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Announcements + Featured Paper + Featured Soil Modeller

4th ISMC Conference

More than 125 abstracts have been submitted to the 9 sessions of the 4th ISMC conference held in Tianjin, China, between 7th and 10th of May, 2024.  The program contained 5 plenary keynotes and 9 session keynotes. Overall, about 200 scientists from Europe, Asia, and the Americas attended the conference and had a full program of excellent oral and poster presentations. The full program with all conference abstracts can be downloaded here.

ISMC would like to thank the local organization team, especially Yonggen Zhang from Tianjin University and all his helping hands for the perfect organization of the conference and excursion.  
Photos of the conference can be accessed here and if you are interested, follow us on LinkedIn.


Opening of the 4th ISMC Conference 
Top left, Prof. Jiubin Chen, the vice dean of the school of Earth System Sciences chair the opening session. Top right, the opening speech by Prof. Jinlong Gong, the Vice president of Tianjin University. Bottom left, opening speech by Academician Congqiang Liu, the dean of the School of Earth System Sciences at Tianjin University, and Bottom right, ISMC Co-Chair Dr. Yijian Zeng from the University of Twente. 

ISMC Awards 2024

The biennial Rien van Genuchten Award issued for outstanding contributions to the understanding of flow and transport processes in soils has been awarded to Paolo Nasta from the University of Naples Federico II, Italy.


The Early Career Award is dedicated to recognizing outstanding scientific achievements made by early career researchers in the field of soil and vadose zone sciences and has been awarded to  Nasrollah Sepehrnia from University of Aberdeen, UK.

The ISMC paper award honoring a significant impact in modeling soil processes, consistent with the mission of ISMC has been awarded to Pamela. L. Sullivan from Oregon State University for her paper entitled “Embracing the dynamic nature of soil structure: A paradigm illuminating the role of life in critical zones of the Anthropocene”.

Additionally, the best 3 posters were awarded during the 4th ISMC conference to young scientists.
1. Wenhao Shi from Tianjin University for his poster “Exploring the relationship between soil hydraulic parameters and soil basic properties within dual-modal porous media ”
2. Liantao Niu from the Chinese Academy of Sciences for her poster “Water and Nitrate Transport Through the Vadose Zone Under Orchard Expansion in A Cultivated Loess Critical Zone”
 3. Jiong Zhu from Wuhan University, China or his poster “Forward and Inverse Modelling   
  of Soil Water Flow in Layered Soil: A Perspective from Frequency Domain”
 4. Yanqiao Li from China Agricultural University for his poster “Spatio-Temporal Risks of Phosphorus Losses in Sloping Farmland under Future Climate in the Black Soil Region

Poster awardees of the 4th ISMC conference

ISMC co-sponsored at EGU 2024 a full success

The ISMC co-sponsored session  Vadose Zone Hydrology: Advances and Future Perspectives in Soil Hydrologic Processes has been a full success with  29 oral presentations, 23 posters, and 2 virtual posters. Many thanks to the convenors Roland Baatz,  Thomas Baumgartl, Stefano Ferraris, Teamrat Ghezzehei, Martine van der Ploeg, and Harry Vereecken for the organization

Call for abstracts for the ERB 2024 Conference September 2024 Inca, Mallorca, Spain

The 19th biennial Conference ERB 2024 “Hydrological investigations in human- and climate change impacted small catchments” will be held between 17th-20th September 2024 Inca, Mallorca, Spain. More information 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.

