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Soil erosion modelling: The new challenges as the result of policy developments in Europe
Environmental Research 172 (2019) 470–474
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Soil erosion modelling: The new challenges as the result of policy developments in Europe
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ABSTRACT
Keywords: Policy support Science policy interface Sediments Erosivity Wind erosion Wildfires Land degradation
New challenges and policy developments after 2015 (among others, the Common Agricultural Policy (CAP), Sustainable Development Goals (SDGs)) are opportunities for soil scientists and soil erosion modellers to respond with more accurate assessments and solutions as to how to reduce soil erosion and furthermore, how to reach Zero Net Land Degradation targets by 2030. This special issue includes papers concerning the use of fallout for estimating soil erosion, new wind erosion modelling techniques, the importance of extreme events (forest fires, intense rainfall) in accelerating soil erosion, management practices to reduce soil erosion in vineyards, the impact of wildfires in erosion, updated methods for estimating soil erodibility, comparisons between sediment distribution models, the application of the WaTEM/SEDEM model in Europe, a review of the G2 model and a proposal for a land degradation modelling approach. New data produced from field surveys such as LUCAS topsoil and the increasing availability of remote sensing data may facilitate the work of erosion modellers. Finally, better integration with other soil related disciplines (soil carbon, biodiversity, compaction and contamination) and Earth Systems modelling is the way forward for a new generation of erosion process models.
1. Background With the exponential increase of the world population from 1 billion in 1820 to 7 billion in 2012 and projections for 10 billion in 2056, a substantial increase in the demand for food, energy and natural resources (water, air, soil) is expected (Ferreira et al., 2018). Land degradation through human activities is negatively impacting the wellbeing of at least 3.2 billion people and is pushing the planet towards mass extinction affecting a sixth of all species (Scholes et al., 2018). Human activity (deforestation, overgrazing, tillage and unsuitable agricultural practices) and related land use changes are the main reasons for accelerated soil erosion, which has substantial implications for the nutrient and carbon cycle, land productivity and in turn, worldwide socio-economic conditions (Borrelli et al., 2018). According to the Thematic Strategy for the Soil Protection in European Union (EU) (European Commission – Soil Thematic Strategy, 2006), soil erosion by water is the most severe hazard for soils in Europe. It reduces soil productivity and leads to desertification in vulnerable areas (Kirkby et al., 2008). A major policy response is required to reverse the impacts of soil erosion in degraded areas, particularly in light of current climate change and the future water crisis (Panagos et al., 2016). The publication of the new assessment of soil loss by water erosion in Europe (Panagos et al., 2015c) has triggered a scientific discussion of the modelling results and how these can be improved and better used in the policy cycle. The resulting soil erosion maps are used to identify areas where detailed studies are needed and where remedial actions should be implemented. In addition, this modelling development allows for relative spatial and temporal comparisons, a scenario analysis and integration of the erosion model with the carbon cycle. The main objective of this editorial article is to present the recent
policy developments in the Common Agricultural Policy (CAP) and the Sustainable Development Goals (SDGs) and how they can influence the soil erosion modelling. 2. Policy developments and challenges for soil erosion modelling The recent pan-European soil loss by water erosion assessment allows for the development of indicators, maps and reports in support of EU policies such as the Common Agricultural Policy (CAP), the Sustainable Development Goals (SDGs) and the Soil Thematic Strategy (Fig. 1). The UN Sustainable Development Goals (SDGs) explicitly identify soil resources as being of crucial importance for sustainable development and promote the protection of soil resources in order to achieve the ambitious goal of zero land degradation by 2030 (Keesstra et al., 2016). The EU is a front-runner in SDGs and established detailed regular monitoring of SDGs in an EU context by releasing 100 indicators (European Commission, 2018). Soil erosion by water is contributing in monitoring both the SDG2 (zero hanger) and the SDG15 (Life on land). According to the monitoring report on progress towards SDGs in the EU context (European Commission, 2018), more than 201 * 103 Km2 are estimated to be at risk of severe erosion (> 10 t ha−1 yr−1). Even if soil erosion is a major threat for sustainable and productive agricultural systems (in particular for the 140 *103 Km2 with severe erosion), there are signs of improvement across the EU due to mandatory cross-compliance measures in the EU Common Agricultural Policy (CAP), the trends in croplands area decline and the raising of awareness among farmers. The Directorate General Agriculture and Rural development (DG AGRI) of the European Commission is responsible for the implementation of the current EU Common Agricultural Policy (CAP
https://doi.org/10.1016/j.envres.2019.02.043
Available online 28 February 2019 0013-9351/ © 2019 Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).
Environmental Research 172 (2019) 470–474
Fig. 1. Soil erosion indicators and policy support.
2014–2020) and for the proposal of the future CAP (2021–2017). The sustainable development and efficient management of natural resources (water, soil and air) is one of the 9 key objectives of the future CAP. In addition, the reduction of soil erosion by water is one of the indicators proposed by the European Commission legislative proposal (European Commission, CAP 2021-2027, 2018) in order to monitor the environmental and climatic benefits of the future CAP (Fig. 1). The Roadmap to a Resource-Efficient Europe (European Commission, 2011) sets out a milestone to reduce soil erosion and requires Member States to implement the actions needed to decrease erosion rates. In addition to the agricultural and environmental policies of EU, the current pan-European assessment on soil loss by water erosion is used for various policy reports such as the regional statistics, the EU Agricultural Outlook, and the European Parliament technical reports (Fig. 1). At a global scale, the soil erosion assessment is included in the United Nations Environment Programme (UNEP) report on the sustainable potential of land resources (Herrick et al., 2016) and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) for Europe and Central Asia (Rounsevell et al., 2018). This list of policy organisations and initiatives is not exhaustive as the pan-European soil erosion assessment provides data and indicators to the Food Agricultural Organisation (FAO) and the Organisation for Economic Co-operation and Development (OECD). Recently, FAO has published the Voluntary Guidelines for Sustainable Soil Management (FAO, 2017) with recommendations as to how to minimise risk concerning soil erosion.
