Research Excellence Award
Javad Momeni Damaneh
Hormozgan University (Alumnus), Iran.
Javad Momeni Damaneh is an Iranian researcher and alumnus of Hormozgan University working in environmental science. His research applies machine learning and species distribution modeling to ecological niche prediction, soil erosion susceptibility and groundwater quality. He is nominated for the Research Excellence Award at the International Soil Scientist Awards in recognition of his contributions to environmental modeling [1][2].
Abstract
This article presents the research profile of Javad Momeni Damaneh in connection with the Research Excellence Award. His work uses machine learning and maximum entropy modeling to predict the distribution of ecologically important plant species [1], to assess soil erosion susceptibility [2], and to evaluate spatial variation in groundwater quality [3]. His Scopus record lists six documents and 47 citations [5].
Keywords
Machine learning, ecological niche modeling, soil erosion susceptibility, maximum entropy, groundwater quality, spatial interpolation, drylands, land degradation.
Introduction
Dryland and semi-arid environments face pressures from soil degradation, vegetation loss and declining water quality. Data-driven spatial modeling has become an important approach for understanding these processes and for supporting land management decisions. Javad Momeni Damaneh’s publications apply such methods to rangeland species, erosion-prone basins and aquifers, mainly in Iran [1][4].
Research Profile
Momeni Damaneh is an alumnus of Hormozgan University, and his subject area is environmental science. His Scopus Author ID is 58000716900. The profile shows six documents, 47 citations and an h-index of 2 [5]. His research covers three main themes:
- Species distribution and ecological niche modeling
- Soil erosion assessment and land degradation
- Geostatistical analysis of groundwater quality
Research Contributions
In ecological informatics, Momeni Damaneh and co-authors compared machine learning models to predict the ecological niche of wild pistachio, providing spatial information relevant to conservation and land-use planning [1]. A related study used the maximum entropy model to predict the growth of Ferula assa-foetida L. in northeastern Iran, published in the Iranian Journal of Range and Desert Research.
In water resources, he co-authored an evaluation of interpolation methods for mapping groundwater qualitative parameters in the Gonabad Plain [3].
Publications
- Momeni Damaneh, J., Ahmadi, J., Rahmanian, S., Sadeghi, S. M. M., Nasiri, V., & Borz, S. A. (2022). Prediction of wild pistachio ecological niche using machine learning models. Ecological Informatics, 72, 101907. https://doi.org/10.1016/j.ecoinf.2022.101907 [1]
- Momeni Damaneh, J., Safdari, A. A., Azarnejad, N., Ghorbani, M., Panahi, F., et al. (2025). Modeling soil erosion susceptibility using machine learning techniques: Rud-e-Faryab Basin, Iran. Land Degradation & Development, 36(18), 6396–6409. [2]
- Momeni Damaneh, J., Joulaei, F., Alidadi, H., & Peiravi, R. (2015). Evaluation of interpolation methods to determine spatial variations of groundwater qualitative parameters (Case study: Gonabad Plain). Journal of Research in Environmental Health, 1(3), 165–176. [3]
Research Impact
According to the figures supplied for this profile, the 2022 wild pistachio study has received 51 citations, the 2022 chapter on soil erosion control in drylands 30, the 2015 groundwater interpolation study 21, the 2021 Ferula assa-foetida study 15 and the 2025 erosion susceptibility study 8. These counts come from a citation database and may differ from the Scopus total of 47 because of differences in coverage and update timing [5]. The practical value of this work lies in its support for conservation planning, erosion control and groundwater monitoring in dryland regions.
Award Suitability
Momeni Damaneh is considered suitable for the Research Excellence Award on the following grounds:
- Publications in international peer-reviewed journals and an academic book volume [1][2]
- Application of machine learning to soil and ecological problems
- Research relevant to land degradation and sustainable land management
- A publication record spanning from 2015 to 2025
Conclusion
Javad Momeni Damaneh’s research demonstrates a sustained focus on environmental modeling with relevance to soils, vegetation and water resources. His nomination for the Research Excellence Award at the International Soil Scientist Awards recognizes the practical orientation and methodological breadth of his work [1][2].
External Links
References
- Momeni Damaneh, J., Ahmadi, J., Rahmanian, S., Sadeghi, S. M. M., Nasiri, V., & Borz, S. A. (2022). Prediction of wild pistachio ecological niche using machine learning models. Ecological Informatics, 72, 101907.
https://doi.org/10.1016/j.ecoinf.2022.101907
- Momeni Damaneh, J., Safdari, A. A., Azarnejad, N., Ghorbani, M., Panahi, F., et al. (2025). Modeling soil erosion susceptibility using machine learning techniques: Rud-e-Faryab Basin, Iran. Land Degradation & Development, 36(18), 6396–6409.
https://onlinelibrary.wiley.com/journal/10991530
- Momeni Damaneh, J., Joulaei, F., Alidadi, H., & Peiravi, R. (2015). Evaluation of interpolation methods to determine spatial variations of groundwater qualitative parameters (Case study: Gonabad Plain). Journal of Research in Environmental Health, 1(3), 165–176.
https://www.researchgate.net/publication/373330915
- Momeni Damaneh, J., Esmaeilpour, Y., Gholami, H., & Farashi, A. (2021). Properly predict the growth of Ferula assa-foetida L. in northeastern Iran using the maximum entropy model. Iranian Journal of Range and Desert Research, 28(3), 578–592.
https://orcid.org/0009-0006-9131-6167
- Elsevier. (n.d.). Scopus author details: Javad Momeni Damaneh, Author ID 58000716900. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=58000716900