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.
Vegetation can significantly contribute to stabilise sloping terrain by adding cohesion to soil: this reinforcement depends on the morphological characteristics of the root systems and the tensile strength of single roots. The paper presents the results of research carried out in order to evaluate the biotechnical characteristics of the root system of three typical Mediterranean plant species which can affect slope stability. The species considered in the present study are Lygeum spartum L. (a perennial herbaceous monocotyledonous), Atriplex halimus L. and Pistacia lentiscus L. (two dicotyledonous shrub species). The plant specimens were collected in the Basilicata region (Southern Italy) by in situ excavation to obtain the whole root systems. Single root specimens for each species were sampled and tested for tensile strength measurement, and the complete root systems were analysed to evaluate the root density distribution with depth in terms of Root Area Ratio. The resulting data have been used to calculate the reinforcing effect in terms of increased shear strength of the soil using the model of Wu (1976, Investigation of landslides on Prince of Wales Island. Geotech. Eng. Rep. 5 Civil Eng. Dep. Ohio State Univ. Columbus, Ohio, USA) and Waldron (1977, Soil Sci. Soc. Am. J. 41(3), 843-849), a simple and widespread model based on the reinforced earth theory. The results show that root reinforcement exerted by L. spartum is stronger than the reinforcement exerted by P. lentiscus and A. halimus in the upper layers of the soil, while P. lentiscus presents higher reinforcement values in deeper horizons. A. halimus presents lower values than either of the other species studied.
In this paper, the Annualized Agricultural Non-Point Source (AnnAGNPS) model has been used to estimate runoff, peak discharge and sediment load at the event scale in a Mediterranean watershed. The study area is the Carapelle torrent, Southern Italy (area = 506 km 2 ), where continuous rainfall, streamflow and sediment load data are available. Nineteen flood events have been registered in the period 2007-2009 and were used for the application of the model.The aim of the paper is to evaluate the predictive accuracy of the model at the event scale, in a medium-size watershed, given the specific conditions of the semi-arid environments. A sensitivity analysis has been carried out to assign the correct parameterization: the mean normalized output variation of the most meaningful input parameters pointed out the influence of the curve number on runoff, peak discharge and sediment load predictions (values greater than 1); the MN Manning's roughness coefficient and K, C and P factors of the universal soil loss equation showed a moderate influence on sediment load simulations (values between 0Á5 and 1).The selection of the Soil Conservation Service synthetic storm types has been based on the observed storm events analysis to improve the peak discharge simulations. The model prediction has proved to be good for runoff (R 2 = 0Á74, NSE = 0Á75, W = 0Á92) and peak discharge (R 2 = 0Á85, NSE = 0Á70, W = 0Á94), and satisfactory for sediment yield (R 2 = 0Á70, NSE = 0Á63, W = 0Á91). The relative error is lower for high events; this result is quite interesting in semi-arid environments, where most of the annual sediment yield is concentrated in a few, severe events.
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