@article{8772142,
  abstract     = {{Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.}},
  articleno    = {{111087}},
  author       = {{Bezak, Nejc and Mikos, Matjaz and Borrelli, Pasquale and Alewell, Christine and Alvarez, Pablo and Ayach Anache, Jamil Alexandre and Baartman, Jantiene and Ballabio, Cristiano and Biddoccu, Marcella and Cerda, Artemi and Chalise, Devraj and Chen, Songchao and Chen, Walter and De Girolamo, Anna Maria and Gessesse, Gizaw Desta and Deumlich, Detlef and Diodato, Nazzareno and Efthimiou, Nikolaos and Erpul, Gunay and Fiener, Peter and Freppaz, Michele and Gentile, Francesco and Gericke, Andreas and Haregeweyn, Nigussie and Hu, Bifeng and Jeanneau, Amelie and Kaffas, Konstantinos and Kiani-Harchegani, Mahboobeh and Lizaga Villuendas, Ivan and Li, Changjia and Lombardo, Luigi and Lopez-Vicente, Manuel and Esteban Lucas-Borja, Manuel and Maerker, Michael and Miao, Chiyuan and Modugno, Sirio and Moeller, Markus and Naipal, Victoria and Nearing, Mark and Owusu, Stephen and Panday, Dinesh and Patault, Edouard and Patriche, Cristian Valeriu and Poggio, Laura and Portes, Raquel and Quijano, Laura and Rahdari, Mohammad Reza and Renima, Mohammed and Ricci, Giovanni Francesco and Rodrigo-Comino, Jesus and Saia, Sergio and Samani, Aliakbar Nazari and Schillaci, Calogero and Syrris, Vasileios and Kim, Hyuck Soo and Spinola, Diogo Noses and Oliveira, Paulo Tarso and Teng, Hongfen and Thapa, Resham and Vantas, Konstantinos and Vieira, Diana and Yang, Jae E. and Yin, Shuiqing and Zema, Demetrio Antonio and Zhao, Guangju and Panagos, Panos}},
  issn         = {{0013-9351}},
  journal      = {{ENVIRONMENTAL RESEARCH}},
  keywords     = {{LAND-USE,RESEARCH TRENDS,SEDIMENT YIELD,ORGANIC-CARBON,CLIMATE-CHANGE,WATER EROSION,LOESS PLATEAU,IMPACT,SUSCEPTIBILITY,LANDSLIDES,Soil erosion modelling,Research impact,Participatory network,Systematic literature review,Citation analysis}},
  language     = {{eng}},
  pages        = {{16}},
  title        = {{Soil erosion modelling : a bibliometric analysis}},
  url          = {{http://doi.org/10.1016/j.envres.2021.111087}},
  volume       = {{197}},
  year         = {{2021}},
}

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