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Changes in future soil erosion rates are driven by climatic conditions, land use patterns, socio-economic development, farmers’ choices, and importantly modified by agro-environmental policies. This study simulates the impact of expected climatic and land use change projections on future rates of soil erosion by water (sheet and rill processes) in 2050 within the agricultural areas of the European Union and the UK, compared to a current representative baseline (2016). We used the Revised Universal Soil Loss Equation (RUSLE) adjusted at continental scale with projections of future rainfall erosivity and land use change. Future rainfall erosivity is predicted using an average composite of 19 Global Climate Models (GCMs) from the Coupled Model Inter-comparison Projects (CMIP5) WorldClim dataset across three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Concerning future land use change and crop dynamics, we used the projections provided by the Common Agricultural Policy Regional Impact Analysis (CAPRI) model. Depending on the RCP scenario, we estimate a +13 %-22.5 % increase in the mean soil erosion rate in the EU and UK, rising from an estimated 3.07 t ha−1 yr−1 (2016) to between 3.46 t ha−1 yr−1 (RCP2.6 scenario) and 3.76 t ha−1 yr−1 (RCP8.5 scenario). Here, we disentangle the impact of land use change and climate change in relation to future soil losses. Projected land use change in the EU and UK indicates an overall increase of pasture coverage in place of croplands. This land use change is estimated to reduce soil erosion rates (-3%). In contrast, the increases in future rainfall erosivity (+15.7 %–25.5 %) will force important increases of soil erosion requiring further targeted intervention measures. Given that agro-environmental policies will be the most effective mechanisms to offset this future increase in soil erosion rates, this study proposes soil conservation instruments foreseen in the EU Common Agricultural Policy (CAP) to run policy scenarios. A targeted application of cover crops in soil erosion hotspots combined with limited soil disturbance measures can partially or completely mitigate the effect of climate change on soil losses. Effective mitigation of future soil losses requires policy measures for soil conservation on at least 50 % of agricultural land with erosion rates above 5 t ha−1 yr−1.
Panos Panagos; Cristiano Ballabio; Mihaly Himics; Simone Scarpa; Francis Matthews; Mariia Bogonos; Jean Poesen; Pasquale Borrelli. Projections of soil loss by water erosion in Europe by 2050. Environmental Science & Policy 2021, 124, 380 -392.
AMA StylePanos Panagos, Cristiano Ballabio, Mihaly Himics, Simone Scarpa, Francis Matthews, Mariia Bogonos, Jean Poesen, Pasquale Borrelli. Projections of soil loss by water erosion in Europe by 2050. Environmental Science & Policy. 2021; 124 ():380-392.
Chicago/Turabian StylePanos Panagos; Cristiano Ballabio; Mihaly Himics; Simone Scarpa; Francis Matthews; Mariia Bogonos; Jean Poesen; Pasquale Borrelli. 2021. "Projections of soil loss by water erosion in Europe by 2050." Environmental Science & Policy 124, no. : 380-392.
Mercury (Hg) is one of the most dangerous pollutants worldwide. In the European Union (EU), we recently estimated the Hg distribution in topsoil using 21,591 samples and a series of geo-physical inputs. In this manuscript, we investigate the impact of mining activities, chrol-alkali industries and other diffuse pollution sources as primary anthropogenic sources of Hg hotspots in the EU. Based on Hg measured soil samples, we modelled the Hg pool in EU topsoils, which totals about 44.8 Gg, with an average density of 103 g ha−1. As a following step, we coupled the estimated Hg stocks in topsoil with the pan-European assessment of soil loss due to water erosion and sediment distribution. In the European Union and UK, we estimated that about 43 Mg Hg yr−1 are displaced by water erosion and c. a. 6 Mg Hg yr−1 are transferred with sediments to river basins and eventually released to coastal Oceans. The Mediterranean Sea receives almost half (2.94 Mg yr−1) of the Hg fluxes to coastal oceans and it records the highest quantity of Hg sediments. This is the result of elevated soil Hg concentration and high erosion rates in the catchments draining into the Mediterranean Sea. This work contributes to new knowledge in support of the policy development in the EU on the Zero Pollution Action Plan and the Sustainable Development Goal (SDGs) 3.9 and 14.1, which both have as an objective to reduce soil pollution by 2030.
Panos Panagos; Martin Jiskra; Pasquale Borrelli; Leonidas Liakos; Cristiano Ballabio. Mercury in European topsoils: Anthropogenic sources, stocks and fluxes. Environmental Research 2021, 201, 111556 .
AMA StylePanos Panagos, Martin Jiskra, Pasquale Borrelli, Leonidas Liakos, Cristiano Ballabio. Mercury in European topsoils: Anthropogenic sources, stocks and fluxes. Environmental Research. 2021; 201 ():111556.
Chicago/Turabian StylePanos Panagos; Martin Jiskra; Pasquale Borrelli; Leonidas Liakos; Cristiano Ballabio. 2021. "Mercury in European topsoils: Anthropogenic sources, stocks and fluxes." Environmental Research 201, no. : 111556.
Luca Montanarella; Panos Panagos. Soil Security for the European Union. Soil Security 2021, 4, 100009 .
