USLE K-Factor Method Selection for a Tropical Catchment

Abstract

The use of the Universal Soil Loss Equation (USLE) and the Sediment Delivery Ratio (SDR) facilitates sediment yield (SY) estimates in watersheds. However, the soil loss predictions are frequently unrealistic because of the methods used to estimate the USLE’s factors. Here, we evaluated the performance of methods to estimate the soil erodibility (K-factor) and the influence of its estimation in the SY predictions. K-factor values were obtained from three widely used equations and using a portable rainfall simulator. These values were used to compute annual average soil loss and SY in a tropical watershed. We compared SY estimates with a 15-month observed sediment discharge dataset sampled in the catchment outlet. The most reliable method for the K-factor estimating was the USLE nomograph. Furthermore, our results indicate that the use of a portable rainfall simulator to estimate the K-factor tends to underestimate soil loss and sediment delivery.

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

“…Soil texture and soil organic matter content are often used for the measurement of the K factor [55,56]. The information needed to acquire these soil indicators is dependent on K identification.…”

Effects of DEM resolution on the RUSLE-LS factor and its implications on soil and water management policies through the land cover seasonality

“…This factor can be estimated by different methodologies. According to Marques et al (2019), one of the alternatives to measure the K factor is from direct measurements in experimental fields under natural or simulated rain, however, under these conditions the estimate becomes costly and time-consuming, even considering the standard method (Lin et al, 2019). Besides this methodology, erodibility can be estimated using pedotransfer function, which uses multiple regression models (Young and Mutchler, 1977;Bertoni and Lombardi Neto, 2005;Marques et al, 2019).…”

“…According to Marques et al (2019), one of the alternatives to measure the K factor is from direct measurements in experimental fields under natural or simulated rain, however, under these conditions the estimate becomes costly and time-consuming, even considering the standard method (Lin et al, 2019). Besides this methodology, erodibility can be estimated using pedotransfer function, which uses multiple regression models (Young and Mutchler, 1977;Bertoni and Lombardi Neto, 2005;Marques et al, 2019). On the other hand, Marques et al (2019) report that for countries like Brazil, the determination of this parameter is hampered by costs and, therefore, the use of predefined values for some soil classes are commonly used (Beskow et al, 2009).…”

A geomorphodiversity map of the Soutpansberg Range, South Africa

“…Though there are other formulae such as USLE (Wischmeier, Smith 1978) and SLEMSA (Elwell 1978) that use different parameters to calculate the K factor, Bouyoucos' method was chosen because it has proved to efficiently match field data (Anache et al 2015, Marques et al 2019) in addition to its simplicity to use in a GIS. Therefore, the K factor was the focus in rasterising the soil shape file.…”