Commission, Ispra (Italy) in March 2017. In this workshop, 120 soil scientists and modellers from 28 countries debated future directions for soil erosion modelling. Among others, it was noticed that there are other erosional processes such as gully erosion, tillage erosion, wind erosion, piping erosion, snow induced erosion and soil loss by harvesting crops, all of which get little attention compared to rill and sheet erosion. Further research should address those erosional processes and model their impacts (Poesen, 2018). As a follow up action, a working group on gully erosion was established for developing a review of the current status on gully erosion in Europe. In this workshop, the main highlights were also the importance of extreme events (wildfires, intense rainfalls) and the need to better include them in the modelling. In addition, the workshop addressed the importance of soil conservation practices and the need to further incorporate them in policy developments in agriculture. Furthermore, many scientists proposed advanced remote sensing products (Landsat, MODIS) for modelling crop phenology and cover management. Finally, the integration of the erosion models with the carbon cycle for better assessing the impact of soil erosion in agricultural productivity loss and climate change was also addressed. 4. Manuscripts in this special issue The papers in this special issue deal with different aspects of soil erosion modelling and provide an outlook on the ongoing research, potentially contributing to new advancements in better soil protection. The papers included in this special issue are a follow-up to the workshop organised in the Joint Research Centre (Ispra, Italy) in March 2017. Fallout-radionuclides (FRNs) are proven techniques which increase our knowledge about the status and resilience of agro-ecosystems. For this special issue, two studies have investigated new techniques using Caesium-137 (Cs) isotopes and Plutonium 239 + 240 for estimating soil erosion change (Gusarov et al., 2018; Meusburger et al., 2018). In the Russian Steppe, Gusarov et al. (2018) used the Cs isotopes to model the sediment rates and the impact of land use changes in sediment distribution. In the Alpine grasslands, the use of excess Lead-210 (210Pbex)
3. Workshops on soil erosion modelling At an international level, this exponential raise of interest in soil erosion data in policy developments and international organisations over the past 5 years (2015–2019) is considered an opportunity for soil erosion modellers to propose solutions and best practices to reduce soil erosion. The special issue is a follow-up to the soil erosion modelling workshop done in the Joint Research Centre (JRC) of the European 471
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and Plutonium 239 + 240 (239+240Pu) as soil erosion tracers proved more efficient compared to 137CS (Meusburger et al., 2018). Wind erosion affecting mostly arid and semi-arid areas is also an erosional process that should not be ignored (Middleton, 2017). In European Union, a recent quantitative estimate of wind erosion (Borrelli et al., 2017) shows that around 7% of the EU arable lands have rates higher than 2 t ha−1 yr−1. As the Moldavian Plateau in Romania is one of the regions which often has wind erosion incidents, the combination of remote sensing with field observations proved useful in estimating the soil loss and area depositions in arable lands caused by extreme blizzards (Niacsu et al., 2018). Rainfall erosivity is the soil erosion factor that has gained most attention during the last decade and a lot of research has been done to improve the erosivity indexes (Beguería et al., 2018). Slovenia is the European country with highest erosivity values (Bezak et al., 2015; Panagos et al., 2015a). As part of this special issue, Petek et al. (2018) estimated the highest monthly rainfall erosivity in Slovenia during summer in accordance with the European patterns (Ballabio et al., 2017). In addition, adjustments in the rainfall erosivity functions can be applied depending on the local conditions (Petek et al., 2018). Because erosional processes are mainly driven by seasonal climatic fluctuations, agricultural management practices are the appropriate tools for mitigating soil erosion. As cultivated vineyards are among the most erosive agricultural areas (Biddoccu et al., 2018; Panagos et al., 2015b), recent research studies addressed the issue of soil conservation in these precious crops (Rodrigo-Comino, 2018). As part of this special issue, Bagagiolo et al. (2018) reported the positive effect of contouring as a measure to prevent runoff and highlighted the effectiveness of seasonal grass cover in reducing soil erosion. The importance to condition the farmers’ incentives (mainly from the Common Agricultural Policy) for keeping land in a good agricultural condition (GAEC) has been addressed recently in the literature (Borrelli et al., 2016b; Piorr et al., 2009). A recent scenario analysis included in the Impact Assessment of the post 2020 Common Agricultural Policy (European Commission, CAP 2021–2027, 2018) modelled the impact of cover crops in reducing soil erosion on arable lands by up to 15% and on permanent crops by up to 37%. Wildfires and logging are the major causes of soil erosion by water in forestlands (Borrelli et al., 2016a). When reducing or eliminating the vegetation and the ground cover, wildfires make the soil more susceptible to raindrop impact because of sediment detachment and reduction of aggregate stability (Prats et al., 2016). In this special issue, Vieira et al. (2018) compared the ability of three models to predict the hydrological and erosive response and effectiveness of different mulching techniques. The RUSLE model performed better and can designate risk areas of prioritisation while MMF and PESERA models seem more valuable in assessing the risk of water contamination in fireaffecting aquatic ecosystems (Vieira et al., 2018). Estimating soil erosion after fires is a challenge for Mediterranean areas such as Spain, Portugal, South Italy and Greece. In this special issue, Fernández and Vega (2018) used the RUSLE and WEPP models to estimate the soil loss in the first year after a wildfire in 44 experimental field plots in NW Spain. The RUSLE model performed poorly in predicting post-fire loss due to soil erodibility and the reduced capacity to reflect fire-induced changes (Fernández and Vega, 2018). The soil erodibility factor (K-factor) takes into account the soil texture, soil structure, permeability and stoniness; however further research is needed for estimating the K-factor in areas with a high proportion of organic matter in the soil (Panagos et al., 2014b). The performance of the WEPP model in post-fire plots was worst compared to the RUSLE model due to its sensitivity in terms of hydraulic conductivity (Larsen and MacDonald, 2007). In cases of post-fire areas, a soil burn severity sub-factor should be included in soil erosion models (Moody et al., 2013; Fernández and Vega, 2018). In this special issue, there is a comparison of SWAT and AnnAGNPS models for sediment distribution and PESERA and RUSLE models for
soil loss (Abdelwahab et al., 2018). Both SWAT and AnnAGNPS are watershed scale models for estimating the impact of land management on water and sediments. The calibration of the most sensitive hydrological and sediment parameters is a key point for modelling sediment distribution (Malagò et al., 2015). As such, both models have been calibrated and validated at a monthly time interval for hydrology and sediment load using four-year observations for streamflow and suspended sediment concentrations (Abdelwahab et al., 2018). The impact of soil erosion in carbon fluxes is a recent hot topic addressed in the literature (Lal and Pimentel, 2008; Lugato et al., 2016). This special issue includes the first attempt to model the sediment distribution at a European scale using the WaTEM/SEDEM model (Borrelli et al., 2018). The spatially distributed sediment delivery model WaTEM/SEDEM estimates long-term annual rates of soil loss, sediment transfer and deposition (Van Oost et al., 2000; Van Rompaey et al., 2001). Besides the limitations of the model (calibration scheme, unique coefficient of transport capacity, etc.), the sediment delivery ratio (SDR) indicates that the sediment routed down the hillslopes to the river system accounts for 15.3% of the total eroded soil (European scale) (Borrelli et al., 2018). Sediments and phosphorus is an interesting topic in modelling integration. In this special issue, Krasa et al. (2019) estimated the possible phosphorus losses due to water erosion in Czech Republic. The RUSLE model is the most widely applied soil erosion model for estimating rill and sheet erosion (Benavidez et al., 2018). The ability to predict sub-annual soil losses (seasonal erosion modelling) is important for policy making and this special issue includes also a review of the G2 soil erosion model (Karydas and Panagos, 2018). G2 is a complete, quantitative algorithm for mapping soil loss and sediment yield rates at a monthly interval and initially, it has been applied on a regional scale in Crete (Panagos et al., 2014a). G2 has developed its own equations for estimating at monthly scale both the vegetation cover and the management factor including the effect of landscape alterations on erosion (Karydas and Panagos, 2018). Soil erosion is a major land degradation process. Assessing and mapping land degradation is a challenging task of research which requires the evaluation of major soil degradation processes such as water erosion, wind erosion, soil acidification, soil compaction, loss of organic matter and heavy metal intoxication. As part of this special issue, Bednář and Šarapatka (2018) developed a multi-linear regression analysis which takes into account seven physical-geographical factors: slope steepness, altitude, elevation differences, rainfall, temperature, soil texture and solar radiation. This national study in Czech Republic (Bednář and Šarapatka, 2018) together with recent developments in assessing land desertification risk in Romania (Prăvălie et al., 2017) and Greece (Karamesouti et al., 2018) raise the issue of further research for land degradation indexes. 5. Developments and outlook Soil erosion modelling at a large scale is facilitated with recent soil surveys data such as the LUCAS topsoil and remote sensing data. Land Use/Cover Area frame Statistical survey soil (LUCAS Soil) is an extensive and regular topsoil survey (every 3 years) that is carried out across the European Union (EU) in order to assess physical/chemical soil properties and derive policy-relevant statistics related to the effect of land management on soil characteristics (Orgiazzi et al., 2018). The measured physical properties of LUCAS 2009–12 topsoil database facilitated the modelling both of soil erodibility (Panagos et al., 2014b) and wind erodible fraction of soil (Borrelli et al., 2014). As such the continuity and enlargement of LUCAS 2015 in Balkan countries (Albania, Bosnia-Herzegovina, Croatia, Former Yugoslav Republic of Macedonia, Montenegro, and Serbia) and Switzerland may provide new insights for soil erosion. In addition, the visual assessment of soil erosion was carried out at each LUCAS soil sampling location (i.e. ∼26 000 points) during the 2018 campaign (Orgiazzi et al., 2018). The surveyors 472
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provide a qualitative assessment of soil erosion by indicating the type of erosion (i.e. sheet, rill, gully, mass movement, re-deposition and wind erosion), the distance and the direction from the LUCAS point, together with an estimate of the number of rills or gullies observed. In addition to the increased availability of surveyed data, the use of remote sensing data (MODIS, Landsat) plus the outputs from and Copernicus products will facilitate the development of crop dynamics indexes and the proxies for soil coverage (Möller et al., 2017). NDVI time series and other derived products (e.g. vegetation density, fraction of vegetation coverage, leaf area indexes) can assess the spatio-temporal variability of the phenological phases, thus contributing to more accurate modelling and monthly estimates of cover-protection factors, resulting in dynamic soil erosion assessments. The model calibration and validation requests large-scale data collection and data mining of published data concerning soil erosion rates (or even input factors) (Poesen, 2018). As a first step, it is important to review the existing published studies (even in the grey literature) and extract the most relevant information such as soil loss rates, precise location, scale, modelled/measured period, etc. An important step in this direction is the meta-analysis compiled by García-Ruiz et al. (2015). As a follow-up action of the Ispra workshop, starting in autumn 2018, a group of 80 scientists compiled an initial database of local/ regional modelled datasets available in the literature with the utmost objective of using the data gained from model calibration and validation. An important conclusion of the Ispra workshop, also highlighted by Poesen (2018), was the need for further research in other erosional processes such as piping erosion, soil loss by crop harvesting and gully erosion. Based on recent developments in the literature (Vanmaercke et al., 2016) and as a follow up of Ispra workshop, a gully erosion working group targets to model gully erosion at regional and continental scale. In addition, a first gross estimate of soil loss by crop harvesting at European scale has recently presented in the literature (Panagos et al., 2019). The quantification of most important erosion processes (water, wind, soil loss by harvesting crops, gully, tillage erosion, piping, etc.) will further contribute to better assess land degradation in EU. The soil modelling community faces the challenge of improving the exchange of knowledge and data between different soil science disciplines and better integrating it in Earth Science modelling (Vereecken et al., 2016). For example, soil erosion plays an important role in biochemical cycles of C, N and P and also redistributes a significant amount of these elements over the earth's surface (Van Oost et al., 2007). By using a biochemistry-erosion model framework, Lugato et al. (2018) quantified the impact of the future climate in the C cycle at a European scale and concluded that soil erosion is unlikely to be a future carbon sink in Europe. Soil erosion modellers face also the challenge to propose to policy makers specific guidelines to reduce soil erosion taking into account the geographic location, the land use/cover, climate and the funding conditions. Among best practices to reduce erosion, we highlight the prevention of deforestation (also the improper conversion from grassland to cropland), cover crops, buffer strips, reduced tillage, plant residues, terracing in sloppy areas and contour farming. The efficient soil management as one of the main objectives in the future Common Agricultural Policy (CAP) will be implemented with actions to reduce soil erosion and increase soil organic carbon in European agricultural soils. At global scale, the Voluntary Guidelines for Sustainable Soil Management (FAO, 2017) can contribute to minimise soil erosion if they are included in national policies.
