Modelling soil organic carbon changes under different maize cropping scenarios for cellulosic ethanol in Europe

The utilization of crop residues in the production of second generation biofuels has the potential to boost the bioenergy sector without affecting food commodity prices. However, policies leading to large-scale biomass removal should carefully balance the consequences, both environmental and in terms of emissions, on soil organic carbon (SOC) stocks depletion. Using a recently developed simulation platform, SOC changes were estimated at European level (EU + candidate and potential candidate countries) under two scenarios of low (R30) and high (R90) maize stover removal for cellulosic ethanol production (i.e. 30% and 90% of stover removal, respectively). Additionally, mitigation practices for SOC preservation, namely the introduction of a ryegrass cover crop (R90_C) and biodigestate return to soil (R90_B), were explored under the highest rate of stover removal. The results showed that 15.3 to 50.6 Mt yr-1 of stover (dry matter) would be potentially available for ethanol production under the lower and high removal rates considered. However, large-scale exploitation of maize residues will lead to a SOC depletion corresponding to 39.7 – 135.4 Mt CO2 eq. by 2020 (under R30 and R90, respectively) with greater losses in the long-term. In particular, every tonne of C residue converted to bioethanol was predicted to have an additional impact on SOC loss almost ranging from 0.2-0.5 CO2 eq ha-1 yr-1, considering a continuous biofuel scenario by 2050. The mitigation practices evaluated could more than halve SOC losses compared to R90, but not totally offsetting the negative soil C balance. There is a pressing need to design policies at EU level for optimum maize biofuel cultivations that will preserve the current SOC stock or even generate C credits.JRC.H.5-Land Resources Managemen

Monitoring sediment transfer processes on the desert margin

LANDSAT Thematic Mapper and Multispectral Scanner data have been used to construct change detection images for three playas in south-central Tunisia. Change detection images have been used to analyze changes in surface reflectance and absorption between wet and dry season (intra-annual change) and between different years (inter-annual change). Change detection imagery has been used to examine geomorphological changes on the playas. Changes in geomorphological phenomena are interpreted from changes in soil and foliar moisture levels, differences in reflectances between different salt and sediments and the spatial expression of geomorphological features. Intra-annual change phenomena that can be detected from multidate imagery are changes in surface moisture, texture and chemical composition, vegetation cover and the extent of aeolian activity. Inter-annual change phenomena are divisible into those restricted to marginal playa facies (sedimentation from sheetwash and alluvial fans, erosion from surface runoff and cliff retreat) and these are found in central playa facies which are related to the internal redistribution of water, salt and sediment

Integration of the Soil Database of Turkey into European Soil Database 1:1.000.000

Developing the Version 4 of the Soil Geographical Database at scale 1:1,000,000 aims that providing a harmonised set of soil parameters covering Eurasia and Mediterranean countries for use in agro-meteorological and environmental modelling at regional, national, and continental levels. In this context, the expansion into the Mediterranean Basin will eventually include Turkey. In order to extend the Soil Geographical Database (SGDBE) to the countries of Mediterranean Basin, the preparation of soil geographical database of Turkey at 1:1 million scales was initiated at the end of 2008. In the current report, the reader will be informed about the preparation of soil geographical database of Turkey compatible with European database and how the Turkish soil data have been integrated the European Soil Database. The implementation of this work has been achieved since we have built a common understanding and nomenclature of soils in Europe and Mediterranean region. A number of attributes have been transformed from local/regional/national soil datasets while some other attributes have been obtained from auxiliary datasets using remote sensing and GIS Techniques.JRC.DDG.H.7 - Land management and natural hazard

Soil Sampling Protocol to Certify the Changes of Organic Carbon Stock in Mineral Soils Of European Union - Version 2

The revised second edition of the “Soil Sampling Protocol to Certify the Changes of Organic Carbon Stock in Mineral Soils of European Union” updates the Manual published in 2005. The revision is based on the practical testing in the field. Following numerous comments of the users the revised manual is illustrated by examples of the application of the manual and computation routine.JRC.H.7-Land management and natural hazard

Environmental Assessment of Soil for Monitoring: Volume IIb Survey of National Networks

The ENVASSO Project (Contract 022713) was funded 2006-8, under the European Commission 6th Framework Programme of Research, with the objective of defining and documenting a soil monitoring system appropriate for soil protection at continental level. The ENVASSO Consortium, comprising 37 partners drawn from 25 EU Member States, reviewed almost 300 soil indicators, identified existing soil inventories and monitoring programmes in the Member States, designed and programmed a database management system to capture, store and supply soil profile data, and drafted procedures and protocols appropriate for inclusion in a European soil monitoring network of sites that are geo-referenced and at which a qualified sampling process is or could be conducted. This volume (IIb), a Survey of National Networks, is the second of two reports that together constitute the most comprehensive study to date of the soil inventory and monitoring activities in the European Union. It contains comprehensive fact sheets for each national network, listing the purpose, sampling strategy adopted, analytical methods used and the number of monitoring sites.JRC.H.7-Climate Risk Managemen

