Human activity and related land use change are the primary cause of accelerated soil erosion, which has substantial implications for nutrient and carbon cycling, land productivity and in turn, worldwide socio-economic conditions. Here we present an unprecedentedly high resolution (250 × 250 m) global potential soil erosion model, using a combination of remote sensing, GIS modelling and census data. We challenge the previous annual soil erosion reference values as our estimate, of 35.9 Pg yr−1 of soil eroded in 2012, is at least two times lower. Moreover, we estimate the spatial and temporal effects of land use change between 2001 and 2012 and the potential offset of the global application of conservation practices. Our findings indicate a potential overall increase in global soil erosion driven by cropland expansion. The greatest increases are predicted to occur in Sub-Saharan Africa, South America and Southeast Asia. The least developed economies have been found to experience the highest estimates of soil erosion rates.

This book summarises the main results of many contributions from researchers worldwide who have used the water infiltration process to characterize soil in the field. Determining soil hydrodynamic properties is essential to interpret and simulate the hydrological processes of economic and environmental interest. This book can be used as a guide to soil hydraulic characterization and in addition it gives a complete description of the treated techniques, including an outline of the most significant research results, with the main points that still needing development and improvement

Simplified measurements of the field‐saturated hydraulic conductivity, Kfs, require short duration experiments, small water volumes, and easily transportable equipment. A simplified falling‐head (SFH) technique for the rapid determination of Kfs has been developed and tested. The technique consists in applying a small volume of water on a soil surface, confined by a ring inserted a short distance into the soil, and then measuring the time from the application of water to the instant at which the surface area is no longer covered by water. A measurement of the initial and field‐saturated soil water contents, and an estimate of the α* parameter of the Gardner's exponential model are then used to calculate Kfs using a simple solution that includes gravity. The Kfs of both repacked and undisturbed soil cores was determined in the laboratory by the SFH and the early time constant‐head (ECH) techniques. The SFH and (constant‐head) pressure infiltrometer (PI) techniques were then compared in the field. The maximum discrepancy between the mean Kfs results obtained within an experiment was of a factor of approximately two. This difference is negligible in most practical applications and it was concluded that the SFH technique compared favorably with the ECH technique in the laboratory and to the PI technique in the field. The SFH technique appears promising for determining Kfs in a relatively short period of time without the need for extensive instrumentation or analytical methodology, and therefore it appears suitable for detailed field measurements over large areas.

Methods for predicting unit plot soil loss for the 'Sparacia' Sicilian (Southern Italy) site were developed using 316 simultaneous measurements of runoff and soil loss from individual bare plots varying in length from 11 to 44 m. The event unit plot soil loss was directly proportional to an erosivity index equal to (QREI30)1.47, being QREI30 the runoff ratio (QR) times the single storm erosion index (EI30). The developed relationship represents a modified version of the USLE-M, and therefore it was named USLE-MM. By the USLE-MM, a constant erodibility coefficient was deduced for plots of different lengths, suggesting that in this case the calculated erodibility factor is representative of an intrinsic soil property. Testing the USLE-M and USLE-MM schemes for other soils and developing simple procedures for estimating the plot runoff ratio has practical importance to develop a simple method to predict soil loss from bare plots at the erosive event temporal scale

Field-saturated soil hydraulic conductivity, Kfs, is highly variable. Therefore, interpreting and simulating hydrological processes,\ud such as rainfall excess generation, need a large number of Kfs data even at the plot scale. Simple and reasonably rapid\ud experiments should be carried out in the field. In this investigation, a simple infiltration experiment with a ring inserted shortly\ud into the soil and the estimation of the so-called a* parameter allowed to obtain an approximate measurement of Kfs. The\ud theoretical approach was tested with reference to 149 sampling points established on Burundian soils. The estimated Kfs with the\ud value of first approximation of a* for most agricultural field soils (a* = 0.012mm_1) differed by a practically negligible\ud maximum factor of two from the saturated conductivity obtained by the complete Beerkan Estimation of Soil Transfer parameters\ud (BEST) procedure for soil hydraulic characterization. The measured infiltration curve contained the necessary information to\ud obtain a site-specific prediction of a*. The empirically derived a* relationship gave similar results for Kfs (mean = 0.085mms_1;\ud coefficient of variation (CV) = 71%) to those obtained with BEST (mean = 0.086mms_1; CV = 67%), and it was also successfully\ud tested with reference to a few Sicilian sampling points, since it yielded a mean and a CV of Kfs (0.0094mms_1 and 102%,\ud respectively) close to the values obtained with BEST (mean = 0.0092mms_1; CV = 113%). The developed method appears\ud attractive due to the extreme simplicity of the experiment

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Abstract:Obtaining good quality soil loss data from plots requires knowledge of the factors that affect natural and measurement data variability and of the erosion processes that occur on plots of different sizes. Data variability was investigated in southern Italy by collecting runoff and soil loss from four universal soil-loss equation (USLE) plots of 176 m 2 , 20 'large' microplots (0Ð16 m 2 and 40 'small' microplots (0Ð04 m 2 . For the four most erosive events (event erosivity index, R e ½ 139 MJ mm ha 1 h 1 , mean soil loss from the USLE plots was significantly correlated with R e . Variability of soil loss measurements from microplots was five to ten times greater than that of runoff measurements. Doubling the linear size of the microplots reduced mean runoff and soil loss measurements by a factor of 2Ð6-2Ð8 and increased data variability. Using sieved soil instead of natural soil increased runoff and soil loss by a factor of 1Ð3-1Ð5. Interrill erosion was a minor part (0Ð1-7Ð1%) of rill plus interrill erosion. The developed analysis showed that the USLE scheme was usable to predict mean soil loss at plot scale in Mediterranean areas. A microplot of 0Ð04 m 2 could be used in practice to obtain field measurements of interrill soil erodibility in areas having steep slopes.