Evaluating the extrapolation potential of random forest digital soil mapping
Spatial soil information is essential for informed decision-making in a wide range of fields. Digital soil mapping (DSM) using machine learning algorithms has become a popular approach for generating soil maps. DSM capitalises on the relation between environmental variables (i.e., features) and a soil property of interest. It typically needs a training dataset that covers the feature space well. Mapping in areas where there are no training data is challenging, because extrapolation in geographic space often induces extrapolation in feature space and can seriously deteriorate prediction accuracy. The objective of this study was to analyse the extrapolation effects of random forest DSM models by predicting topsoil properties (OC, clay, and pH) in four African countries using soil data from the ISRIC Africa Soil Profiles database. The study was conducted in eight experiments whereby soil data from one or three countries were used to predict in the other countries. We calculated similarities between donor and recipient areas using four measures, including soil type similarity, homosoil, dissimilarity index by area of applicability (AOA), and quantile regression forest (QRF) prediction interval width. The aim was to determine the level of agreement between these four measures and identify the method that had the strongest agreement with common validation metrics. The results indicated a positive correlation between soil type similarity, homosoil and dissimilarity index by AOA. Surprisingly, we observed a negative correlation between dissimilarity index by AOA and QRF prediction interval width. Although the cross-validation results for the trained models were acceptable, the extrapolation results were unsatisfactory, highlighting the risk of extrapolation. Using soil data from three countries instead of one increased the similarities for all measures, but it had a limited effect on improving extrapolation. Also, none of the measures had a strong correlation with the validation metrics. This was particularly disappointing for AOA and QRF, which we had expected to be strong indicators of extrapolation prediction performance. Results showed that homosoil and soil type methods had the strongest correlation with validation metrics. The results for this case study revealed limitations of using AOA and QRF as measures of extrapolation effects, highlighting the importance of not relying on these methods blindly. Further research and more case studies are needed to address the effects of extrapolation of DSM models.

More details can be found here

Featured Soil Modeller Maite Jiménez

Evaluating Water Use in Agricultural Systems
Maite Jiménez is a researcher at the Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM) of the Universidad Politécnica de Madrid (UPM), Spain. During her PhD at the Agri-Food Research and Technology Centre of Aragon (CITA) in Zaragoza, she studied agricultural engineering at this university and specialized in environmental and irrigation modelling. She focused on evaluating soil-water use in agricultural systems and monitoring irrigation return flows and their environmental impact. Before, she joined the private sector for hydrological and snow reservoir modelling at high mountains and continued her professional pathway at consulting companies.

- Please tell us briefly about yourself and your research interest.
The sustainable use of available resources and improving efficiency are key under the current environmental context. Therefore, I was fascinated by the possibility of doing my PhD addressing the agronomic and environmental challenges faced by the modernization of irrigation systems, revealing the complex paradox of efficient water use in agriculture. To this end, analyzing many data types (water, edaphological, meteorological, etc) and applying computer tools, such as hydrogeological modelling, was necessary. At this point, I got into modelling using software packages such as HYDRUS 1D or MODFLOW during my doctoral training or currently with SWAT.

-  How did you first become interested in soil modelling and learn about ISMC?
The agronomical and environmental analysis should be based on understanding the soil-plant-water system. So, soil knowledge becomes a key factor in this work when evaluating the modernization of the irrigation system. In this line, the soil map of the study area in my PhD work was developed for hydrologic modelization purposes. This led me to a HYDRUS 1D training short course in Prague with Jirka Šimůnek or a three-month stay at Colorado State University for a MODFLOW model of the irrigated area.
I learned deeply about ISMC at my current position at CEIGRAM invited by Prof. Ana María Tarquis. Nevertheless, I had been checking the web previously.

-Can you share with us your current research focus? And, please tell us briefly how your research could contribute to the ISMC Science Panel’s activities
As a continuation of the agricultural water use research line, I am currently engaged in evaluating water demand for agricultural use under climate change scenarios. This is the main objective of the AGUAGRADA project. The project pretends the modelization at sub-basin level with SWAT as the primary hydrologic tool integrating the soil-crop-water system. The crop modelization of the system also aims to be improved with AQUACROP. Afterwards, the climate change scenarios will be introduced to analyze the potential adaptation strategies for this climate change.

-Please tell us how ISMC can help you advance in your career.
ISMC is the perfect meeting point for soil modellers. ISMC provides the opportunity to establish interactions between international researchers. Also, it offers the perfect auditorium for exchange and, of course, to improve our soil modelling knowledge, especially for young modellers.

- 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?
That is an excellent question I would like someone to tell me about it!! As an early career member, I would like to acquire every skill of senior researchers and become a DaVinci, but it is impossible for sure. At this point, I found some fundamental skills: observation and analysis capacity to get into the system processes to be modelled; and to be patient in setting up the model, the self-learning and the trial and error methodology are going to be the general procedure in modelling. On the other hand, there are those methodological skills related to learning aspects (physical, chemical, and biological processes, software management, programming, etc) that ISMC is the perfect network place to improve it.

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