AMA StyleLuca Montanarella, Panos Panagos. Soil Security for the European Union. Soil Security. 2021; 4 ():100009.
Chicago/Turabian StyleLuca Montanarella; Panos Panagos. 2021. "Soil Security for the European Union." Soil Security 4, no. : 100009.
Soil carbon sequestration is seen as an effective means to draw down atmospheric CO2, but at the same time warming may accelerate the loss of extant soil carbon, so an accurate estimation of soil carbon stocks and their vulnerability to climate change is required. Here we demonstrate how separating soil carbon into particulate and mineral-associated organic matter (POM and MAOM, respectively) aids in the understanding of its vulnerability to climate change and identification of carbon sequestration strategies. By coupling European-wide databases with soil organic matter physical fractionation, we assessed the current geographical distribution of mineral topsoil carbon in POM and MAOM by land cover using a machine-learning approach. Further, using observed climate relationships, we projected the vulnerability of carbon in POM and MAOM to future climate change. Arable and coniferous forest soils contain the largest and most vulnerable carbon stocks when cumulated at the European scale. Although we show a lower carbon loss from mineral topsoils with climate change (2.5 ± 1.2 PgC by 2080) than those in some previous predictions, we urge the implementation of coniferous forest management practices that increase plant inputs to soils to offset POM losses, and the adoption of best management practices to avert the loss of and to build up both POM and MAOM in arable soils. Particulate and mineral-associated soil organic carbon have different climate sensitivity and distributions in Europe, according to analyses of measurements of soil carbon fractions from 352 topsoils.
Emanuele Lugato; Jocelyn M. Lavallee; Michelle L. Haddix; Panos Panagos; M. Francesca Cotrufo. Different climate sensitivity of particulate and mineral-associated soil organic matter. Nature Geoscience 2021, 14, 295 -300.
AMA StyleEmanuele Lugato, Jocelyn M. Lavallee, Michelle L. Haddix, Panos Panagos, M. Francesca Cotrufo. Different climate sensitivity of particulate and mineral-associated soil organic matter. Nature Geoscience. 2021; 14 (5):295-300.
Chicago/Turabian StyleEmanuele Lugato; Jocelyn M. Lavallee; Michelle L. Haddix; Panos Panagos; M. Francesca Cotrufo. 2021. "Different climate sensitivity of particulate and mineral-associated soil organic matter." Nature Geoscience 14, no. 5: 295-300.
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.
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. Soil erosion modelling: A bibliometric analysis. Environmental Research 2021, 197, 111087 .
AMA StyleNejc 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. Soil erosion modelling: A bibliometric analysis. Environmental Research. 2021; 197 ():111087.
Chicago/Turabian StyleNejc 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. 2021. "Soil erosion modelling: A bibliometric analysis." Environmental Research 197, no. : 111087.
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 Erosion Modelling 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- erosion models and model applications worldwide. 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, and make future expansions.
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; Francis Matthews; 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. Soil erosion modelling: A global review and statistical analysis. Science of The Total Environment 2021, 780, 146494 .
AMA StylePasquale 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, Francis Matthews, 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. Soil erosion modelling: A global review and statistical analysis. Science of The Total Environment. 2021; 780 ():146494.
Chicago/Turabian StylePasquale 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; Francis Matthews; 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. 2021. "Soil erosion modelling: A global review and statistical analysis." Science of The Total Environment 780, no. : 146494.
The characteristics (magnitude and timing) of individual rainfall erosivity (RE) events in Europe strongly control soil loss at timescales from the individual event to long term annual average. While annual averages of soil erosion encompass the long-term variability of the event-based drivers of soil erosion (soil condition, water kinetic energy, vegetation properties), they provide both little direct information on the timing of soil loss or capacity to fully understand future erosion. Across the spectrum of empirical to physically based process models, event-scale estimates of rainfall energy are vital. The (R)USLE EI30 index is a popular description of the combined effect of rainfall kinetic energy and the maximum 30-minute intensity of a rainfall event on soil loss. Modelling RE from daily or event rainfall accumulation seeks to capture the intra-annual meteorological controls on the EI30 index, with the goal of utilising rainfall data with higher abundance (eg daily) than conventional but less common hyetograph data. To date, no systematic study has provided model parameter surfaces for Europe’s climatic regions and investigated their spatial configuration. For each of 74 relevant environmental strata (EnS) within 13 broader environmental zones, we calibrate and validate 5 power-law based models with monthly and annual parameter sets using the REDES dataset, composed of over 300,000 RE events from national gauge networks.
We demonstrate the applicability of delineated environmental strata for subsampling and modelling event rainfall erosivity with heterogeneous national gauge data coverage and extent. Power-law model fits with 12 individual monthly parameter sets outperformed annual models with periodic cosine functions. The power-law α and β parameters are generally correlated through space (r = 0.66) and follow the general European trend of long-term annual average RE, increasing from North-West to South-East. The average annual Nash-Sutcliffe model efficiency for all strata increased from 0.427 (max: 0.76, min: 0.21) to 0.437 when the top 1 percentile of events were removed, which contribute between 8 and 27% of the total RE per stratum. The prediction capacity was higher in autumn and winter than in spring and summer when rainfall holds generally higher unit kinetic energy. Average model efficiency per environmental zone depended on both the rainfall stochasticity and size of the national data sample within each stratum, highlighting the importance of ample data extents for predicting event rainfall erosivity in Europe.
