Global rainfall erosivity database (GloREDa) and monthly R-factor data at 1 km spatial resolution.

Here, we present and release the Global Rainfall Erosivity Database (GloREDa), a multi-source platform containing rainfall erosivity values for almost 4000 stations globally. The database was compiled through a global collaboration between a network of researchers, meteorological services and environmental organisations from 65 countries. GloREDa is the first open access database of rainfall erosivity (R-factor) based on hourly and sub-hourly rainfall records at a global scale. This database is now stored and accessible for download in the long-term European Soil Data Centre (ESDAC) repository of the European Commission's Joint Research Centre. This will ensure the further development of the database with insertions of new records, maintenance of the data and provision of a helpdesk. In addition to the annual erosivity data, this release also includes the mean monthly erosivity data for 94% of the GloREDa stations. Based on these mean monthly R-factor values, we predict the global monthly erosivity datasets at 1 km resolution using the ensemble machine learning approach (ML) as implemented in the mlr package for R. The produced monthly raster data (GeoTIFF format) may be useful for soil erosion prediction modelling, sediment distribution analysis, climate change predictions, flood, and natural disaster assessments and can be valuable inputs for Land and Earth Systems modelling.

EUSEDcollab: a network of data from European catchments to monitor net soil erosion by water.

As a network of researchers we release an open-access database (EUSEDcollab) of water discharge and suspended sediment yield time series records collected in small to medium sized catchments in Europe. EUSEDcollab is compiled to overcome the scarcity of open-access data at relevant spatial scales for studies on runoff, soil loss by water erosion and sediment delivery. Multi-source measurement data from numerous researchers and institutions were harmonised into a common time series and metadata structure. Data reuse is facilitated through accompanying metadata descriptors providing background technical information for each monitoring station setup. Across ten European countries, EUSEDcollab covers over 1600 catchment years of data from 245 catchments at event (11 catchments), daily (22 catchments) and monthly (212 catchments) temporal resolution, and is unique in its focus on small to medium catchment drainage areas (median = 43 km2, min = 0.04 km2, max = 817 km2) with applicability for soil erosion research. We release this database with the aim of uniting people, knowledge and data through the European Union Soil Observatory (EUSO).

Improving the phosphorus budget of European agricultural soils.

Despite phosphorus (P) being crucial for plant nutrition and thus food security, excessive P fertilization harms soil and aquatic ecosystems. Accordingly, the European Green Deal and derived strategies aim to reduce P losses and fertilizer consumption in agricultural soils. The objective of this study is to calculate a soil P budget, allowing the quantification of the P surpluses/deficits in the European Union (EU) and the UK, considering the major inputs (inorganic fertilizers, manure, atmospheric deposition, and chemical weathering) and outputs (crop production, plant residues removal, losses by erosion) for the period 2011-2019. The Land Use/Cover Area frame Survey (LUCAS) topsoil data include measured values for almost 22,000 samples for both available and total P. With advanced machine learning models, we developed maps for both attributes at 500 m resolution. We estimated the available P for crops at a mean value of 83 kg ha-1 with a clear distinction between North and South. The ratio of available P to the total P is about 1:17. The inorganic fertilizers and manure contribute almost equally as P inputs (mean 16 ± 2 kg P ha-1 yr-1 at 90 % confidence level) to agricultural soils, with high regional variations depending on farming practices, livestock density, and cropping systems. The P outputs came mainly from the exportation by the harvest of crop products and residues (97.5 %) and, secondly, by erosion. Using a sediment distribution model, we quantified the P fluxes to river basins and sea outlets. In the EU and UK, we estimated an average surplus of 0.8 kg P ha-1 yr-1 with high variability between countries with some regional variations. The P annual budget at regional scale showed ample possibility to improve P management by both reducing inputs in regions with high surplus (and P soil available) and rebalancing fertilization in those at risk of soil fertility depletion.

Mercury in European topsoils: Anthropogenic sources, stocks and fluxes.

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.