Soil erosion modelling: A global review and statistical analysis

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: http://doi.org/10.1016/j.scitotenv.2021.146494. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Authors

Pasquale Borrelli, Christine Alewell, Pablo Alvarez, Jamil Alexandre Ayach Anache, Jantiene Baartman, Cristiano Ballabio, Nejc Bezak, 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 Märker, Chiyuan Miao, Matjaž Mikoš, 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

Abstract

To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling 1994-2017. Our aim was to identify (i) processes and models most frequently addressed in the literature, (ii) regions within which models are primarily applied, (iii) what regions remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we merged the knowledge of a group of 66 soil-erosion scientists from 67 research institutions and 25 countries. The resulting database ‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’ includes 3,030 individual modelling records from 126 counties encompassing all continents (except Antarctica). Out of 8,471 articles identified as potentially relevant, we reviewed 1,697 articles and transferred relevant information from each into the database. For each record reported in the GASEMT database, 42 attributes were evaluated. The GASEMT database provides insights into the state-of-the-art of soil- erosion models and model applications worldwide. The database is also intended to support the upcoming country-based United Nations global soil-erosion assessment. This database may help inform soil erosion research priorities in that it builds a foundation for future targeted in-depth analyses. GASEMT is an open-source database that anyone can use to develop research, rectify errors, and expand.

DOI

https://doi.org/10.31223/X5GS3T

Subjects

Soil Science

Keywords

Erosion rates; modelling; GIS; land sustainability; land degradation; policy support.

Dates

Published: 2020-12-22 11:11

Last Updated: 2020-12-22 19:11

License

CC BY Attribution 4.0 International