Soil erosion modelling: A global review and statistical analysis

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 published between 1994 and 2017.We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which 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 combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named ‘Global Applications of Soil ErosionModelling Tracker (GASEMT)’, includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosionmodels and model applicationsworldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, andmake future expansions.

BORRELLI Pasquale;  ALEWELL Christine;  ALVAREZ Pablo;  AYACH ANACHE Jamil Alexandre;  BAARTMAN Jantiene;  BALLABIO Cristiano;  BEZAK Nejc;  BIDDOCCU Marcella;  CERDA Artemi;  CHALISE Devraj;  CHEN Songchao;  CHEN Walter;  DE GIROLAMO Anna Maria;  DESTA GESSESSE Gizaw;  DEUMLICH Detlef;  DIODATO Nazareno;  EFTHIMIOU Nikolaos;  ERPUL Gunay;  FIENER Peter;  FREPPAZ Michele;  GENTILE Francesco;  GERICKE Andreas;  HAREGEWEYN Nigussie;  HU Bifeng;  JEANNEAU Amelie;  KAFFAS Konstantinos;  KIANI-HARCHEGANI Mahboobeh;  LIZAGA Ivan;  LI Changjia;  LOMBARDO Luigi;  LÓPEZ-VICENTE Manuel;  LUCAS-BORJA Manuel Esteban;  MÄRKER Michael;  MATTHEWS Francis;  MIAO Chiyuan;  MIKOŠ Matjaž;  MODUGNO Sirio;  MÖLLER Markus;  NAIPAL Victoria;  NEARING Mark;  OWUSU Stephen;  PANDAY Dinesh;  PATAULT Edouard;  PATRICHE Cristian;  POGGIO Laura;  PORTES Raquel;  QUIJANO Laura;  RAHDARI Mohammad Reza;  RENIMA Mohammed;  RICCI Giovanni Francesco;  RODRIGO-COMINO Jesús;  SAIA Sergio;  SAMANI Aliakbar Nazari;  SCHILLACI Calogero;  SYRRIS Vasileios;  KIM Hyuck Soo;  SPINOLA Diogo Noses;  OLIVEIRA Paulo Tarso;  TENG Hongfen;  THAPA Resham;  VANTAS Konstantinos;  VIEIRA Diana;  YANG J.;  YIN Shuiqing;  ZEMA Demetrio Antonio;  ZHAO Guangju;  PANAGOS Panagiotis; 

2021-03-29

ELSEVIER

JRC120100

0048-9697 (online),   

https://www.sciencedirect.com/science/article/pii/S004896972101562X,    https://publications.jrc.ec.europa.eu/repository/handle/JRC120100,   

10.1016/j.scitotenv.2021.146494 (online),