research and the excellent publications; (3) the reviewers, for their efforts in providing substantial and helpful comments for the published articles of the special issue. Conflict of interest The authors confirm that there is no conflict of interest with the networks, organisations and data centres referred to in this paper. References Abdelwahab, O.M.M., Ricci, G.F., De Girolamo, A.M., Gentile, F., 2018. Modelling soil erosion in a Mediterranean watershed: comparison between SWAT and AnnAGNPS models. Environ. Res. 166, 363–376. Bagagiolo, G., Biddoccu, M., Rabino, D., Cavallo, E., 2018. Effects of rows arrangement, soil management, and rainfall characteristics on water and soil losses in Italian sloping vineyards. Environ. Res. 166, 690–704. Ballabio, C., Borrelli, P., Spinoni, J., Meusburger, K., Michaelides, S., Beguería, S., Klik, A., Petan, S., Janeček, M., Olsen, P., 2017. Mapping monthly rainfall erosivity in Europe. Sci. Total Environ. 579, 1298–1315. Bednář, M., Šarapatka, B., 2018. Relationships between physical–geographical factors and soil degradation on agricultural land. Environ. Res. 164, 660–668. Beguería, S., Serrano-Notivoli, R., Tomas-Burguera, M., 2018. Computation of rainfall erosivity from daily precipitation amounts. Sci. Total Environ. 637, 359–373. Benavidez, R., Jackson, B., Maxwell, D., Norton, K., 2018. A review of the (Revised) Universal Soil Loss Equation ((R) USLE): with a view to increasing its global applicability and improving soil loss estimates. Hydrol. Earth Syst. Sci. 22, 6059–6086. Bezak, N., Rusjan, S., Petan, S., Sodnik, J., Mikoš, M., 2015. Estimation of soil loss by the WATEM/SEDEM model using an automatic parameter estimation procedure. Environ. Earth Sci. 74, 5245–5261. Biddoccu, M., Zecca, O., Audisio, C., Godone, F., Barmaz, A., Cavallo, E., 2018. Assessment of long‐term soil erosion in a Mountain Vineyard, Aosta Valley (NW Italy). Land Degrad. Dev. 29, 617–629. Borrelli, P., Ballabio, C., Panagos, P., Montanarella, L., 2014. Wind erosion susceptibility of European soils. Geoderma 232, 471–478. Borrelli, P., Lugato, E., Montanarella, L., Panagos, P., 2017. A new assessment of soil loss due to wind erosion in European agricultural soils using a quantitative spatially distributed modelling approach. Land Degrad. Dev. 28, 335–344. Borrelli, P., Panagos, P., Langhammer, J., Apostol, B., Schütt, B., 2016a. Assessment of the cover changes and the soil loss potential in European forestland: first approach to derive indicators to capture the ecological impacts on soil-related forest ecosystems. Ecol. Indic. 60, 1208–1220. Borrelli, P., Paustian, K., Panagos, P., Jones, A., Schütt, B., Lugato, E., 2016b. Effect of good agricultural and environmental conditions on erosion and soil organic carbon balance: a national case study. Land Use Policy 50, 408–421. Borrelli, P., Van Oost, K., Meusburger, K., Alewell, C., Lugato, E., Panagos, P., 2018. A step towards a holistic assessment of soil degradation in Europe: coupling on-site erosion with sediment transfer and carbon fluxes. Environ. Res. 161, 291–298. European Commission - Soil Thematic Strategy, 2006. Thematic Strategy for Soil Protection (COM2006.231). Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of Regions. Brussels. European Commission CAP 2021–2027, 2018. COMMISSION STAFF WORKING DOCUMENT IMPACT ASSESSMENT SWD(2018) 301 final. European Commission, 2011. Roadmap to a Resource Efficient Europe. European Commission, 2018. Sustainable development in the European Union — Monitoring report on progress towards the SDGs in an EU context - 2018 edition. FAO, 2017. Voluntary Guidelines for Sustainable Soil Management. Food and Agriculture Organization of the United Nations, Rome, Italy. Fernández, C., Vega, J.A., 2018. Evaluation of the rusle and disturbed wepp erosion models for predicting soil loss in the first year after wildfire in NW Spain. Environ. Res. 165, 279–285. Ferreira, C.S., Pereira, P., Kalantari, Z., 2018. Human impacts on soil. Sci. Total Environ. 644, 830–834. García-Ruiz, J.M., Beguería, S., Nadal-Romero, E., González-Hidalgo, J.C., Lana-Renault, N., Sanjuán, Y., 2015. A meta-analysis of soil erosion rates across the world. Geomorphology 239, 160–173. Gusarov, A.V., Golosov, V.N., Sharifullin, A.G., 2018. Contribution of climate and land cover changes to reduction in soil erosion rates within small cultivated catchments in the eastern part of the Russian Plain during the last 60 years. Environ. Res. 167, 21–33. Herrick, J.E., Arnalds, O., Bestelmeyer, B., Bringezu, S., Han, G., Johnson, M.V., 2016. Unlocking the sustainable potential of land resources: Evaluation systems, strategies and tools. United Nations Environment Programme. Karamesouti, M., Panagos, P., Kosmas, C., 2018. Model-based spatio-temporal analysis of land desertification risk in Greece. CATENA 167, 266–275. Karydas, C.G., Panagos, P., 2018. The G2 erosion model: an algorithm for month-time step assessments. Environ. Res. 161, 256–267. Keesstra, S.D., Bouma, J., Wallinga, J., Tittonell, P., Smith, P., Cerdà, A., Montanarella, L., Quinton, J.N., Pachepsky, Y., van der Putten, W.H., 2016. The significance of soils and soil science towards realization of the United Nations Sustainable Development Goals. Soil 2, 111–128.