Francis Matthews; Panos Panagos; Gert Verstraeten. Modelling event scale rainfall erosivity across European climate regions . 2021, 1 .
AMA StyleFrancis Matthews, Panos Panagos, Gert Verstraeten. Modelling event scale rainfall erosivity across European climate regions . . 2021; ():1.
Chicago/Turabian StyleFrancis Matthews; Panos Panagos; Gert Verstraeten. 2021. "Modelling event scale rainfall erosivity across European climate regions ." , no. : 1.
We use the latest projections of climate and land use change (year 2070) to assess potential global soil erosion rates by water erosion (interrill and rill processes) (Borrelli et al., 2020) using the RUSLE-based semiempirical modeling platform (GloSEM) (Borrelli et al., 2017). With some degree of uncertainty, GloSEM allows prediction of both state and change of soil erosion, identifying hotspots thanks to its high resolution (250 × 250 m) and predicting future variation based on projections of change in land use, soil conservation practices, and climate change.
Three alternative scenarios (2.6, 4.5, and 8.5) are tested using the Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) (LUH2 data) and 14 General Climate Models (GCMs) (WorldClim data), for a total of 42 modelling scenarios.
In the 2015 scenario, we estimate global soil erosion equal to 43 (+9.2/−7) Pg yr−1; with a study area covering ∼95.5% of the Earth’s land surface (in Borrelli et al. 2017 the study area was ~84.1% of the Earth’s land surface). The future scenarios suggest that socioeconomic developments impacting land use will either decrease (SSP1-RCP2.6–10%) or increase (SSP2-RCP4.5 +2%, SSP5-RCP8.5 +10%) water erosion by 2070. By contrast, climate projections, for all global dynamics scenarios, indicate a trend, moving toward a more vigorous hydrological cycle, which could increase global water erosion (+30 to +66%). Quantitatively, 56.1 (+20.6+ /- 16.4) Pg yr−1, 64.8 (+28.5/-21.4) Pg yr−1, and 71.6 (+32.5/-24.7) Pg yr−1 are predicted for the SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios, respectively.
The modeling framework presented in this study adopts standardized data in an adequate format to communicate with adjacent disciplines and moves us toward robust, reproducible, and open data science.
References
Borrelli, P., Robinson, D.A., Fleischer, L.R., Lugato, E., Ballabio, C., Alewell, C., Meusburger, K., Modugno, S., Schütt, B., Ferro, V. and Bagarello, V., 2017. An assessment of the global impact of 21st century land use change on soil erosion. Nature communications, 8(1), pp.1-13.
Borrelli, P., Robinson, D.A., Panagos, P., Lugato, E., Yang, J.E., Alewell, C., Wuepper, D., Montanarella, L. and Ballabio, C., 2020. Land use and climate change impacts on global soil erosion by water (2015-2070). Proceedings of the National Academy of Sciences, 117(36), pp.21994-22001.
Pasquale Borrelli; David A. Robinson; Panos Panagos; Emanuele Lugato; Jae E. Yang; Christine Alewell; David Wuepper; Luca Montanarella; Cristiano Ballabio. Global soil erosion: Storm on the horizon . 2021, 1 .
AMA StylePasquale Borrelli, David A. Robinson, Panos Panagos, Emanuele Lugato, Jae E. Yang, Christine Alewell, David Wuepper, Luca Montanarella, Cristiano Ballabio. Global soil erosion: Storm on the horizon . . 2021; ():1.
Chicago/Turabian StylePasquale Borrelli; David A. Robinson; Panos Panagos; Emanuele Lugato; Jae E. Yang; Christine Alewell; David Wuepper; Luca Montanarella; Cristiano Ballabio. 2021. "Global soil erosion: Storm on the horizon ." , no. : 1.
Mapping of surface soil Hg concentrations, a priority pollutant, at continental scale is important in order to identify hotspots of soil Hg distribution (e.g. mining or industrial pollution) and identify factors that influence soil Hg concentrations (e.g. climate, soil properties, vegetation). Here we present soil Hg concentrations from the LUCAS topsoil (0–20 cm) survey including 21,591 samples from 26 European Union countries (one sample every ~200 km2). Deep Neural Network (DNN) learning models were used to map the European soil Hg distribution. DNN estimated a median Hg concentration of 38.3 μg kg−1 (2.6 to 84.7 μg kg−1) excluding contaminated sites. At continental scale, we found that soil Hg concentrations increased with latitude from south to north and with altitude. A GLMM revealed a correlation (R2 = 0.35) of soil Hg concentrations with vegetation activity, normalized difference vegetation index (NDVI), and soil organic carbon content. This observation corroborates the importance of atmospheric Hg0 uptake by plants and the build-up of the soil Hg pool by litterfall over continental scales. The correlation of Hg concentrations with NDVI was amplified by higher soil organic matter content, known to stabilize Hg in soils through thiol bonds. We find a statistically significant relation between soil Hg levels and coal use in large power plants, proving that emissions from power plants are associated with higher mercury deposition in their proximity. In total 209 hotspots were identified, defined as the top percentile in Hg concentration (>422 μg kg−1). 87 sites (42% of all hotspots) were associated with known mining areas. The sources of the other hotspots could not be identified and may relate to unmined geogenic Hg or industrial pollution. The mapping effort in the framework of LUCAS can serve as a starting point to guide local and regional authorities in identifying Hg contamination hotspots in soils.
