Modeling aggregate size distribution of eroded sediment resulting from rain-splash and raindrop impacted flow processes.

Autor: Deviren Saygin, Selen, Erpul, Gunay
Zdroj: International Journal of Sediment Research; Apr2019, Vol. 34 Issue 2, p166-177, 12p
Abstrakt: Abstract Soil susceptibility to detachment and transport sub-processes of erosion is generally controled by the aggregate breakdown mechanism. Measuring particle size and aggregation to the estimate erodibility potential of soils is important under erosive rainfall conditions. The Aggregate Size Distribution (ASD) is one of the most important determinants of soil structure along with soil organic matter content for describing the efficiency of applied, sustainable management strategies. This study aimed to compare the performances of three different aggregate size distribution models to predict the characteristic aggregate size parameter (median diameter, D 50) for eroded sediment from interrill erosion processes of Rain-Splash Transport (RST) and Raindrop Impacted Flow Transport (RIFT). The ASDs of 1143 collected sediment samples from the RST and RIFT processes were measured and modeled by the Log-normal, Fractal, and Weibull approaches. The D 50 value, as a characteristic parameter for aggregate size distributions, derived from the cumulative ASD curve was compared for soils from different land use types and different slope and rainfall intensity conditions. The performance of each model was evaluated using the Mean Square Error (MSE) and Coefficient of Determination (R2). The Weibull approach was the most accurate model showing the best fit with the lowest MSE values (0.0002 ≤ MSE ≤ 0.0048) and having the greatest R2 values (0.936 ≤ R2 ≤ 0.998) when compared with the Log-normal and Fractal models. Herewith, for semi-arid land use and soil, specific shape and scale parameters for the Weibull distribution, the respective ASDs were successfully re-generated for modeling the eroded sediment of the simulated RST and RIFT interill processes. [ABSTRACT FROM AUTHOR]
Databáze: Supplemental Index