Acknowledgements The Guest editors are thankful to (1) editor in Chief Jose Luis Doming, for the opportunity to host this special issue and to Das Palavi for the technical support; (b) the authors, for the great quality of their 473
Environmental Research 172 (2019) 470–474 Kirkby, M.J., Irvine, B.J., Jones, R.J., Govers, G., team, P., 2008. The PESERA coarse scale erosion model for Europe. I.–Model rationale and implementation. Eur. J. Soil Sci. 59, 1293–1306. Krasa, J., Dostal, T., Jachymova, B., Bauer, M., Devaty, J., 2019. Soil erosion as a source of sediment and phosphorus in rivers and reservoirs–watershed analyses using WaTEM/SEDEM. Environ. Res. 171, 470–483. https://doi.org/10.1016/j.envres. 2019.01.044. Lal, R., Pimentel, D., 2008. Soil erosion: a carbon sink or source? Science 319, 1040–1042. Larsen, I.J., MacDonald, L.H., 2007. Predicting postfire sediment yields at the hillslope scale: testing RUSLE and Disturbed WEPP. Water Resour. Res. 43. Lugato, E., Paustian, K., Panagos, P., Jones, A., Borrelli, P., 2016. Quantifying the erosion effect on current carbon budget of European agricultural soils at high spatial resolution. Glob. Change Biol. 22, 1976–1984. Lugato, E., Smith, P., Borrelli, P., Panagos, P., Ballabio, C., Orgiazzi, A., FernandezUgalde, O., Montanarella, L., Jones, A., 2018. Soil erosion is unlikely to drive a future carbon sink in Europe. Sci. Adv. 4 (eaau3523). Malagò, A., Pagliero, L., Bouraoui, F., Franchini, M., 2015. Comparing calibrated parameter sets of the SWAT model for the Scandinavian and Iberian peninsulas. Hydrol. Sci. J. 60, 949–967. Meusburger, K., Porto, P., Mabit, L., La Spada, C., Arata, L., Alewell, C., 2018. Excess Lead-210 and Plutonium-239+ 240: two suitable radiogenic soil erosion tracers for mountain grassland sites. Environ. Res. 160, 195–202. Middleton, N.J., 2017. Desert dust hazards: a global review. Aeolian Res. 24, 53–63. Möller, M., Gerstmann, H., Gao, F., Dahms, T.C., Förster, M., 2017. Coupling of phenological information and simulated vegetation index time series: limitations and potentials for the assessment and monitoring of soil erosion risk. Catena 150, 192–205. Moody, J.A., Shakesby, R.A., Robichaud, P.R., Cannon, S.H., Martin, D.A., 2013. Current research issues related to post-wildfire runoff and erosion processes. Earth-Sci. Rev. 122, 10–37. Niacsu, L., Sfica, L., Ursu, A., Ichim, P., Bobric, D.E., Breaban, I.G., 2018. Wind erosion on arable lands, associated with extreme blizzard conditions within the hilly area of Eastern Romania. Environ. Res. Orgiazzi, A., Ballabio, C., Panagos, P., Jones, A., Fernández‐Ugalde, O., 2018. LUCAS Soil, the largest expandable soil dataset for Europe: a review. Eur. J. Soil Sci. 69, 140–153. Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., Tadić, M.P., Michaelides, S., Hrabalíková, M., Olsen, P., 2015a. Rainfall erosivity in Europe. Sci. Total Environ. 511, 801–814. Panagos, P., Borrelli, P., Meusburger, K., Alewell, C., Lugato, E., Montanarella, L., 2015b. Estimating the soil erosion cover-management factor at the European scale. Land Use Policy 48, 38–50. Panagos, P., Borrelli, P., Poesen, J., 2019. Soil loss due to crop harvesting in the European Union: a first estimation of an underrated geomorphic process. Sci. Total Environ. 664, 487–498. https://doi.org/10.1016/j.scitotenv.2019.02.009. Panagos, P., Borrelli, P., Poesen, J., Ballabio, C., Lugato, E., Meusburger, K., Montanarella, L., Alewell, C., 2015c. The new assessment of soil loss by water erosion in Europe. Environ. Sci. Policy 54, 438–447. Panagos, P., Imeson, A., Meusburger, K., Borrelli, P., Poesen, J., Alewell, C., 2016. Soil conservation in Europe: wish or reality? Land Degrad. Dev. 27, 1547–1551. Panagos, P., Karydas, C.G., Ballabio, C., Gitas, I.Z., 2014a. Seasonal monitoring of soil erosion at regional scale: an application of the G2 model in Crete focusing on agricultural land uses. Int. J. Appl. Earth Obs. Geoinform. 27, 147–155.
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Panagos, P., Meusburger, K., Ballabio, C., Borrelli, P., Alewell, C., 2014b. Soil erodibility in Europe: a high-resolution dataset based on LUCAS. Sci. Total Environ. 479, 189–200. Petek, M., Mikoš, M., Bezak, N., 2018. Rainfall erosivity in Slovenia: sensitivity estimation and trend detection. Environ. Res. 167, 528–535. Piorr, A., Ungaro, F., Ciancaglini, A., Happe, K., Sahrbacher, A., Sattler, C., Uthes, S., Zander, P., 2009. Integrated assessment of future cap policies: land use changes, spatial patterns and targeting. Environ. Sci. Policy 12, 1122–1136. Poesen, J., 2018. Soil erosion in the anthropocene: research needs. Earth Surf. Process. Landf. 43, 64–84. Prats, S.A., Malvar, M.C., Vieira, D.C.S., MacDonald, L., Keizer, J.J., 2016. Effectiveness of hydromulching to reduce runoff and erosion in a recently burnt pine plantation in central Portugal. Land Degrad. Dev. 27, 1319–1333. Prăvălie, R., Săvulescu, I., Patriche, C., Dumitraşcu, M., Bandoc, G., 2017. Spatial assessment of land degradation sensitive areas in southwestern Romania using modified MEDALUS method. Catena 153, 114–130. Rodrigo-Comino, J., 2018. Five decades of soil erosion research in “terroir”. The state-ofthe-art. Earth-Sci. Rev. Rounsevell, M., Fischer, M., Mader, A., Torre-Marin Rando, A., 2018. IPBES (2018): the IPBES Regional Assessment Report on Biodiversity and Ecosystem Services for Europe and Central Asia. Secretariat of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, Bonn, Germany (892 pages). Scholes, R., Montanarella, L., Brainich, A., Barger, N., Brink, B., Cantele, M., Erasmus, B., Fisher, J., Gardner, T., Holland, T.G., 2018. Summary for Policymakers of the Thematic Assessment Report on Land Degradation and Restoration of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. IPBES Secretariat, Bonn, Germany, pp. 1–31. Van Oost, K., Govers, G., Desmet, P., 2000. Evaluating the effects of changes in landscape structure on soil erosion by water and tillage. Landsc. Ecol. 15, 577–589. Van Oost, K., Quine, T.A., Govers, G., De Gryze, S., Six, J., Harden, J.W., Ritchie, J.C., McCarty, G.W., Heckrath, G., Kosmas, C., 2007. The impact of agricultural soil erosion on the global carbon cycle. Science 318, 626–629. Van Rompaey, A.J., Verstraeten, G., Van Oost, K., Govers, G., Poesen, J., 2001. Modelling mean annual sediment yield using a distributed approach. Earth Surf. Process. Landf. 26, 1221–1236. Vanmaercke, M., Poesen, J., Van Mele, B., Demuzere, M., Bruynseels, A., Golosov, V., Bezerra, J.F.R., Bolysov, S., Dvinskih, A., Frankl, A., 2016. How fast do gully headcuts retreat? Earth-Sci. Rev. 154, 336–355. Vereecken, H., Schnepf, A., Hopmans, J.W., Javaux, M., Or, D., Roose, T., Vanderborght, J., Young, M.H., Amelung, W., Aitkenhead, M., 2016. Modeling soil processes: review, key challenges, and new perspectives. Vadose Zone J. 15. Vieira, D.C.S., Serpa, D., Nunes, J.P.C., Prats, S.A., Neves, R., Keizer, J.J., 2018. Predicting the effectiveness of different mulching techniques in reducing post-fire runoff and erosion at plot scale with the RUSLE, MMF and PESERA models. Environ. Res. 165, 365–378.