Cristiano Ballabio; Martin Jiskra; Stefan Osterwalder; Pasquale Borrelli; Luca Montanarella; Panos Panagos. A spatial assessment of mercury content in the European Union topsoil. Science of The Total Environment 2021, 769, 144755 .
AMA StyleCristiano Ballabio, Martin Jiskra, Stefan Osterwalder, Pasquale Borrelli, Luca Montanarella, Panos Panagos. A spatial assessment of mercury content in the European Union topsoil. Science of The Total Environment. 2021; 769 ():144755.
Chicago/Turabian StyleCristiano Ballabio; Martin Jiskra; Stefan Osterwalder; Pasquale Borrelli; Luca Montanarella; Panos Panagos. 2021. "A spatial assessment of mercury content in the European Union topsoil." Science of The Total Environment 769, no. : 144755.
While agricultural systems are a major pillar in global food security, their productivity is currently threatened by many environmental issues triggered by anthropogenic climate change and human activities, such as land degradation. However, the planetary spatial footprint of land degradation processes on arable lands, which can be considered a major component of global agricultural systems, is still insufficiently well understood. This study analyzes the land degradation footprint on global arable lands, using complex geospatial data on certain major degradation processes, i.e. aridity, soil erosion, vegetation decline, soil salinization and soil organic carbon decline. By applying geostatistical techniques that are representative for identifying the incidence of the five land degradation processes in global arable lands, results showed that aridity is by far the largest singular pressure for these agricultural systems, affecting ~40% of the arable lands' area, which cover approximately 14 million km2 globally. It was found that soil erosion is another major degradation process, the unilateral impact of which affects ~20% of global arable systems. The results also showed that the two degradation processes simultaneously affect an additional ~7% of global arable lands, which makes this synergy the most common form of multiple pressure of land degradative conditions across the world's arable areas. The absolute statistical data showed that India, the United States, China, Brazil, Argentina, Russia and Australia are the most vulnerable countries in the world to the various pathways of arable land degradation. Also, in terms of percentages, statistical observations showed that African countries are the most heavily affected by arable system degradation. This study's findings can be useful for prioritizing agricultural management actions that can mitigate the negative effects of the two degradation processes or of others that currently affect many arable systems across the planet.
Remus Prăvălie; Cristian Patriche; Pasquale Borrelli; Panos Panagos; Bogdan Roșca; Monica Dumitraşcu; Ion-Andrei Nita; Ionuţ Săvulescu; Marius-Victor Birsan; Georgeta Bandoc. Arable lands under the pressure of multiple land degradation processes. A global perspective. Environmental Research 2021, 194, 110697 .
AMA StyleRemus Prăvălie, Cristian Patriche, Pasquale Borrelli, Panos Panagos, Bogdan Roșca, Monica Dumitraşcu, Ion-Andrei Nita, Ionuţ Săvulescu, Marius-Victor Birsan, Georgeta Bandoc. Arable lands under the pressure of multiple land degradation processes. A global perspective. Environmental Research. 2021; 194 ():110697.
Chicago/Turabian StyleRemus Prăvălie; Cristian Patriche; Pasquale Borrelli; Panos Panagos; Bogdan Roșca; Monica Dumitraşcu; Ion-Andrei Nita; Ionuţ Săvulescu; Marius-Victor Birsan; Georgeta Bandoc. 2021. "Arable lands under the pressure of multiple land degradation processes. A global perspective." Environmental Research 194, no. : 110697.
Soil erosion is a major global soil degradation threat to land, freshwater, and oceans. Wind and water are the major drivers, with water erosion over land being the focus of this work; excluding gullying and river bank erosion. Improving knowledge of the probable future rates of soil erosion, accelerated by human activity, is important both for policy makers engaged in land use decision-making and for earth-system modelers seeking to reduce uncertainty on global predictions. Here we predict future rates of erosion by modeling change in potential global soil erosion by water using three alternative (2.6, 4.5, and 8.5) Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. Global predictions rely on a high spatial resolution Revised Universal Soil Loss Equation (RUSLE)-based semiempirical modeling approach (GloSEM). The baseline model (2015) predicts global potential soil erosion rates of 43 − 7 + 9.2 Pg yr−1, with current conservation agriculture (CA) practices estimated to reduce this by ∼5%. Our future scenarios suggest that socioeconomic developments impacting land use will either decrease (SSP1-RCP2.6–10%) or increase (SSP2-RCP4.5 +2%, SSP5-RCP8.5 +10%) water erosion by 2070. Climate projections, for all global dynamics scenarios, indicate a trend, moving toward a more vigorous hydrological cycle, which could increase global water erosion (+30 to +66%). Accepting some degrees of uncertainty, our findings provide insights into how possible future socioeconomic development will affect soil erosion by water using a globally consistent approach. This preliminary evidence seeks to inform efforts such as those of the United Nations to assess global soil erosion and inform decision makers developing national strategies for soil conservation.
