No abstract

The exposure of the Earth’s surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha−1 h−1 yr−1, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.

Worldwide regulatory frameworks for the assessment and remediation of contaminated soils have moved towards a risk-based approach, taking contaminant bioavailability into consideration. However, there is much debate on the precise definition of bioavailability and on the standardization of methods for the measurement of bioavailability so that it can be reliably applied as a tool for risk assessment. Therefore, in this paper, we reviewed the existing definitions of heavy metal bioavailability in relation to plant uptake (phytoavailability), in order to better understand both the conceptual and operational aspects of bioavailability. The related concepts of specific and non-specific adsorption, as well as complex formation and organic ligand affinity were also intensively discussed to explain the variations of heavy metal solubility and mobility in soils. Further, the most frequently used methods to measure bioavailable metal soil fractions based on both chemical extractions and mechanistic geochemical models were reviewed. For relatively highly mobile metals (Cd, Ni, and Zn), a neutral salt solution such as 0.01 M CaCl2 or 1 M NH4NO3 was recommended, whereas a strong acid or chelating solution such as 0.43 M HNO3 or 0.05 M DTPA was recommended for strongly soil-adsorbed and less mobile metals (Cu, Cr, and Pb). While methods which assessed the free metal ion activity in the pore water such as DGT and DMT or WHAM/Model VI, NICA-Donnan model, and TBLM are advantageous for providing a more direct measure of bioavailability, few of these models have to date been properly validated.

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.

No abstract