Panos Panagos , Athanasios Katsoyiannis European Commission, Joint Research Centre (JRC), Ispra, Italy E-mail address: [email protected] (P. Panagos). ⁎
Corresponding author. 474
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Soil erosion modelling: The new challenges as the result of policy developments in Europe
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ABSTRACT
Keywords: Policy support Science policy interface Sediments Erosivity Wind erosion Wildfires Land degradation
New challenges and policy developments after 2015 (among others, the Common Agricultural Policy (CAP), Sustainable Development Goals (SDGs)) are opportunities for soil scientists and soil erosion modellers to respond with more accurate assessments and solutions as to how to reduce soil erosion and furthermore, how to reach Zero Net Land Degradation targets by 2030. This special issue includes papers concerning the use of fallout for estimating soil erosion, new wind erosion modelling techniques, the importance of extreme events (forest fires, intense rainfall) in accelerating soil erosion, management practices to reduce soil erosion in vineyards, the impact of wildfires in erosion, updated methods for estimating soil erodibility, comparisons between sediment distribution models, the application of the WaTEM/SEDEM model in Europe, a review of the G2 model and a proposal for a land degradation modelling approach. New data produced from field surveys such as LUCAS topsoil and the increasing availability of remote sensing data may facilitate the work of erosion modellers. Finally, better integration with other soil related disciplines (soil carbon, biodiversity, compaction and contamination) and Earth Systems modelling is the way forward for a new generation of erosion process models.
1. Background With the exponential increase of the world population from 1 billion in 1820 to 7 billion in 2012 and projections for 10 billion in 2056, a substantial increase in the demand for food, energy and natural resources (water, air, soil) is expected (Ferreira et al., 2018). Land degradation through human activities is negatively impacting the wellbeing of at least 3.2 billion people and is pushing the planet towards mass extinction affecting a sixth of all species (Scholes et al., 2018). Human activity (deforestation, overgrazing, tillage and unsuitable agricultural practices) and related land use changes are the main reasons for accelerated soil erosion, which has substantial implications for the nutrient and carbon cycle, land productivity and in turn, worldwide socio-economic conditions (Borrelli et al., 2018). According to the Thematic Strategy for the Soil Protection in European Union (EU) (European Commission – Soil Thematic Strategy, 2006), soil erosion by water is the most severe hazard for soils in Europe. It reduces soil productivity and leads to desertification in vulnerable areas (Kirkby et al., 2008). A major policy response is required to reverse the impacts of soil erosion in degraded areas, particularly in light of current climate change and the future water crisis (Panagos et al., 2016). The publication of the new assessment of soil loss by water erosion in Europe (Panagos et al., 2015c) has triggered a scientific discussion of the modelling results and how these can be improved and better used in the policy cycle. The resulting soil erosion maps are used to identify areas where detailed studies are needed and where remedial actions should be implemented. In addition, this modelling development allows for relative spatial and temporal comparisons, a scenario analysis and integration of the erosion model with the carbon cycle. The main objective of this editorial article is to present the recent
policy developments in the Common Agricultural Policy (CAP) and the Sustainable Development Goals (SDGs) and how they can influence the soil erosion modelling. 2. Policy developments and challenges for soil erosion modelling The recent pan-European soil loss by water erosion assessment allows for the development of indicators, maps and reports in support of EU policies such as the Common Agricultural Policy (CAP), the Sustainable Development Goals (SDGs) and the Soil Thematic Strategy (Fig. 1). The UN Sustainable Development Goals (SDGs) explicitly identify soil resources as being of crucial importance for sustainable development and promote the protection of soil resources in order to achieve the ambitious goal of zero land degradation by 2030 (Keesstra et al., 2016). The EU is a front-runner in SDGs and established detailed regular monitoring of SDGs in an EU context by releasing 100 indicators (European Commission, 2018). Soil erosion by water is contributing in monitoring both the SDG2 (zero hanger) and the SDG15 (Life on land). According to the monitoring report on progress towards SDGs in the EU context (European Commission, 2018), more than 201 * 103 Km2 are estimated to be at risk of severe erosion (> 10 t ha−1 yr−1). Even if soil erosion is a major threat for sustainable and productive agricultural systems (in particular for the 140 *103 Km2 with severe erosion), there are signs of improvement across the EU due to mandatory cross-compliance measures in the EU Common Agricultural Policy (CAP), the trends in croplands area decline and the raising of awareness among farmers. The Directorate General Agriculture and Rural development (DG AGRI) of the European Commission is responsible for the implementation of the current EU Common Agricultural Policy (CAP
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Fig. 1. Soil erosion indicators and policy support.
2014–2020) and for the proposal of the future CAP (2021–2017). The sustainable development and efficient management of natural resources (water, soil and air) is one of the 9 key objectives of the future CAP. In addition, the reduction of soil erosion by water is one of the indicators proposed by the European Commission legislative proposal (European Commission, CAP 2021-2027, 2018) in order to monitor the environmental and climatic benefits of the future CAP (Fig. 1). The Roadmap to a Resource-Efficient Europe (European Commission, 2011) sets out a milestone to reduce soil erosion and requires Member States to implement the actions needed to decrease erosion rates. In addition to the agricultural and environmental policies of EU, the current pan-European assessment on soil loss by water erosion is used for various policy reports such as the regional statistics, the EU Agricultural Outlook, and the European Parliament technical reports (Fig. 1). At a global scale, the soil erosion assessment is included in the United Nations Environment Programme (UNEP) report on the sustainable potential of land resources (Herrick et al., 2016) and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) for Europe and Central Asia (Rounsevell et al., 2018). This list of policy organisations and initiatives is not exhaustive as the pan-European soil erosion assessment provides data and indicators to the Food Agricultural Organisation (FAO) and the Organisation for Economic Co-operation and Development (OECD). Recently, FAO has published the Voluntary Guidelines for Sustainable Soil Management (FAO, 2017) with recommendations as to how to minimise risk concerning soil erosion.