Pasquale Borrelli; David A. Robinson; Panos Panagos; Emanuele Lugato; Jae E. Yang; Christine Alewell; David Wuepper; Luca Montanarella; Cristiano Ballabio. Land use and climate change impacts on global soil erosion by water (2015-2070). Proceedings of the National Academy of Sciences 2020, 117, 21994 -22001.
AMA StylePasquale Borrelli, David A. Robinson, Panos Panagos, Emanuele Lugato, Jae E. Yang, Christine Alewell, David Wuepper, Luca Montanarella, Cristiano Ballabio. Land use and climate change impacts on global soil erosion by water (2015-2070). Proceedings of the National Academy of Sciences. 2020; 117 (36):21994-22001.
Chicago/Turabian StylePasquale Borrelli; David A. Robinson; Panos Panagos; Emanuele Lugato; Jae E. Yang; Christine Alewell; David Wuepper; Luca Montanarella; Cristiano Ballabio. 2020. "Land use and climate change impacts on global soil erosion by water (2015-2070)." Proceedings of the National Academy of Sciences 117, no. 36: 21994-22001.
The new European Green Deal has the ambition to make the European Union the first climate-neutral continent by 2050. The European Commission presented an ambitious package of measures within the Biodiversity Strategy 2030, the Farm to Fork and the European Climate Law including actions to protect our soils. The Farm to Fork strategy addresses soil pollution with 50 % reduction in use of chemical pesticides by 2030 and aims 20 % reduction in fertilizer use plus a decrease of nutrient losses by at least 50%. The Biodiversity Strategy has the ambition to set a minimum of 30 % of the EU’s land area as protected areas, limit urban sprawl, reduce the pesticides risk, bring back at least 10 % of agricultural area under high-diversity landscape features, put forward the 25 % of the EU’s agricultural land as organically farmed, progress in the remediation of contaminated sites, reduce land degradation and plant more than three billion new trees. The maintenance of wetlands and the enhancement of soil organic carbon are also addressed in the European Climate Law. The new EU Soil Observatory will be collecting policy relevant data and developing indicators for the regular assessment and progress towards the ambitious targets of the Green Deal.
Luca Montanarella; Panos Panagos. The relevance of sustainable soil management within the European Green Deal. Land Use Policy 2020, 100, 104950 .
AMA StyleLuca Montanarella, Panos Panagos. The relevance of sustainable soil management within the European Green Deal. Land Use Policy. 2020; 100 ():104950.
Chicago/Turabian StyleLuca Montanarella; Panos Panagos. 2020. "The relevance of sustainable soil management within the European Green Deal." Land Use Policy 100, no. : 104950.
Soil erosion is one of the eight threats in the Soil Thematic Strategy, the main policy instrument dedicated to soil protection in the European Union (EU). During the last decade, soil erosion indicators have been included in monitoring the performance of the Common Agricultural Policy (CAP) and the progress towards the Sustainable Development Goals (SDGs). This study comes five years after the assessment of soil loss by water erosion in the EU [Environmental science & policy 54, 438–447 (2015)], where a soil erosion modelling baseline for 2010 was developed. Here, we present an update of the EU assessment of soil loss by water erosion for the year 2016. The estimated long-term average erosion rate decreased by 0.4% between 2010 and 2016. This small decrease of soil loss was due to a limited increase of applied soil conservation practices and land cover change observed at the EU level. The modelling results suggest that, currently, ca. 25% of the EU land has erosion rates higher than the recommended sustainable threshold (2 t ha−1 yr−1) and more than 6% of agricultural lands suffer from severe erosion (11 t ha−1 yr−1). The results suggest that a more incisive set of measures of soil conservation is needed to mitigate soil erosion across the EU. However, targeted measures are recommendable at regional and national level as soil erosion trends are diverse between countries which show heterogeneous application of conservation practices.
Panos Panagos; Cristiano Ballabio; Jean Poesen; Emanuele Lugato; Simone Scarpa; Luca Montanarella; Pasquale Borrelli. A Soil Erosion Indicator for Supporting Agricultural, Environmental and Climate Policies in the European Union. Remote Sensing 2020, 12, 1365 .
AMA StylePanos Panagos, Cristiano Ballabio, Jean Poesen, Emanuele Lugato, Simone Scarpa, Luca Montanarella, Pasquale Borrelli. A Soil Erosion Indicator for Supporting Agricultural, Environmental and Climate Policies in the European Union. Remote Sensing. 2020; 12 (9):1365.
Chicago/Turabian StylePanos Panagos; Cristiano Ballabio; Jean Poesen; Emanuele Lugato; Simone Scarpa; Luca Montanarella; Pasquale Borrelli. 2020. "A Soil Erosion Indicator for Supporting Agricultural, Environmental and Climate Policies in the European Union." Remote Sensing 12, no. 9: 1365.
