soil loss
Recently Published Documents





2022 ◽  
Vol 210 ◽  
pp. 105872
Arika Bridhikitti ◽  
Pajanun Ruamchalerm ◽  
Mathawut Keereesuwannakul ◽  
Thayukorn Prabamroong ◽  
Gaohuan Liu ◽  

2022 ◽  
Vol 218 ◽  
pp. 105292
Sanghyun Lee ◽  
Maria L. Chu ◽  
Jorge A. Guzman ◽  
Dennis C. Flanagan

2022 ◽  
Vol 211 ◽  
pp. 105972
Kaushal K. Garg ◽  
K.H. Anantha ◽  
Sreenath Dixit ◽  
Rajesh Nune ◽  
A. Venkataradha ◽  

2022 ◽  
Legese Abebaw Getu ◽  
Attila Nagy ◽  
Hailu Kendie Addis

Abstract AbstractBackground: Soil erosion is the most serious problem that affects economic development, food security, and ecosystem services which is the main concern in Ethiopia. This study focused on quantifying soil erosion rate and severity mapping of the Megech watershed for effective planning and decision-making processes to implement protection measures. The RUSLE model integrated with ArcGIS software was used to conduct the present study. The six RUSLE model parameters: erosivity, erodibility, slope length and steepness, cover management, and erosion control practices were used as input parameters to predict the average annual soil loss and identify erosion hotspots in the watershed. Results: The RUSLE estimated 1,399,210 tons yr-1 total soil loss from the watershed with a mean annual soil loss of 32.84 tons ha-1yr-1. The soil erosion rate was varied from 0.08 to greater than 500 tons ha-1yr-1. A severity map with seven severity classes was created for 27 sub-watersheds: low (below 10), moderate (10-20), high (20-30), very high (30-35), severe (35-40), very severe (40-45) and extremely severe (above 45) in which the values are in tons ha-1yr-1. The area coverage was 6.5%, 11.1%, 8.7%, 22%, 30.9%, 13.4%, and 7.4% for low, moderate, high, very high, severe, very severe, and extremely severe erosion classes respectively. Conclusion: About 82 % of the watershed was found in more than the high-risk category which reflects the need for immediate land management action. This paper could be important for decision-makers to prioritize critical erosion hotspot areas for comprehensive and sustainable management of the watershed.

2022 ◽  
Vol 14 (2) ◽  
pp. 348
Yashon O. Ouma ◽  
Lone Lottering ◽  
Ryutaro Tateishi

This study presents a remote sensing-based index for the prediction of soil erosion susceptibility within railway corridors. The empirically derived index, Normalized Difference Railway Erosivity Index (NDReLI), is based on the Landsat-8 SWIR spectral reflectances and takes into account the bare soil and vegetation reflectances especially in semi-arid environments. For the case study of the Botswana Railway Corridor (BRC), the NDReLI results are compared with the RUSLE and the Soil Degradation Index (SDI). The RUSLE model showed that within the BRC, the mean annual soil loss index was at 0.139 ton ha−1 year−1, and only about 1% of the corridor area is susceptible to high (1.423–3.053 ton ha−1 year−1) and very high (3.053–5.854 ton ha−1 year−1) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57–1.65 μm) predicted the most vulnerable areas, with a very high erosivity index (0.36–0.95), while SWIR2 (2.11–2.29 μm) predicted the same regions at a high erosivity index (0.13–0.36). From empirical validation using previous soil erosion events within the BRC, the proposed NDReLI performed better that the RUSLE and SDI models in the prediction of the spatial locations and extents of susceptibility to soil erosion within the BRC.

2022 ◽  
Vol 174 ◽  
pp. 106464
Kirsten Ellis ◽  
Rosmarie Lohnes ◽  
Jeremy Lundholm

Sign in / Sign up

Export Citation Format

Share Document