LUCAS 2018 - SOIL COMPONENT: Sampling Instructions for Surveyors

The European Commission launched a soil assessment component to the periodic LUCAS Land Use/Land Cover Area Frame Survey in 2009. Composite soil samples from 0-20-cm depth were taken, air-dried and sieved to 2 mm in order to analyse physical and chemical parameters of topsoil in 25 Member States (EU-27 except Bulgaria, Romania, Malta and Cyprus). The aim of the LUCAS Soil Component was to create a harmonised and comparable dataset of main properties of topsoil at the EU. The LUCAS Soil Component was extended to Bulgaria and Romania in 2012. Overall, ca. 22,000 soil samples were collected and analysed. All samples were analysed for percentage of coarse fragments, particle-size distribution, pH, organic carbon, carbonates, phosphorous, total nitrogen, extractable potassium, cation exchange capacity, multispectral properties and heavy metals. In 2015, the soil sampling was repeated in the same set of points of LUCAS 2009/2012 to monitor changes in topsoil physical and chemical parameters across the EU. The soil component was extended to points above elevations of 1000 m, which were not sampled in LUCAS 2009/2012. Furthermore, soil samples were taken in Albania, Bosnia-Herzegovina, Croatia, Macedonia, Montenegro, Serbia and Switzerland. The soil sampling was carried out following the instructions already used in LUCAS 2009/2012. Approximately 27,000 samples were collected and will be analysed during 2016 and 2017. In 2018, a new soil sampling campaign will be carried out within the LUCAS framework. Soil samples will be taken in repeated points of LUCAS 2009/2012 and LUCAS 2015. The novelty of the survey is that new physical, chemical and biological parameters will be analysed. Key parameters for evaluating soil quality, such as bulk density and soil biodiversity, will be analysed. These analyses require specific methods of soil sampling, preparation and storage of samples. Furthermore, field measurements such as the thickness of organic layer in peat soils, and visual assessment of signs of soil erosion will be carried out in 2018. This technical report compiles the instructions for collecting the various soil samples and for performing field measurements in the soil survey of 2018. These instructions will be used for all LUCAS surveyors, to create a comparable database of soil characteristics all over Europe.JRC.D.3-Land Resource

Soils of the European Union

This report make a detailed summary of the soil resources of the EU. Contents: Acknowledgements 2 1. Introduction 3 2. Materials and methods 4 2.1 Soil Geographical Database of Eurasia at scale 1:1,000,000 (SGDBE) 4 2.2 Nomenclature of soil types 6 2.3 Map legend and representation 6 3. Soils of the European Union: an overview 8 4. Spatial distribution of the major soils in the European Union 11 4.1 Acrisols 11 4.2 Albeluvisols 13 4.3 Andosols 15 4.4 Anthrosols 17 4.5 Arenosols 19 4.6 Calcisols 21 4.7 Cambisols 23 4.8 Chernozems 25 4.9 Fluvisols 27 4.10 Gleysols 29 4.11 Gypsisols 31 4.12 Histosols 33 4.13 Kastanozems 35 4.14 Leptosols 37 4.15 Luvisols 39 4.16 Phaeozems 41 4.17 Planosol 43 4.18 Podzols 45 4.19 Regosols 47 4.20 Solonchaks 49 4.21 Solonetz 51 4.22 Umbrisols 53 4.23 Vertisols 55 5. Concluding remarks 57 References 58 Appendix 1. 59 Appendix 2. 62JRC.H.7-Land management and natural hazard

An Innovative Approach for Updating Soil Information Based on Digital Soil Mapping Techniques

In most part of the world the information on the thematic soil maps (soil erosion, soil degradation, soil organic matter content etc.) are developed as a tool for policy and management support. This information are typically derived through expert interpretation or empirical modeling approaches using typically decades old soil information originating from field investigation, laboratory analysis, reports etc. In recent period, there is a strong emphasis to update the existing soil information in a cost-effective and accurate manner. The advancements in the emerging Geographical Information System (GIS) and digital soil mapping techniques are found to be supportive enough to derive tools addressing the above mentioned problem. In this study, we propose a novel innovative approach to address the issues on evaluating the traditional soil maps and updating the existing soil information based on the principles of digital soil mapping i.e. deriving objective soil information by reformulating the relationships between soil and its environment using ancillary and minimal datasets. The new approach is called as “SEIMS network” (Soil and Environment Interaction based Mapping System). The SEIMS network is a Data Mining and Knowledge Discovery (KDD) based method derived by fusing GIS, DSM techniques along with working principle of the DRIS approach. This approach provides a scheme to transform and update the less detailed, discrete and subjectively derived soil information into a continuous, non-subjective and quantitative spatial datasets. The study was tested on the soil erosion map of Tamil Nadu region, southern part of Indian Peninsula. The SEIMS network attempts to reformulate the soil erosion map of Tamil Nadu region and redefine the contours by spreading back the knowledge acquired from the relationship among the soil and its environmental variables used as predictors in the system. The variables like temperature, rainfall, potential evapotranspiration, rainfall seasonality, land cover percentage (derived from MODIS spectral bands), soil crusting, soil erodibility, top soil organic carbon content, altitude and slope that are having major influence on soil erosion were chosen as predictors for characterizing the relationship among the variables on the context of soil erosion process. The test on the efficiency of the SEIMS network’s capability to extrapolate and derive the target soil information using the weights derived from the ancillary datasets was performed over established soil erosion map of Europe. The erosion index value derived through SEIMS network scheme exhibited a better correlation with PESERA soil erosion estimates (r2 = 0.81), thereby proving its ability to mimic and characterize the soil erosion process by studying the complex interrelationship among the environmental variables. The weights derived for prediction are mathematically unique, thereby holds scope for further elaboration on its application to derive a tool, addressing the upscaling and downscaling issues in digital soil mapping. The flexibility and reproducibility are the main advantages visualized for this approach. Moreover, the results are objective and easy for interpretation. This study demonstrated that the SEIMS network as a promising tool in digital soil mapping to evaluate and update the existing soil information with minimal ancillary datasets.JRC.H.7 - Land management and natural hazard