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Paulo Pereira; Damià Barceló; Panos Panagos. Soil and water threats in a changing environment. Environmental Research 2020, 186, 109501 .
AMA StylePaulo Pereira, Damià Barceló, Panos Panagos. Soil and water threats in a changing environment. Environmental Research. 2020; 186 ():109501.
Chicago/Turabian StylePaulo Pereira; Damià Barceló; Panos Panagos. 2020. "Soil and water threats in a changing environment." Environmental Research 186, no. : 109501.
Phosphorus (P) as a key element in DNA, RNA as well as ATP and phospholipids is essential for the growth, functioning and reproduction of all life on earth. However, if fertilization with animal wastes or human excreta is not available or not organized, P fertilizers stem from nonrenewable geological P deposits, which are an increasingly limited resource. The potential threats of a global P limitation due to “peak phosphorus” have been discussed intensively in the recent past including the socio economic as well as political consequences which will be dramatic. While a deficit in available soil P leads to a loss of agricultural yield, an excess of total P in soils triggers aquatic eutrophication, loss in biodiversity and wildlife habitat in surrounding water bodies in other regions of the world.
We calculated global soil P balances considering input from atmosphere and plant management (as sum of manure and residue input minus plant uptake) versus depletion due to soil erosion in coupling P fluxes from (Ringeval et al., 2017) with soil erosion rates from (Borrelli et al., 2017).
The world’s soils are currently being depleted in P in spite of high chemical fertilizer input. Considering the current high chemical fertilizer inputs most continents result in slightly positive P balances (e.g. net P input to soils). Exception are Africa with very low chemical fertilizer input of 1.7 kg ha-1yr-1 paired with high losses due to soil erosion of 2 kg ha-1yr-1 and Europe (the latter is the average for the geographic Europe including eastern European countries with very low chemical fertilizer input). Results indicate negative balances globally as well as for all continents (depletion between 4 and 19 kg P ha-1yr-1 ) if input of chemical fertilizers is neglected.
Parallel to the distribution pattern and dynamics of global soil erosion by water (Borrelli et al., 2017), P losses from soils due to water erosion are most dramatic in countries and regions with intensive agriculture and/or extreme climates (e.g., high frequencies of heavy rain storm or droughts followed by significant rain events).
References
Borrelli, P., Robinson, D.A., Fleischer, L.R., Lugato, E., Ballabio, C., Alewell, C., Meusburger, K., Modugno, S., Schütt, B., Ferro, V., Bagarello, V., Oost, K.V., Montanarella, L. and Panagos, P., 2017. An assessment of the global impact of 21st century land use change on soil erosion. Nature Communications, 8(1): 2013.
Ringeval, B., Augusto, L., Monod, H., van Apeldoorn, D., Bouwman, L., Yang, X., Achat, D.L., Chini, L.P., Van Oost, K., Guenet, B., Wang, R., Decharme, B., Nesme, T. and Pellerin, S., 2017. Phosphorus in agricultural soils: drivers of its distribution at the global scale. Global Change Biology
Christine Alewell; Pasquale Borrelli; Bruno Ringeval; Cristiano Ballabio; David A. Robinson; Panos Panagos. Obvious but overlooked: soil erosion neglect in the global phosphorus cycle. 2020, 1 .
AMA StyleChristine Alewell, Pasquale Borrelli, Bruno Ringeval, Cristiano Ballabio, David A. Robinson, Panos Panagos. Obvious but overlooked: soil erosion neglect in the global phosphorus cycle. . 2020; ():1.
Chicago/Turabian StyleChristine Alewell; Pasquale Borrelli; Bruno Ringeval; Cristiano Ballabio; David A. Robinson; Panos Panagos. 2020. "Obvious but overlooked: soil erosion neglect in the global phosphorus cycle." , no. : 1.
Over the last two decades, geospatial technologies such as Geographic Information System and spatial interpolation methods have facilitated the development of increasingly accurate spatially explicit assessments of soil erosion. Despite these advances, current modelling approaches in Europe rest on (i) an insufficient definition of the proportion of arable land that is exploited for crop production, (ii) a neglect of the intra‐annual variability of soil cover conditions in arable land, and (iii) offer little understanding of the spatio-temporal trends of soil erosion. Here, we represent the recent developments of two methods tested to overcome current limitations and move towards the implementation of new modelling approaches in Europe.
The Object-oriented Soil Erosion Modelling and Monitoring v2.0 (O-SEMM) (Land degradation & development, 29, 1270-1281, 2018) combines highly accurate agricultural parcel information systems (LPIS) with crop statistics, Landsat 8 and Sentinel 2 satellite data and high temporal resolution rainfall data to assess soil erosion events at parcel level.
The Daily Erosion Project (DEP) (Earth Surface Processes and Landforms, 43, 1105-1117, 2018), developed by the Iowa State University, estimates soil erosion and water runoff occurring on hill slopes using the WEPP erosion prediction model.
