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. 2021 Jun:197:111087.
doi: 10.1016/j.envres.2021.111087. Epub 2021 Mar 31.

Soil erosion modelling: A bibliometric analysis

Nejc Bezak  1 Matjaž Mikoš  2 Pasquale Borrelli  3 Christine Alewell  4 Pablo Alvarez  5 Jamil Alexandre Ayach Anache  6 Jantiene Baartman  7 Cristiano Ballabio  8 Marcella Biddoccu  9 Artemi Cerdà  10 Devraj Chalise  11 Songchao Chen  12 Walter Chen  13 Anna Maria De Girolamo  14 Gizaw Desta Gessesse  15 Detlef Deumlich  16 Nazzareno Diodato  17 Nikolaos Efthimiou  18 Gunay Erpul  19 Peter Fiener  20 Michele Freppaz  21 Francesco Gentile  22 Andreas Gericke  23 Nigussie Haregeweyn  24 Bifeng Hu  25 Amelie Jeanneau  26 Konstantinos Kaffas  27 Mahboobeh Kiani-Harchegani  28 Ivan Lizaga Villuendas  29 Changjia Li  30 Luigi Lombardo  31 Manuel López-Vicente  32 Manuel Esteban Lucas-Borja  33 Michael Maerker  34 Chiyuan Miao  35 Sirio Modugno  36 Markus Möller  37 Victoria Naipal  38 Mark Nearing  39 Stephen Owusu  40 Dinesh Panday  41 Edouard Patault  42 Cristian Valeriu Patriche  43 Laura Poggio  44 Raquel Portes  45 Laura Quijano  46 Mohammad Reza Rahdari  47 Mohammed Renima  48 Giovanni Francesco Ricci  22 Jesús Rodrigo-Comino  49 Sergio Saia  50 Aliakbar Nazari Samani  51 Calogero Schillaci  52 Vasileios Syrris  8 Hyuck Soo Kim  53 Diogo Noses Spinola  54 Paulo Tarso Oliveira  55 Hongfen Teng  56 Resham Thapa  57 Konstantinos Vantas  58 Diana Vieira  59 Jae E Yang  53 Shuiqing Yin  35 Demetrio Antonio Zema  60 Guangju Zhao  61 Panos Panagos  8
Affiliations
Free article

Soil erosion modelling: A bibliometric analysis

Nejc Bezak et al. Environ Res. 2021 Jun.
Free article

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.

Keywords: Citation analysis; Participatory network; Research impact; Soil erosion modelling; Systematic literature review.

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