be featured in every newsletter. Submission can be done here. 

Data correlation structure controls pedotransfer function performance

The use of pedotransfer functions (PTFs) is a viable alternative in the analysis of these processes due to the high costs or difficulty in measuring these properties. We aimed to (1) examine the performance of a physically-based PTF and a pool of empirical PTFs from both temperate and tropical climates to estimate soil water retention under subtropical climate and (2) performed correlation analysis between PTF inputs, outputs and estimation residuals to help gain understanding why some PTFs are more successful than others in a given study area. The study was carried out in the Pelotas River Watershed, Southern Brazil, where samples were taken at 100 locations in the 0–0.20-m soil layer along a 25-km-spatial transect. For each point, clay, silt, fine sand, total sand, and organic carbon contents were measured along with bulk and particle density, macro, micro, and total porosity, and the soil water retention curve. The PTFs were used to estimate field capacity, permanent wilting point, and the available water (AW) content. The performance of PTFs from different climate zones was mixed, and similarity in the data correlation structure between PTF development and application data sets appeared to be a good predictor of their predictive power. There was no clear grouping in such correlation structures within climate-zones, and we conclude that the often claimed geoclimatic difference or similarity between an empirical PTF’s origin and its application site is not, or at least not the sole driver of a PTF’s expected performance. More details can be found here.

Featured Soil Modeller (Sarem Norouzi)

Physics-informed machine learning for digital mapping and proximal sensing of soil properties

Sarem Norouzi is a PhD fellow in the Department of Agroecology - Soil Physics and Hydropedology at Aarhus University. He began his Ph.D. studies in 2023 under the supervision of Professor Lis Wollesen de Jonge. As part of the AI4SoilHealth project, he focuses on developing both classic physics-based models and physics-informed machine learning models for digital mapping and proximal sensing of soil properties.

- Please tell us briefly about yourself and your research interest.

I began my academic journey with a bachelor’s degree in Agriculture Engineering – Water Engineering at Ferdowsi University of Mashhad (FUM), Iran. My time at FUM made me interested in fundamental courses such as Fluid Mechanics, Groundwater Hydrology, and Numerical Analysis. My interest in these subjects motivated me to continue my studies with a master’s degree in the same field at FUM. For my thesis, I worked on solving the general form of the transport (convection-diffusion) equation in curvilinear coordinates. During my master’s, I also had this chance to take extra courses in the Mathematics and Mechanical Engineering Departments, which helped me gain experience with the numerical analysis of partial differential equations and computational fluid mechanics.

In 2019, I started collaborating with two brilliant soil physicists Dr. Morteza Sadeghi and the late Prof. Markus Tuller on several projects centered around developing radiative transfer models for the estimation of soil properties from spectral reflectance measurements, which continued under the supervision of Prof. Lis W. de Jonge. These efforts led to several outcomes, including the invention of a physics-based approach for the rapid retrieval of the entire soil water retention curve from SWIR reflectance measurements. This new method reduces the measurement time from several weeks to 3-4 hours.

-  How did you first become interested in soil modelling and learn about ISMC?

I first encountered soil physics during my bachelor's program, but my serious engagement began in 2018 when I started reading the seminal papers by Markus Tuller and Dani Or on soil water retention and hydraulic conductivity curves. Their work, which accounts for the individual contributions of adsorptive and capillary forces to the matric potential within a physically-based framework, profoundly influenced me. These papers laid the groundwork for our future research, where we demonstrated that different soil water structures (i.e., adsorbed and capillary forms) affect soil reflectance differently. This observation led us to develop a radiative transfer model that directly connects the soil water retention curve to SWIR reflectance.

I learned about the ISMC and their activities through LinkedIn when I was in Iran. I later became a member of the pedotransfer function and land-surface parameterization group, which gave me the opportunity to attend various presentations and present my own work.

- Can you share with us your current research focus? And, please tell us briefly how your research could contribute to ISMC Science Panel’s activities

Besides continuing my research on developing spectroscopic models for soil characterization, I am focused on using physics-informed machine learning methods for large-scale mapping of soil characteristics, such as hydraulic properties and particle size distribution. My goal is to integrate our existing knowledge of these properties into the training of machine learning models. This approach helps us improve the models’ ability to work with sparse, incomplete, and unbalanced datasets, which in turn enhances the spatial coverage and accuracy of the mapped properties.

- Please tell us how can ISMC help you advance in your career?

Engaging with both well-established and early-career soil physicists through ISMC is a valuable opportunity to expand my network and stay informed about the latest advancements in our field. The research groups within ISMC also offer a unique platform for sharing my work and receiving constructive feedback from experts who are involved in this area of study.

- What resources or skills would you recommend that early career members of ISMC should acquire? And how can ISMC help and support early career members in this regard?

Developing a solid background in math and physics is crucial for conducting in-depth and interdisciplinary research. I would recommend that early career members focus on strengthening these foundational skills. ISMC can support early career members by providing opportunities to interact and collaborate with researchers from various disciplines through workshops, seminars, and networking events that allow for the exchange of ideas and knowledge.