Commission, Ispra (Italy) in March 2017. In this workshop, 120 soil scientists and modellers from 28 countries debated future directions for soil erosion modelling. Among others, it was noticed that there are other erosional processes such as gully erosion, tillage erosion, wind erosion, piping erosion, snow induced erosion and soil loss by harvesting crops, all of which get little attention compared to rill and sheet erosion. Further research should address those erosional processes and model their impacts (Poesen, 2018). As a follow up action, a working group on gully erosion was established for developing a review of the current status on gully erosion in Europe. In this workshop, the main highlights were also the importance of extreme events (wildfires, intense rainfalls) and the need to better include them in the modelling. In addition, the workshop addressed the importance of soil conservation practices and the need to further incorporate them in policy developments in agriculture. Furthermore, many scientists proposed advanced remote sensing products (Landsat, MODIS) for modelling crop phenology and cover management. Finally, the integration of the erosion models with the carbon cycle for better assessing the impact of soil erosion in agricultural productivity loss and climate change was also addressed. 4. Manuscripts in this special issue The papers in this special issue deal with different aspects of soil erosion modelling and provide an outlook on the ongoing research, potentially contributing to new advancements in better soil protection. The papers included in this special issue are a follow-up to the workshop organised in the Joint Research Centre (Ispra, Italy) in March 2017. Fallout-radionuclides (FRNs) are proven techniques which increase our knowledge about the status and resilience of agro-ecosystems. For this special issue, two studies have investigated new techniques using Caesium-137 (Cs) isotopes and Plutonium 239 + 240 for estimating soil erosion change (Gusarov et al., 2018; Meusburger et al., 2018). In the Russian Steppe, Gusarov et al. (2018) used the Cs isotopes to model the sediment rates and the impact of land use changes in sediment distribution. In the Alpine grasslands, the use of excess Lead-210 (210Pbex)
3. Workshops on soil erosion modelling At an international level, this exponential raise of interest in soil erosion data in policy developments and international organisations over the past 5 years (2015–2019) is considered an opportunity for soil erosion modellers to propose solutions and best practices to reduce soil erosion. The special issue is a follow-up to the soil erosion modelling workshop done in the Joint Research Centre (JRC) of the European 471
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and Plutonium 239 + 240 (239+240Pu) as soil erosion tracers proved more efficient compared to 137CS (Meusburger et al., 2018). Wind erosion affecting mostly arid and semi-arid areas is also an erosional process that should not be ignored (Middleton, 2017). In European Union, a recent quantitative estimate of wind erosion (Borrelli et al., 2017) shows that around 7% of the EU arable lands have rates higher than 2 t ha−1 yr−1. As the Moldavian Plateau in Romania is one of the regions which often has wind erosion incidents, the combination of remote sensing with field observations proved useful in estimating the soil loss and area depositions in arable lands caused by extreme blizzards (Niacsu et al., 2018). Rainfall erosivity is the soil erosion factor that has gained most attention during the last decade and a lot of research has been done to improve the erosivity indexes (Beguería et al., 2018). Slovenia is the European country with highest erosivity values (Bezak et al., 2015; Panagos et al., 2015a). As part of this special issue, Petek et al. (2018) estimated the highest monthly rainfall erosivity in Slovenia during summer in accordance with the European patterns (Ballabio et al., 2017). In addition, adjustments in the rainfall erosivity functions can be applied depending on the local conditions (Petek et al., 2018). Because erosional processes are mainly driven by seasonal climatic fluctuations, agricultural management practices are the appropriate tools for mitigating soil erosion. As cultivated vineyards are among the most erosive agricultural areas (Biddoccu et al., 2018; Panagos et al., 2015b), recent research studies addressed the issue of soil conservation in these precious crops (Rodrigo-Comino, 2018). As part of this special issue, Bagagiolo et al. (2018) reported the positive effect of contouring as a measure to prevent runoff and highlighted the effectiveness of seasonal grass cover in reducing soil erosion. The importance to condition the farmers’ incentives (mainly from the Common Agricultural Policy) for keeping land in a good agricultural condition (GAEC) has been addressed recently in the literature (Borrelli et al., 2016b; Piorr et al., 2009). A recent scenario analysis included in the Impact Assessment of the post 2020 Common Agricultural Policy (European Commission, CAP 2021–2027, 2018) modelled the impact of cover crops in reducing soil erosion on arable lands by up to 15% and on permanent crops by up to 37%. Wildfires and logging are the major causes of soil erosion by water in forestlands (Borrelli et al., 2016a). When reducing or eliminating the vegetation and the ground cover, wildfires make the soil more susceptible to raindrop impact because of sediment detachment and reduction of aggregate stability (Prats et al., 2016). In this special issue, Vieira et al. (2018) compared the ability of three models to predict the hydrological and erosive response and effectiveness of different mulching techniques. The RUSLE model performed better and can designate risk areas of prioritisation while MMF and PESERA models seem more valuable in assessing the risk of water contamination in fireaffecting aquatic ecosystems (Vieira et al., 2018). Estimating soil erosion after fires is a challenge for Mediterranean areas such as Spain, Portugal, South Italy and Greece. In this special issue, Fernández and Vega (2018) used the RUSLE and WEPP models to estimate the soil loss in the first year after a wildfire in 44 experimental field plots in NW Spain. The RUSLE model performed poorly in predicting post-fire loss due to soil erodibility and the reduced capacity to reflect fire-induced changes (Fernández and Vega, 2018). The soil erodibility factor (K-factor) takes into account the soil texture, soil structure, permeability and stoniness; however further research is needed for estimating the K-factor in areas with a high proportion of organic matter in the soil (Panagos et al., 2014b). The performance of the WEPP model in post-fire plots was worst compared to the RUSLE model due to its sensitivity in terms of hydraulic conductivity (Larsen and MacDonald, 2007). In cases of post-fire areas, a soil burn severity sub-factor should be included in soil erosion models (Moody et al., 2013; Fernández and Vega, 2018). In this special issue, there is a comparison of SWAT and AnnAGNPS models for sediment distribution and PESERA and RUSLE models for
soil loss (Abdelwahab et al., 2018). Both SWAT and AnnAGNPS are watershed scale models for estimating the impact of land management on water and sediments. The calibration of the most sensitive hydrological and sediment parameters is a key point for modelling sediment distribution (Malagò et al., 2015). As such, both models have been calibrated and validated at a monthly time interval for hydrology and sediment load using four-year observations for streamflow and suspended sediment concentrations (Abdelwahab et al., 2018). The impact of soil erosion in carbon fluxes is a recent hot topic addressed in the literature (Lal and Pimentel, 2008; Lugato et al., 2016). This special issue includes the first attempt to model the sediment distribution at a European scale using the WaTEM/SEDEM model (Borrelli et al., 2018). The spatially distributed sediment delivery model WaTEM/SEDEM estimates long-term annual rates of soil loss, sediment transfer and deposition (Van Oost et al., 2000; Van Rompaey et al., 2001). Besides the limitations of the model (calibration scheme, unique coefficient of transport capacity, etc.), the sediment delivery ratio (SDR) indicates that the sediment routed down the hillslopes to the river system accounts for 15.3% of the total eroded soil (European scale) (Borrelli et al., 2018). Sediments and phosphorus is an interesting topic in modelling integration. In this special issue, Krasa et al. (2019) estimated the possible phosphorus losses due to water erosion in Czech Republic. The RUSLE model is the most widely applied soil erosion model for estimating rill and sheet erosion (Benavidez et al., 2018). The ability to predict sub-annual soil losses (seasonal erosion modelling) is important for policy making and this special issue includes also a review of the G2 soil erosion model (Karydas and Panagos, 2018). G2 is a complete, quantitative algorithm for mapping soil loss and sediment yield rates at a monthly interval and initially, it has been applied on a regional scale in Crete (Panagos et al., 2014a). G2 has developed its own equations for estimating at monthly scale both the vegetation cover and the management factor including the effect of landscape alterations on erosion (Karydas and Panagos, 2018). Soil erosion is a major land degradation process. Assessing and mapping land degradation is a challenging task of research which requires the evaluation of major soil degradation processes such as water erosion, wind erosion, soil acidification, soil compaction, loss of organic matter and heavy metal intoxication. As part of this special issue, Bednář and Šarapatka (2018) developed a multi-linear regression analysis which takes into account seven physical-geographical factors: slope steepness, altitude, elevation differences, rainfall, temperature, soil texture and solar radiation. This national study in Czech Republic (Bednář and Šarapatka, 2018) together with recent developments in assessing land desertification risk in Romania (Prăvălie et al., 2017) and Greece (Karamesouti et al., 2018) raise the issue of further research for land degradation indexes. 5. Developments and outlook Soil erosion modelling at a large scale is facilitated with recent soil surveys data such as the LUCAS topsoil and remote sensing data. Land Use/Cover Area frame Statistical survey soil (LUCAS Soil) is an extensive and regular topsoil survey (every 3 years) that is carried out across the European Union (EU) in order to assess physical/chemical soil properties and derive policy-relevant statistics related to the effect of land management on soil characteristics (Orgiazzi et al., 2018). The measured physical properties of LUCAS 2009–12 topsoil database facilitated the modelling both of soil erodibility (Panagos et al., 2014b) and wind erodible fraction of soil (Borrelli et al., 2014). As such the continuity and enlargement of LUCAS 2015 in Balkan countries (Albania, Bosnia-Herzegovina, Croatia, Former Yugoslav Republic of Macedonia, Montenegro, and Serbia) and Switzerland may provide new insights for soil erosion. In addition, the visual assessment of soil erosion was carried out at each LUCAS soil sampling location (i.e. ∼26 000 points) during the 2018 campaign (Orgiazzi et al., 2018). The surveyors 472
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provide a qualitative assessment of soil erosion by indicating the type of erosion (i.e. sheet, rill, gully, mass movement, re-deposition and wind erosion), the distance and the direction from the LUCAS point, together with an estimate of the number of rills or gullies observed. In addition to the increased availability of surveyed data, the use of remote sensing data (MODIS, Landsat) plus the outputs from and Copernicus products will facilitate the development of crop dynamics indexes and the proxies for soil coverage (Möller et al., 2017). NDVI time series and other derived products (e.g. vegetation density, fraction of vegetation coverage, leaf area indexes) can assess the spatio-temporal variability of the phenological phases, thus contributing to more accurate modelling and monthly estimates of cover-protection factors, resulting in dynamic soil erosion assessments. The model calibration and validation requests large-scale data collection and data mining of published data concerning soil erosion rates (or even input factors) (Poesen, 2018). As a first step, it is important to review the existing published studies (even in the grey literature) and extract the most relevant information such as soil loss rates, precise location, scale, modelled/measured period, etc. An important step in this direction is the meta-analysis compiled by García-Ruiz et al. (2015). As a follow-up action of the Ispra workshop, starting in autumn 2018, a group of 80 scientists compiled an initial database of local/ regional modelled datasets available in the literature with the utmost objective of using the data gained from model calibration and validation. An important conclusion of the Ispra workshop, also highlighted by Poesen (2018), was the need for further research in other erosional processes such as piping erosion, soil loss by crop harvesting and gully erosion. Based on recent developments in the literature (Vanmaercke et al., 2016) and as a follow up of Ispra workshop, a gully erosion working group targets to model gully erosion at regional and continental scale. In addition, a first gross estimate of soil loss by crop harvesting at European scale has recently presented in the literature (Panagos et al., 2019). The quantification of most important erosion processes (water, wind, soil loss by harvesting crops, gully, tillage erosion, piping, etc.) will further contribute to better assess land degradation in EU. The soil modelling community faces the challenge of improving the exchange of knowledge and data between different soil science disciplines and better integrating it in Earth Science modelling (Vereecken et al., 2016). For example, soil erosion plays an important role in biochemical cycles of C, N and P and also redistributes a significant amount of these elements over the earth's surface (Van Oost et al., 2007). By using a biochemistry-erosion model framework, Lugato et al. (2018) quantified the impact of the future climate in the C cycle at a European scale and concluded that soil erosion is unlikely to be a future carbon sink in Europe. Soil erosion modellers face also the challenge to propose to policy makers specific guidelines to reduce soil erosion taking into account the geographic location, the land use/cover, climate and the funding conditions. Among best practices to reduce erosion, we highlight the prevention of deforestation (also the improper conversion from grassland to cropland), cover crops, buffer strips, reduced tillage, plant residues, terracing in sloppy areas and contour farming. The efficient soil management as one of the main objectives in the future Common Agricultural Policy (CAP) will be implemented with actions to reduce soil erosion and increase soil organic carbon in European agricultural soils. At global scale, the Voluntary Guidelines for Sustainable Soil Management (FAO, 2017) can contribute to minimise soil erosion if they are included in national policies.
