Soil erosion modelling: A bibliometric analysis

Nejc Bezak; Matjaž Mikoš; Pasquale Borrelli; Christine Alewell; Pablo Alvarez; Jamil Alexandre Ayach Anache; Jantiene Baartman; Cristiano Ballabio; Marcella Biddoccu; Artemi Cerdà; Devraj Chalise; Songchao Chen; Walter Chen; Anna Maria De Girolamo; Gizaw Desta Gessesse; Detlef Deumlich; Nazzareno Diodato; Nikolaos Efthimiou; Gunay Erpul; Peter Fiener; Michele Freppaz; Francesco Gentile; Andreas Gericke; Nigussie Haregeweyn; Bifeng Hu; Amelie Jeanneau; Konstantinos Kaffas; Mahboobeh Kiani-Harchegani; Ivan Lizaga Villuendas; Changjia Li; Luigi Lombardo; Manuel López-Vicente; Manuel Esteban Lucas-Borja; Michael Maerker; Chiyuan Miao; Sirio Modugno; Markus Möller; Victoria Naipal; Mark Nearing; Stephen Owusu; Dinesh Panday; Edouard Patault; Cristian Valeriu Patriche; Laura Poggio; Raquel Portes; Laura Quijano; Mohammad Reza Rahdari; Mohammed Renima; Giovanni Francesco Ricci; Jesús Rodrigo-Comino; Sergio Saia; Aliakbar Nazari Samani; Calogero Schillaci; Vasileios Syrris; Hyuck Soo Kim; Diogo Noses Spinola; Paulo Tarso Oliveira; Hongfen Teng; Resham Thapa; Konstantinos Vantas; Diana Vieira; Jae E. Yang; Shuiqing Yin; Demetrio Antonio Zema; Guangju Zhao; Panos Panagos

doi:10.1016/j.envres.2021.111087

Soil erosion modelling: A bibliometric analysis

Nejc Bezak^*, Matjaž Mikoš, Pasquale Borrelli, Christine Alewell, Pablo Alvarez, Jamil Alexandre Ayach Anache, Jantiene Baartman, Cristiano Ballabio, Marcella Biddoccu, Artemi Cerdà, Devraj Chalise, Songchao Chen, Walter Chen, Anna Maria De Girolamo, Gizaw Desta Gessesse, Detlef Deumlich, Nazzareno Diodato, Nikolaos Efthimiou, Gunay Erpul, Peter FienerMichele Freppaz, Francesco Gentile, Andreas Gericke, Nigussie Haregeweyn, Bifeng Hu, Amelie Jeanneau, Konstantinos Kaffas, Mahboobeh Kiani-Harchegani, Ivan Lizaga Villuendas, Changjia Li, Luigi Lombardo, Manuel López-Vicente, Manuel Esteban Lucas-Borja, Michael Maerker, Chiyuan Miao, Sirio Modugno, Markus Möller, Victoria Naipal, Mark Nearing, Stephen Owusu, Dinesh Panday, Edouard Patault, Cristian Valeriu Patriche, Laura Poggio, Raquel Portes, Laura Quijano, Mohammad Reza Rahdari, Mohammed Renima, Giovanni Francesco Ricci, Jesús Rodrigo-Comino, Sergio Saia, Aliakbar Nazari Samani, Calogero Schillaci, Vasileios Syrris, Hyuck Soo Kim, Diogo Noses Spinola, Paulo Tarso Oliveira, Hongfen Teng, Resham Thapa, Konstantinos Vantas, Diana Vieira, Jae E. Yang, Shuiqing Yin, Demetrio Antonio Zema, Guangju Zhao, Panos Panagos

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

91 Citations (Scopus)

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.

Original language	English
Article number	111087
Journal	Environmental Research
Volume	197
DOIs	https://doi.org/10.1016/j.envres.2021.111087
Publication status	Published - 31 Mar 2021

Keywords

Citation analysis
Participatory network
Research impact
Soil erosion modelling
Systematic literature review

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https://edepot.wur.nl/546811Licence: CC BY

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Bezak, N., Mikoš, M., Borrelli, P., Alewell, C., Alvarez, P., Anache, J. A. A., Baartman, J., Ballabio, C., Biddoccu, M., Cerdà, A., Chalise, D., Chen, S., Chen, W., De Girolamo, A. M., Gessesse, G. D., Deumlich, D., Diodato, N., Efthimiou, N., Erpul, G., ... Panagos, P. (2021). Soil erosion modelling: A bibliometric analysis. Environmental Research, 197, Article 111087. https://doi.org/10.1016/j.envres.2021.111087

@article{8934a280b3fd48b0ab273ba60e1777aa,

title = "Soil erosion modelling: A bibliometric analysis",

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",

author = "Nejc Bezak and Matja{\v z} Miko{\v s} and Pasquale Borrelli and Christine Alewell and Pablo Alvarez and Anache, {Jamil Alexandre Ayach} and Jantiene Baartman and Cristiano Ballabio and Marcella Biddoccu and Artemi Cerd{\`a} and Devraj Chalise and Songchao Chen and Walter Chen and {De Girolamo}, {Anna Maria} and Gessesse, {Gizaw Desta} and Detlef Deumlich and Nazzareno Diodato and Nikolaos Efthimiou and Gunay Erpul and Peter Fiener and Michele Freppaz and Francesco Gentile and Andreas Gericke and Nigussie Haregeweyn and Bifeng Hu and Amelie Jeanneau and Konstantinos Kaffas and Mahboobeh Kiani-Harchegani and Villuendas, {Ivan Lizaga} and Changjia Li and Luigi Lombardo and Manuel L{\'o}pez-Vicente and Lucas-Borja, {Manuel Esteban} and Michael Maerker and Chiyuan Miao and Sirio Modugno and Markus M{\"o}ller and Victoria Naipal and Mark Nearing and Stephen Owusu and Dinesh Panday and Edouard Patault and Patriche, {Cristian Valeriu} and Laura Poggio and Raquel Portes and Laura Quijano and Rahdari, {Mohammad Reza} and Mohammed Renima and Ricci, {Giovanni Francesco} and Jes{\'u}s Rodrigo-Comino and Sergio Saia and Samani, {Aliakbar Nazari} and Calogero Schillaci and Vasileios Syrris and Kim, {Hyuck Soo} and Spinola, {Diogo Noses} and Oliveira, {Paulo Tarso} and Hongfen Teng and Resham Thapa and Konstantinos Vantas and Diana Vieira and Yang, {Jae E.} and Shuiqing Yin and Zema, {Demetrio Antonio} and Guangju Zhao and Panos Panagos",

