Comparison of different approaches to LS factor calculations based on a measured soil loss under simulated rainfall.

Abstract

Hrabalíková M., Janeček M. (2017) Geographic Information Systems (GIS) in combination with soil loss models can enhance evaluation of soil erosion estimation. SAGA and ARC/INFO geographic information systems were used to estimate the topographic (LS) factor of the Universal Soil Loss Equation (USLE) that in turn was used to calculate the soil erosion on a long-term experimental plot near Prague in the Czech Republic. To determine the influence of a chosen algorithm on the soil erosion estimates a digital elevation model with high accuracy (1 × 1 m) and a measured soil loss under simulated rainfall were used. These then provided input for five GIS-based and two manual procedures of computing the combined slope length and steepness factor in the (R)USLE. The results of GIS-based (R)USLE erosion estimates from the seven procedures were compared to the measured soil loss from the 11 m long experimental plot and from 38 rainfall simulations performed here during 15 years. The results indicate that the GIS-based (R)USLE soil loss estimates from five different approaches to calculation of LS factor are lower than the measured average annual soil loss. The two remaining approaches over-predicted the measured soil loss. The best method for LS factor estimation on field scale is the original manual method of the USLE, which predicted the average soil loss with 6% difference from the measured soil loss. The second method is the GIS-based method that concluded a difference of 8%. The results of this study show the need for further work in the area of soil erosion estimation (with particular focus on the rill/ interrill ratio) using the GIS and USLE. The study also revealed the need for an application of the same approach to catchment area as it might bring different outcomes.

Comparing different multiple flow algorithms to calculate RUSLE factors of slope length (L) and slope steepness (S) in Switzerland

“…agricultural canals, roads, soil furrows, or gullies. Maugnard et al (2013) It could be pointed out that the use of various algorithms for detecting the LS-factor remains a subject of controversial discussions despite numerous new developments, GIS technologies, and better computing capacity (Mitasova et al 2013;Oliveira et al 2013;Hrabalíková and Janeček 2017). Desmet and Govers (1996) stated that the LS values predicted by the GIS method are generally higher by 10-50% than those obtained by manual approach.…”

Estimation of potential soil erosion in the Prosecco DOCG area (NE Italy), toward a soil footprint of bottled sparkling wine production in different land-management scenarios

“…Due to some limitations in estimating LS factor several GIS-modelling techniques were adopted and tested to improve LS estimation [59–62]. To compensate possible overestimation for LS factor we adjusted the slope length (λ), setting the unit contributing area (UCA) on a threshold of 5 ha basin.…”

Understanding Indigenous Farming Systems in Response to Climate Change: An Investigation into Soil Erosion in the Mountainous Regions of Central Vietnam

“…The flow direction algorithm is also an effective tool in determining the LS value [64,65]. Given the necessity of these determining factors, we can conclude that the LS is a sensitive aspect of soil loss prediction by the USLE model [66]. The LS factor is usually limited to a maximum slope angle by 26.6 degrees [67].…”