research and the excellent publications; (3) the reviewers, for their efforts in providing substantial and helpful comments for the published articles of the special issue. Conflict of interest The authors confirm that there is no conflict of interest with the networks, organisations and data centres referred to in this paper. References Abdelwahab, O.M.M., Ricci, G.F., De Girolamo, A.M., Gentile, F., 2018. Modelling soil erosion in a Mediterranean watershed: comparison between SWAT and AnnAGNPS models. Environ. Res. 166, 363–376. Bagagiolo, G., Biddoccu, M., Rabino, D., Cavallo, E., 2018. Effects of rows arrangement, soil management, and rainfall characteristics on water and soil losses in Italian sloping vineyards. Environ. Res. 166, 690–704. Ballabio, C., Borrelli, P., Spinoni, J., Meusburger, K., Michaelides, S., Beguería, S., Klik, A., Petan, S., Janeček, M., Olsen, P., 2017. Mapping monthly rainfall erosivity in Europe. Sci. Total Environ. 579, 1298–1315. Bednář, M., Šarapatka, B., 2018. Relationships between physical–geographical factors and soil degradation on agricultural land. Environ. Res. 164, 660–668. Beguería, S., Serrano-Notivoli, R., Tomas-Burguera, M., 2018. Computation of rainfall erosivity from daily precipitation amounts. Sci. Total Environ. 637, 359–373. Benavidez, R., Jackson, B., Maxwell, D., Norton, K., 2018. A review of the (Revised) Universal Soil Loss Equation ((R) USLE): with a view to increasing its global applicability and improving soil loss estimates. Hydrol. Earth Syst. Sci. 22, 6059–6086. Bezak, N., Rusjan, S., Petan, S., Sodnik, J., Mikoš, M., 2015. Estimation of soil loss by the WATEM/SEDEM model using an automatic parameter estimation procedure. Environ. Earth Sci. 74, 5245–5261. Biddoccu, M., Zecca, O., Audisio, C., Godone, F., Barmaz, A., Cavallo, E., 2018. Assessment of long‐term soil erosion in a Mountain Vineyard, Aosta Valley (NW Italy). Land Degrad. Dev. 29, 617–629. Borrelli, P., Ballabio, C., Panagos, P., Montanarella, L., 2014. Wind erosion susceptibility of European soils. Geoderma 232, 471–478. Borrelli, P., Lugato, E., Montanarella, L., Panagos, P., 2017. A new assessment of soil loss due to wind erosion in European agricultural soils using a quantitative spatially distributed modelling approach. Land Degrad. Dev. 28, 335–344. Borrelli, P., Panagos, P., Langhammer, J., Apostol, B., Schütt, B., 2016a. Assessment of the cover changes and the soil loss potential in European forestland: first approach to derive indicators to capture the ecological impacts on soil-related forest ecosystems. Ecol. Indic. 60, 1208–1220. Borrelli, P., Paustian, K., Panagos, P., Jones, A., Schütt, B., Lugato, E., 2016b. Effect of good agricultural and environmental conditions on erosion and soil organic carbon balance: a national case study. Land Use Policy 50, 408–421. Borrelli, P., Van Oost, K., Meusburger, K., Alewell, C., Lugato, E., Panagos, P., 2018. A step towards a holistic assessment of soil degradation in Europe: coupling on-site erosion with sediment transfer and carbon fluxes. Environ. Res. 161, 291–298. European Commission - Soil Thematic Strategy, 2006. Thematic Strategy for Soil Protection (COM2006.231). Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of Regions. Brussels. European Commission CAP 2021–2027, 2018. COMMISSION STAFF WORKING DOCUMENT IMPACT ASSESSMENT SWD(2018) 301 final. European Commission, 2011. Roadmap to a Resource Efficient Europe. European Commission, 2018. Sustainable development in the European Union — Monitoring report on progress towards the SDGs in an EU context - 2018 edition. FAO, 2017. Voluntary Guidelines for Sustainable Soil Management. Food and Agriculture Organization of the United Nations, Rome, Italy. Fernández, C., Vega, J.A., 2018. Evaluation of the rusle and disturbed wepp erosion models for predicting soil loss in the first year after wildfire in NW Spain. Environ. Res. 165, 279–285. Ferreira, C.S., Pereira, P., Kalantari, Z., 2018. Human impacts on soil. Sci. Total Environ. 644, 830–834. García-Ruiz, J.M., Beguería, S., Nadal-Romero, E., González-Hidalgo, J.C., Lana-Renault, N., Sanjuán, Y., 2015. A meta-analysis of soil erosion rates across the world. Geomorphology 239, 160–173. Gusarov, A.V., Golosov, V.N., Sharifullin, A.G., 2018. Contribution of climate and land cover changes to reduction in soil erosion rates within small cultivated catchments in the eastern part of the Russian Plain during the last 60 years. Environ. Res. 167, 21–33. Herrick, J.E., Arnalds, O., Bestelmeyer, B., Bringezu, S., Han, G., Johnson, M.V., 2016. Unlocking the sustainable potential of land resources: Evaluation systems, strategies and tools. United Nations Environment Programme. Karamesouti, M., Panagos, P., Kosmas, C., 2018. Model-based spatio-temporal analysis of land desertification risk in Greece. CATENA 167, 266–275. Karydas, C.G., Panagos, P., 2018. The G2 erosion model: an algorithm for month-time step assessments. Environ. Res. 161, 256–267. Keesstra, S.D., Bouma, J., Wallinga, J., Tittonell, P., Smith, P., Cerdà, A., Montanarella, L., Quinton, J.N., Pachepsky, Y., van der Putten, W.H., 2016. The significance of soils and soil science towards realization of the United Nations Sustainable Development Goals. Soil 2, 111–128.