year = "2021",

month = mar,

day = "31",

doi = "10.1016/j.envres.2021.111087",

language = "English",

volume = "197",

journal = "Environmental Research",

issn = "0013-9351",

publisher = "Elsevier",

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Bezak, N, Mikoš, M, Borrelli, P, Alewell, C, Alvarez, P, Anache, JAA, Baartman, J, Ballabio, C, Biddoccu, M, Cerdà, A, Chalise, D, Chen, S, Chen, W, De Girolamo, AM, Gessesse, GD, Deumlich, D, Diodato, N, Efthimiou, N, Erpul, G, Fiener, P, Freppaz, M, Gentile, F, Gericke, A, Haregeweyn, N, Hu, B, Jeanneau, A, Kaffas, K, Kiani-Harchegani, M, Villuendas, IL, Li, C, Lombardo, L, López-Vicente, M, Lucas-Borja, ME, Maerker, M, Miao, C, Modugno, S, Möller, M, Naipal, V, Nearing, M, Owusu, S, Panday, D, Patault, E, Patriche, CV, Poggio, L, Portes, R, Quijano, L, Rahdari, MR, Renima, M, Ricci, GF, Rodrigo-Comino, J, Saia, S, Samani, AN, Schillaci, C, Syrris, V, Kim, HS, Spinola, DN, Oliveira, PT, Teng, H, Thapa, R, Vantas, K, Vieira, D, Yang, JE, Yin, S, Zema, DA, Zhao, G & Panagos, P 2021, 'Soil erosion modelling: A bibliometric analysis', Environmental Research, vol. 197, 111087. https://doi.org/10.1016/j.envres.2021.111087

TY - JOUR

T1 - Soil erosion modelling

T2 - A bibliometric analysis

AU - Bezak, Nejc

AU - Mikoš, Matjaž

AU - Borrelli, Pasquale

AU - Alewell, Christine

AU - Alvarez, Pablo

AU - Anache, Jamil Alexandre Ayach

AU - Baartman, Jantiene

AU - Ballabio, Cristiano

AU - Biddoccu, Marcella

AU - Cerdà, Artemi

AU - Chalise, Devraj

AU - Chen, Songchao

AU - Chen, Walter

AU - De Girolamo, Anna Maria

AU - Gessesse, Gizaw Desta

AU - Deumlich, Detlef

AU - Diodato, Nazzareno

AU - Efthimiou, Nikolaos

AU - Erpul, Gunay

AU - Fiener, Peter

AU - Freppaz, Michele

AU - Gentile, Francesco

AU - Gericke, Andreas

AU - Haregeweyn, Nigussie

AU - Hu, Bifeng

AU - Jeanneau, Amelie

AU - Kaffas, Konstantinos

AU - Kiani-Harchegani, Mahboobeh

AU - Villuendas, Ivan Lizaga

AU - Li, Changjia

AU - Lombardo, Luigi

AU - López-Vicente, Manuel

AU - Lucas-Borja, Manuel Esteban

AU - Maerker, Michael

AU - Miao, Chiyuan

AU - Modugno, Sirio

AU - Möller, Markus

AU - Naipal, Victoria

AU - Nearing, Mark

AU - Owusu, Stephen

AU - Panday, Dinesh

AU - Patault, Edouard

AU - Patriche, Cristian Valeriu

AU - Poggio, Laura

AU - Portes, Raquel

AU - Quijano, Laura

AU - Rahdari, Mohammad Reza

AU - Renima, Mohammed

AU - Ricci, Giovanni Francesco

AU - Rodrigo-Comino, Jesús

AU - Saia, Sergio

AU - Samani, Aliakbar Nazari

AU - Schillaci, Calogero

AU - Syrris, Vasileios

AU - Kim, Hyuck Soo

AU - Spinola, Diogo Noses

AU - Oliveira, Paulo Tarso

AU - Teng, Hongfen

AU - Thapa, Resham

AU - Vantas, Konstantinos

AU - Vieira, Diana

AU - Yang, Jae E.

AU - Yin, Shuiqing

AU - Zema, Demetrio Antonio

AU - Zhao, Guangju

AU - Panagos, Panos

PY - 2021/3/31

Y1 - 2021/3/31

N2 - 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.

AB - 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.

KW - Citation analysis

KW - Participatory network

KW - Research impact

KW - Soil erosion modelling

KW - Systematic literature review

U2 - 10.1016/j.envres.2021.111087

DO - 10.1016/j.envres.2021.111087

M3 - Article

C2 - 33798514

AN - SCOPUS:85104376762

SN - 0013-9351

VL - 197

JO - Environmental Research

JF - Environmental Research

M1 - 111087

ER -

Soil erosion modelling: A bibliometric analysis

Abstract

Keywords

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