References
Borrelli, P., Meusburger, K., Ballabio, C., Panagos, P., & Alewell, C. (2018). Object‐oriented soil erosion modelling: A possible paradigm shift from potential to actual risk assessments in agricultural environments. Land degradation & development, 29(4), 1270-1281.
Gelder, B., Sklenar, T., James, D., Herzmann, D., Cruse, R., Gesch, K., & Laflen, J. (2018). The Daily Erosion Project–daily estimates of water runoff, soil detachment, and erosion. Earth Surface Processes and Landforms, 43(5), 1105-1117.
Pasquale Borrelli; Richard Cruse; Brian Gelder; Panos Panagos. Object‐oriented Soil Erosion Modelling and Daily Erosion Project: Laying the foundation for a new generation of soil erosion assessments in Europe. 2020, 1 .
AMA StylePasquale Borrelli, Richard Cruse, Brian Gelder, Panos Panagos. Object‐oriented Soil Erosion Modelling and Daily Erosion Project: Laying the foundation for a new generation of soil erosion assessments in Europe. . 2020; ():1.
Chicago/Turabian StylePasquale Borrelli; Richard Cruse; Brian Gelder; Panos Panagos. 2020. "Object‐oriented Soil Erosion Modelling and Daily Erosion Project: Laying the foundation for a new generation of soil erosion assessments in Europe." , no. : 1.
Gully erosion may cause considerable soil losses and produce large volumes of sediment. The aim of this study was to perform a preliminary assessment on the presence of ephemeral gullies in Greece by sampling representative cultivated fields in 100 sites randomly distributed throughout the country. The almost 30-ha sampling surfaces were examined with visual interpretation of multi-temporal imagery from the online Google Earth for the period 2002–2019. In parallel, rill and sheet erosion signs, land uses, and presence of terraces and other anti-erosion features, were recorded within every sample. One hundred fifty-three ephemeral gullies were identified in total, inside 22 examined agricultural surfaces. The mean length of the gullies was 55.6 m, with an average slope degree of 9.7%. Vineyards showed the largest proportion of gullies followed by olive groves and arable land, while pastures exhibited limited presence of gullies. Spatial clusters of high gully severity were observed in the north and east of the country. In 77% of the surfaces with gullies, there were no terraces, although most of these surfaces were situated in slopes higher than 8%. It was the first time to use visual interpretation with Google Earth image time-series on a country scale producing a gully erosion inventory. Soil conservation practices such as contour farming and terraces could mitigate the risk of gully erosion in agricultural areas.
Christos Karydas; Panos Panagos. Towards an Assessment of the Ephemeral Gully Erosion Potential in Greece Using Google Earth. Water 2020, 12, 603 .
AMA StyleChristos Karydas, Panos Panagos. Towards an Assessment of the Ephemeral Gully Erosion Potential in Greece Using Google Earth. Water. 2020; 12 (2):603.
Chicago/Turabian StyleChristos Karydas; Panos Panagos. 2020. "Towards an Assessment of the Ephemeral Gully Erosion Potential in Greece Using Google Earth." Water 12, no. 2: 603.
The occurrence of hydrological extremes in the Amazon region and the associated sediment loss during rainfall events are key features in the global climate system. Climate extremes alter the sediment and carbon balance but the ecological consequences of such changes are poorly understood in this region. With the aim of examining the interactions between precipitation and landscape-scale controls of sediment export from the Amazon basin, we developed a parsimonious hydro-climatological model on a multi-year series (1997–2014) of sediment discharge data taken at the outlet of Óbidos (Brazil) watershed (the narrowest and swiftest part of the Amazon River). The calibrated model (correlation coefficient equal to 0.84) captured the sediment load variability of an independent dataset from a different watershed (the Magdalena River basin), and performed better than three alternative approaches. Our model captured the interdecadal variability and the long-term patterns of sediment export. In our reconstruction of yearly sediment discharge over 1859–2014, we observed that landscape erosion changes are mostly induced by single storm events, and result from coupled effects of droughts and storms over long time scales. By quantifying temporal variations in the sediment produced by weathering, this analysis enables a new understanding of the linkage between climate forcing and river response, which drives sediment dynamics in the Amazon basin.
Nazzareno Diodato; Naziano Filizola; Pasquale Borrelli; Panos Panagos; Gianni Bellocchi. The Rise of Climate-Driven Sediment Discharge in the Amazonian River Basin. Atmosphere 2020, 11, 208 .
AMA StyleNazzareno Diodato, Naziano Filizola, Pasquale Borrelli, Panos Panagos, Gianni Bellocchi. The Rise of Climate-Driven Sediment Discharge in the Amazonian River Basin. Atmosphere. 2020; 11 (2):208.
Chicago/Turabian StyleNazzareno Diodato; Naziano Filizola; Pasquale Borrelli; Panos Panagos; Gianni Bellocchi. 2020. "The Rise of Climate-Driven Sediment Discharge in the Amazonian River Basin." Atmosphere 11, no. 2: 208.