Acknowledgements The Guest editors are thankful to (1) editor in Chief Jose Luis Doming, for the opportunity to host this special issue and to Das Palavi for the technical support; (b) the authors, for the great quality of their 473
Environmental Research 172 (2019) 470–474 Kirkby, M.J., Irvine, B.J., Jones, R.J., Govers, G., team, P., 2008. The PESERA coarse scale erosion model for Europe. I.–Model rationale and implementation. Eur. J. Soil Sci. 59, 1293–1306. Krasa, J., Dostal, T., Jachymova, B., Bauer, M., Devaty, J., 2019. Soil erosion as a source of sediment and phosphorus in rivers and reservoirs–watershed analyses using WaTEM/SEDEM. Environ. Res. 171, 470–483. https://doi.org/10.1016/j.envres. 2019.01.044. Lal, R., Pimentel, D., 2008. Soil erosion: a carbon sink or source? Science 319, 1040–1042. Larsen, I.J., MacDonald, L.H., 2007. Predicting postfire sediment yields at the hillslope scale: testing RUSLE and Disturbed WEPP. Water Resour. Res. 43. Lugato, E., Paustian, K., Panagos, P., Jones, A., Borrelli, P., 2016. Quantifying the erosion effect on current carbon budget of European agricultural soils at high spatial resolution. Glob. Change Biol. 22, 1976–1984. Lugato, E., Smith, P., Borrelli, P., Panagos, P., Ballabio, C., Orgiazzi, A., FernandezUgalde, O., Montanarella, L., Jones, A., 2018. Soil erosion is unlikely to drive a future carbon sink in Europe. Sci. Adv. 4 (eaau3523). Malagò, A., Pagliero, L., Bouraoui, F., Franchini, M., 2015. Comparing calibrated parameter sets of the SWAT model for the Scandinavian and Iberian peninsulas. Hydrol. Sci. J. 60, 949–967. Meusburger, K., Porto, P., Mabit, L., La Spada, C., Arata, L., Alewell, C., 2018. Excess Lead-210 and Plutonium-239+ 240: two suitable radiogenic soil erosion tracers for mountain grassland sites. Environ. Res. 160, 195–202. Middleton, N.J., 2017. Desert dust hazards: a global review. Aeolian Res. 24, 53–63. Möller, M., Gerstmann, H., Gao, F., Dahms, T.C., Förster, M., 2017. Coupling of phenological information and simulated vegetation index time series: limitations and potentials for the assessment and monitoring of soil erosion risk. Catena 150, 192–205. Moody, J.A., Shakesby, R.A., Robichaud, P.R., Cannon, S.H., Martin, D.A., 2013. Current research issues related to post-wildfire runoff and erosion processes. Earth-Sci. Rev. 122, 10–37. Niacsu, L., Sfica, L., Ursu, A., Ichim, P., Bobric, D.E., Breaban, I.G., 2018. Wind erosion on arable lands, associated with extreme blizzard conditions within the hilly area of Eastern Romania. Environ. Res. Orgiazzi, A., Ballabio, C., Panagos, P., Jones, A., Fernández‐Ugalde, O., 2018. LUCAS Soil, the largest expandable soil dataset for Europe: a review. Eur. J. Soil Sci. 69, 140–153. Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., Tadić, M.P., Michaelides, S., Hrabalíková, M., Olsen, P., 2015a. Rainfall erosivity in Europe. Sci. Total Environ. 511, 801–814. Panagos, P., Borrelli, P., Meusburger, K., Alewell, C., Lugato, E., Montanarella, L., 2015b. Estimating the soil erosion cover-management factor at the European scale. Land Use Policy 48, 38–50. Panagos, P., Borrelli, P., Poesen, J., 2019. Soil loss due to crop harvesting in the European Union: a first estimation of an underrated geomorphic process. Sci. Total Environ. 664, 487–498. https://doi.org/10.1016/j.scitotenv.2019.02.009. Panagos, P., Borrelli, P., Poesen, J., Ballabio, C., Lugato, E., Meusburger, K., Montanarella, L., Alewell, C., 2015c. The new assessment of soil loss by water erosion in Europe. Environ. Sci. Policy 54, 438–447. Panagos, P., Imeson, A., Meusburger, K., Borrelli, P., Poesen, J., Alewell, C., 2016. Soil conservation in Europe: wish or reality? Land Degrad. Dev. 27, 1547–1551. Panagos, P., Karydas, C.G., Ballabio, C., Gitas, I.Z., 2014a. Seasonal monitoring of soil erosion at regional scale: an application of the G2 model in Crete focusing on agricultural land uses. Int. J. Appl. Earth Obs. Geoinform. 27, 147–155.
⁎
Panagos, P., Meusburger, K., Ballabio, C., Borrelli, P., Alewell, C., 2014b. Soil erodibility in Europe: a high-resolution dataset based on LUCAS. Sci. Total Environ. 479, 189–200. Petek, M., Mikoš, M., Bezak, N., 2018. Rainfall erosivity in Slovenia: sensitivity estimation and trend detection. Environ. Res. 167, 528–535. Piorr, A., Ungaro, F., Ciancaglini, A., Happe, K., Sahrbacher, A., Sattler, C., Uthes, S., Zander, P., 2009. Integrated assessment of future cap policies: land use changes, spatial patterns and targeting. Environ. Sci. Policy 12, 1122–1136. Poesen, J., 2018. Soil erosion in the anthropocene: research needs. Earth Surf. Process. Landf. 43, 64–84. Prats, S.A., Malvar, M.C., Vieira, D.C.S., MacDonald, L., Keizer, J.J., 2016. Effectiveness of hydromulching to reduce runoff and erosion in a recently burnt pine plantation in central Portugal. Land Degrad. Dev. 27, 1319–1333. Prăvălie, R., Săvulescu, I., Patriche, C., Dumitraşcu, M., Bandoc, G., 2017. Spatial assessment of land degradation sensitive areas in southwestern Romania using modified MEDALUS method. Catena 153, 114–130. Rodrigo-Comino, J., 2018. Five decades of soil erosion research in “terroir”. The state-ofthe-art. Earth-Sci. Rev. Rounsevell, M., Fischer, M., Mader, A., Torre-Marin Rando, A., 2018. IPBES (2018): the IPBES Regional Assessment Report on Biodiversity and Ecosystem Services for Europe and Central Asia. Secretariat of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, Bonn, Germany (892 pages). Scholes, R., Montanarella, L., Brainich, A., Barger, N., Brink, B., Cantele, M., Erasmus, B., Fisher, J., Gardner, T., Holland, T.G., 2018. Summary for Policymakers of the Thematic Assessment Report on Land Degradation and Restoration of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. IPBES Secretariat, Bonn, Germany, pp. 1–31. Van Oost, K., Govers, G., Desmet, P., 2000. Evaluating the effects of changes in landscape structure on soil erosion by water and tillage. Landsc. Ecol. 15, 577–589. Van Oost, K., Quine, T.A., Govers, G., De Gryze, S., Six, J., Harden, J.W., Ritchie, J.C., McCarty, G.W., Heckrath, G., Kosmas, C., 2007. The impact of agricultural soil erosion on the global carbon cycle. Science 318, 626–629. Van Rompaey, A.J., Verstraeten, G., Van Oost, K., Govers, G., Poesen, J., 2001. Modelling mean annual sediment yield using a distributed approach. Earth Surf. Process. Landf. 26, 1221–1236. Vanmaercke, M., Poesen, J., Van Mele, B., Demuzere, M., Bruynseels, A., Golosov, V., Bezerra, J.F.R., Bolysov, S., Dvinskih, A., Frankl, A., 2016. How fast do gully headcuts retreat? Earth-Sci. Rev. 154, 336–355. Vereecken, H., Schnepf, A., Hopmans, J.W., Javaux, M., Or, D., Roose, T., Vanderborght, J., Young, M.H., Amelung, W., Aitkenhead, M., 2016. Modeling soil processes: review, key challenges, and new perspectives. Vadose Zone J. 15. Vieira, D.C.S., Serpa, D., Nunes, J.P.C., Prats, S.A., Neves, R., Keizer, J.J., 2018. Predicting the effectiveness of different mulching techniques in reducing post-fire runoff and erosion at plot scale with the RUSLE, MMF and PESERA models. Environ. Res. 165, 365–378.
Panos Panagos , Athanasios Katsoyiannis European Commission, Joint Research Centre (JRC), Ispra, Italy E-mail address: [email protected] (P. Panagos). ⁎
Corresponding author. 474