Land degradation by water and wind erosion is a serious problem worldwide. Despite the significant amount of research on this topic, quantifying these processes at large- or regional-scale remains difficult. Furthermore, very few studies provide integrated assessments of land susceptibility to both water and wind erosion. Therefore, this study investigated the spatial patterns of water and wind erosion risks, first separately and then combined, in the drought-prone region of East Africa using the best available datasets. As to water erosion, we adopted the spatially distributed version of the Revised Universal Soil Loss Equation and compared our estimates with plot-scale measurements and watershed sediment yield (SY) data. The order of magnitude of our soil loss estimates by water erosion is within the range of measured plot-scale data. Moreover, despite the fact that SY integrates different soil erosion and sediment deposition processes within watersheds, we observed a strong correlation of SY with our estimated soil loss rates (r2 = 0.4). For wind erosion, we developed a wind erosion index by integrating five relevant factors using fuzzy logic technique. We compared this index with estimates of the frequency of dust storms, derived from long-term Sea-Viewing Wide Field-of-View Sensor Level-3 daily data. This comparison revealed an overall accuracy of 70%. According to our estimates, mean annual gross soil loss by water erosion amounts to 4 billion t, with a mean soil loss rate of 6.3 t ha-1 yr-1, of which ca. 50% was found to originate in Ethiopia. In terms of land cover, ca. 50% of the soil loss by water erosion originates from cropland (with a mean soil loss rate of 18.4 t ha-1 yr-1), which covers ca. 15% of the total area in the study region. Model results showed that nearly 10% of the East Africa region is subject to moderate or elevated water erosion risks (>10 t ha-1 yr-1). With respect to wind erosion, we estimated that around 25% of the study area is experiencing moderate or elevated wind erosion risks (equivalent to a frequency of dust storms >45 days yr-1), of which Sudan and Somalia (which are dominated by bare/sparse vegetation cover) have the largest share (ca. 90%). In total, an estimated 8 million ha is exposed to moderate or elevated risks of soil erosion by both water and wind. The results of this study provide new insights on the spatial patterns of water and wind erosion risks in East Africa and can be used to prioritize areas where further investigations are needed and where remedial actions should be implemented.
Ayele A. Fenta; Atsushi Tsunekawa; Nigussie Haregeweyn; Jean Poesen; Mitsuru Tsubo; Pasquale Borrelli; Panos Panagos; Matthias Vanmaercke; Jente Broeckx; Hiroshi Yasuda; Takayuki Kawai; Yasunori Kurosaki. Land susceptibility to water and wind erosion risks in the East Africa region. Science of The Total Environment 2020, 703, 135016 .
AMA StyleAyele A. Fenta, Atsushi Tsunekawa, Nigussie Haregeweyn, Jean Poesen, Mitsuru Tsubo, Pasquale Borrelli, Panos Panagos, Matthias Vanmaercke, Jente Broeckx, Hiroshi Yasuda, Takayuki Kawai, Yasunori Kurosaki. Land susceptibility to water and wind erosion risks in the East Africa region. Science of The Total Environment. 2020; 703 ():135016.
Chicago/Turabian StyleAyele A. Fenta; Atsushi Tsunekawa; Nigussie Haregeweyn; Jean Poesen; Mitsuru Tsubo; Pasquale Borrelli; Panos Panagos; Matthias Vanmaercke; Jente Broeckx; Hiroshi Yasuda; Takayuki Kawai; Yasunori Kurosaki. 2020. "Land susceptibility to water and wind erosion risks in the East Africa region." Science of The Total Environment 703, no. : 135016.
This study presents the updated version of the recently published LANDUM model [Land Use Policy 48, 38–50 (2015)]. LANDUM is integrated into the 100 m resolution RUSLE-based pan-European soil erosion risk modelling platform of the European Commission. It estimates the effects of local land use and management practices on the magnitude of soil erosion across each NUTS2 region of the European Union. This is done based on a spatially explicit estimation of the so-called cover-management factor of (R)USLE family models which is also known as C-factor. In this updated version, the data on soil conservation measures (i.e., reduced tillage, cover crops and plant residues) reported in the latest EU Farm Structure Survey (2016) were integrated and elaborated in LANDUM in order to estimate the changes of the C-factor in Europe between 2010 and 2016. For 2016, a C-factor of 0.2316 for the arable land of the 28 Member States of the European Union was estimated. This implies an overall decrease of C-factor of ca. -0.84 % compared to the 2010 survey. The change in C-factor from 2010 to 2016 could be an indication for the effectiveness of Common Agricultural Policy (CAP) soil conservation measures in reducing soil erosion in Europe, especially key CAP policies such as Good Agricultural and Environmental Conditions and Greening.
Pasquale Borrelli; Panos Panagos. An indicator to reflect the mitigating effect of Common Agricultural Policy on soil erosion. Land Use Policy 2020, 92, 104467 .
AMA StylePasquale Borrelli, Panos Panagos. An indicator to reflect the mitigating effect of Common Agricultural Policy on soil erosion. Land Use Policy. 2020; 92 ():104467.
Chicago/Turabian StylePasquale Borrelli; Panos Panagos. 2020. "An indicator to reflect the mitigating effect of Common Agricultural Policy on soil erosion." Land Use Policy 92, no. : 104467.